Alfredo Vellido / citations 

 

 

Vellido, A., (2006) Missing data imputation through GTM as a mixture of t-distributions. Neural Networks, Neural Networks, 19(10), 1624-1635.

1. [SELF-CITATION] On the improvement of brain tumour data clustering using class information. In Proc. of the 3rd European Starting AI Researcher Symposium (STAIRS'06), Riva del Garda, Italy.
Cruz, R., Vellido, A.

Andrade, A.O. and Vellido, A. (2006) Determining feature relevance for the grouping of motor unit action potentials through Generative Topographic Mapping. In Proc. of the IASTED 25th Int. Conf. Modelling, Identification, and Control, MIC’06, Lanzarote, Spain, 2006, 507-512.

1. [SELF-CITATION] Assessment of an Unsupervised Feature Selection Method for Generative Topographic Mapping, In Proc. of the 16th International Conference on Artificial Neural Networks (ICANN 2006), Athens, Greece.
Vellido, A.

Vellido, A., Lisboa, P.J.G. and Vicente, D. (2006) Robust analysis of MRS brain tumour data using t-GTM. Neurocomputing, 69(7-9), March 2006, 754-768.
 

1. [SELF-CITATION] Determining feature relevance for the grouping of motor unit action potentials through Generative Topographic Mapping.

In Proc. of the IASTED 25th Int. Conf. Modelling, Identification, and Control, MIC’06, Lanzarote, Spain, 2006, 507-512.  

Andrade, A.O. and Vellido, A.

2. [SELF-CITATION] Characterization of atypical virtual campus usage behavior through robust generative relevance analysis,

In Proc. of the 5th IASTED Int. Conf. on Web-Based Education (WBE 2006), Puerto Vallarta, México, 2006, 183-188.

Vellido, A., Castro, F., Nebot, A., and Múgica, F.

3. [SELF-CITATION] Assessment of an Unsupervised Feature Selection Method for Generative Topographic Mapping, In Proc. of the 16th International Conference on Artificial Neural Networks (ICANN 2006), Athens, Greece.  

Vellido, A.

 

Vellido, A. and Lisboa, P.J.G. (2006) Handling outliers in brain tumour MRS data analysis through robust topographic mapping, Computers in Biology and Medicine, In press.

1. [SELF-CITATION] Determining feature relevance for the grouping of motor unit

action potentials through Generative Topographic Mapping. In Procs. Of the IASTED 25th

Int. Conf. Modelling, Identification, and Control, MIC’06, Lanzarote, Spain, 2006, 507-512.  

Andrade, A.O. and Vellido, A.

 

Vellido, A., Castro, F., Nebot, A., and Múgica, F., (2006) Characterization of atypical virtual campus usage behavior through robust generative relevance analysis, In Proc. of the WBE 2006, Puerto Vallarta, México, pp.183-188.

1. [SELF-CITATION] Identification of fuzzy models to predict students performance in an e-learning environment, In Proc. of the Fifth IASTED International Conference on Web-Based Education (WBE 2006), Jan.23-25, Puerto Vallarta, México, pp.74-79.

Nebot, A., Castro, F., Múgica, F., and Vellido, A.

 

Vellido, A., Lisboa, P.J.G., and Vicente,D. (2005) Handling outliers and missing data in brain tumor clinical assessment usign t-GTM. In Proc. of the ESANN 2005, D-Side Pub., Bruges, Belgium, pp.121-126.

1. [SELF-CITATION] Missing data imputation through GTM as a mixture of t-distributions

                Neural Networks, In Press, Available online 31 March 2006,

                Vellido, A.

 

Vellido, A. and Lisboa, P.J.G. (2005) Functional topographic mapping for robust handling of outliers in brain tumour data, in: Proceedings of ESANN 05, D-Side Pub., Bruges, Belgium, pp. 133–138.

1. [SELF-CITATION] Handling outliers in brain tumour MRS data analysis through robust topographic mapping.

Computers in Biology and Medicine, (2006) In press.

Vellido, A. and Lisboa, P.J.G.

 

Olier, I. and Vellido, A. , (2005) Comparative assessment of the robustness of missing data imputation through Generative Topographic Mapping, In Proc. of the IWANN 2005, Vilanova i la Geltru, Barcelona, Spain. LNCS Vol.3512, 771-778.

1. [SELF-CITATION] Robust analysis of MRS brain tumour data using t-GTM

Neurocomputing, 69 (7-9), 2006, 754-768

2. [SELF-CITATION] Capturing the Dynamics of Multivariate Time Series Through Visualization Using Generative Topographic Mapping Through Time, In Proc. of the 1st IEEE International Conference on Engineering of Intelligent Systems, ICEIS'2006, Islamabad, Pakistán, pp.492-497.

Olier, I. and Vellido, A.

 

Castro, F. , Vellido, A. , Nebot, A. and Minguillón, J. (2005) Detecting atypical student behaviour on an e-learning system. In Proc. of SINTICE’2005, Granada, Spain, September 2005, 153-160.

1. [SELF-CITATION] Identification of fuzzy models to predict students performance in an e-learning environment, In Proc. of the Fifth IASTED International Conference on Web-Based Education (WBE 2006), Jan.23-25, Puerto Vallarta, México, pp.74-79.

Nebot, A., Castro, F., Múgica, F., and Vellido, A.

2. Educational data mining: A survey from 1995 to 2005

Expert Systems with Applications, in press.

C. Romero, S. Ventura

 

Vellido, A. (2005) Preliminary theoretical results on a feature relevance determination method for Generative Topographic Mapping. Technical Report LSI-05-13-R, Universitat Politècnica de Catalunya, UPC, Barcelona, Spain

1. [SELF-CITATION] Robust analysis of MRS brain tumour data using t-GTM

Neurocomputing, 69 (7-9), 2006, 754-768

2. [SELF-CITATION] Characterization of atypical virtual campus usage behavior through robust generative relevance analysis,

In Proc. of the 5th IASTED Int. Conf. on Web-Based Education (WBE 2006), Puerto Vallarta, México, 2006, 183-188.

Vellido, A., Castro, F., Nebot, A., and Múgica, F.

 

Vicente, D., Vellido, A., Martí, E., Comas, J., and Rodriguez-Roda, I. (2004), Exploration of the ecological status of Mediterranean rivers: Clustering, visualizing and reconstructing streams data using Generative Topographic Mapping. In W.I.T. Transactions on Information and Communication Technologies, Vol.33, 121-130.

1. [SELF-CITATION] Robust analysis of MRS brain tumour data using t-GTM

Neurocomputing, 69 (7-9), 2006, 754-768

2. [SELF-CITATION] Missing data imputation through GTM as a mixture of t-distributions

Neural Networks, In Press, Available online 31 March 2006,

Vellido, A. 

 

Vellido, A. (2004) Generative Topographic Mapping as a constrained mixture of Student t-distributions: Theoretical developments. Technical Report LSI-04-44-R, Universitat Politècnica de Catalunya (UPC), Barcelona, Spain.

1. [SELF-CITATION] Handling outliers in brain tumour MRS data analysis through robust topographic mapping.

Computers in Biology and Medicine, (2006) In press.

Vellido, A. and Lisboa, P.J.G.

 

Vellido, A., Lisboa, P.J.G. and Meehan, K. (2003) Selective smoothing of the generative Topographic Mapping. IEEE Transactions on Neural Networks, 2003

               

                1. [SELF-CITATION] Cluster-Based Visualisation of Marketing Data

                Lecture Notes in Computer Science, LNCS 3177, 2004

                P.J.G. Lisboa and S. Patel

2. [SELF-CITATION] Exploration of the ecological status of Mediterranean rivers: Clustering, visualizing and reconstructing streams data using Generative Topographic Mapping.

In W.I.T. Transactions on Information and Communication Technologies, Vol.33, 2004, 121-130

Vicente, D., Vellido, A., Martí, E., Comas, J., and Rodriguez-Roda, I.

3. [SELF-CITATION] Comparative assessment of the robustness of missing data imputation through generative topographic mapping 
Lecture Notes In Computer Science LNCS 3512, 2005, 787-794.

Olier I., Vellido A.

4. The Parameterless Self-Organizing Map Algorithm

IEEE Transactions on Neural Networks, 17(2) 2006, 305-316.

E. Berglund and J. Sitte

5. [SELF-CITATION] Robust analysis of MRS brain tumour data using t-GTM

Neurocomputing, 69 (7-9), 2006, 754-768

6. [SELF-CITATION] Handling outliers in brain tumour MRS data analysis through robust topographic mapping.

Computers in Biology and Medicine, (2006) In press.

Vellido, A. and Lisboa, P.J.G.

7. [SELF-CITATION] Missing data imputation through GTM as a mixture of t-distributions

Neural Networks, In Press, Available online 31 March 2006,

Vellido, A.

 

Vellido, A., Lisboa, P.J.G. and Meehan, K. (2002) Characterizing and Segmenting the On-Line Customer Market Using Neural Networks. In E-Commerce and Intelligent Methods. Heidelberg: Springer-Verlag, 101-119

 

1. Application of Intelligent Methods in Commercial Website Marketing Strategies Development.

Information Technology and Control, 2005, 34(2), 140–144

A. Noreika

2. [SELF-CITATION] Handling outliers in brain tumour MRS data analysis through robust topographic mapping

Computers in Biology and Medicine, In press.

Vellido, A. and Lisboa, P.J.G.

 

Vellido, A and Lisboa, P.J.G (2001) An electronic commerce application of the Bayesian Framework for MLPs: the Effect of Marginalization and ARD. Neural Computing & Applications. 10(1)

 

1. Application of Bayesian Neural Networks to Biological Sequence Analysis

Ziran Zazhi, 2004, 26(2) 108-111.

邵建林  史定华  王翼飞 

2. Enabling a Powerful Marine and Offshore Decision-Support Solution Through Bayesian Network Technique

Risk Analysis, 2006, 26(3), 695-721.

A. G. Eleye-Datubo, A. Wall, A. Saajedi, and J. Wang

 

Lisboa P.J.G, Vellido A, Wong H. (2000) Outstanding issues for clinical decision support with Neural Networks, in: Artificial Neural Networks in Medicine and Biology, Springer, London, pp. 63–71.

 

1. [SELF-CITATION] Handling outliers in brain tumour MRS data analysis through robust topographic mapping

Computers in Biology and Medicine, In press.

Vellido, A. and Lisboa, P.J.G.

2. [SELF-CITATION] Robust analysis of MRS brain tumour data using t-GTM

Neurocomputing, 69 (7-9), 2006, 754-768

 

Lisboa P.J.G, Vellido A, Wong H. (2000) Bias reduction in skewed binary classification with Bayesian neural networks. Neural Networks.

 

1. [SELF-CITATION] Are neural networks best used to help logistic regression? An example from breast cancer survival analysis

Proceedings of the International Joint Conference on Neural Networks, 2001, 2472-2477

P.J.G. Lisboa, H. Wong

2. [SELF-CITATION] A review of evidence of health benefit from artificial neural networks in medical intervention 

Neural Networks, 15(1), 2002, 11-39

P.J.G. Lisboa

3. [SELF-CITATION] A Bayesian neural network approach for modelling censored data with an application to prognosis after surgery for breast cancer

Artificial Intelligence in Medicine, 28(1), 2003, 1-25

P.J.G. Lisboa, H. Wong, P. Harris and R. Swindell

4. An Artificial Neural Network for Analysing the Survival of Patients with Colorectal Cancer

In Procs. of the ESANN 2005, D-Side pub., 2005, 103-108.

R. Bittern, A. Cuschieri, S.D. Dolgobrodov, R. Marshall, P. Moore, and R.J.C. Steele

5. [SELF-CITATION] The use of artificial neural networks in decision support in cancer: A systematic review

Neural Networks, 19(4), 2006, 408-415.

P.J.G. Lisboa and A.F.G. Taktak

6. e-Science and artificial neural networks in cancer management

Concurrency and Computation: Practice and Experience, 2006, in press

S.D. Dolgobrodov, R. Marshall, P. Moore, R. Bittern, R.J.C. Steele, A. Cuschieri

 

Vellido, A., Lisboa, P.G.J., and Meehan, K. (2000)Quantitative characterization and prediction for on-line purchasing behavior: A latent variable approach. International Journal of Electronic Commerce.

 

1. Differential effects of product category on shoppers’ selection of web-based stores: a probabilistic modelling approach

Journal of Electronic Commerce Research, 2(4), 2001

Oded Lowengart, and Noam Tractinsky

2. Factors Affecting e-Commerce Textbook Purchases

In Procs. of the International Association for Computer Information Systems (IACIS), Vancouver, Canada, 2001, 383-389.

Reif, H., Dillon, T.W.

3. Influence of Product Class on Preference for Shopping on the Internet

Journal of Computer-Mediated Communication, 8(1), 2002.

Tulay Girard, Ronnie Silverblatt, Pradeep Korgaonkar

4. Consumer Online Shopping Attitudes and Behavior: An Assessment of Research

Eighth Americas Conference on Information Systems, 2002, 508-517.

Li, N., and Zhang, P.

5. Insights and implications of e-service end-user adoption

Technical Report SWP 2002/65. School of Information Systems. Deakin University, 2002.

Sandhu, K, and Corbitt, B.J.

6. Exploring an understanding of web-based e-service end-user adoption

Technical Report SWP 2002/66. School of Information Systems. Deakin University, 2002.

Sandhu, K, and Corbitt, B.J.

7. Online Consumer Behavior: An Overview and Analysis of the Literature
In Proc. of the 6th Pacific Asian Conference on Information Systems (PACIS 2002), 813-827.
T. Kwong, C. Cheung, L. Zhu, M. Limayem, D.Viehland

8.  Developing a Measurement Instrument for Discerning Consumers’ e-Commerce Purchase Perceptions

In Procs. of the International Association for Computer Information Systems (IACIS), Florida, USA, 2002, 151-157.

Dillon, T.W., Reif, H.

9. Supply-side hurdles in Internet B2C e-commerce: An empirical investigation
IEEE Transactions on Engineering Management, 50 (4), 2003, 458-469

Cheung MT, Liao ZQ

10. Web-Based Shopping: Perceptions of Website Design Factors by Online New Zealand Buyers

Massey University, Department of Commerce Working Paper Series 03.08. (2003).

Shergill, G. S. and Chen, Z.

11. Relationship of Type of Product, Shopping Orientations, and Demographics with Preference for Shopping on the Internet

Journal of Business and Psychology, 18 (1), 2003, 101-120

Tulay Girard, Pradeep Korgaonkar, and Ronnie Silverblatt

12. Electronic Commerce Customer Relationship Management: A Research Agenda

Information Technology and Management 4, 2003, 233–258

Nicholas C. Romano, jr. and Jerry Fjermestad

13. Examination of brand knowledge, perceived risk and consumers' intention to adopt an online retailer.

Total Quality Management and Business Excellence 14 (6), 2003, 677-693.

Chen, R., He, F.

14. Using brand knowledge to understand consumers' intention to adopt an online retailer

International Journal of Services, Technology and Management 4 (4-6), 2003, 464-479.

Chen, R., He, F.

15. Toward an Integrative Framework for Online Consumer Behavior Research: A Meta-Analysis Approach,
Journal of End Use Computing, 15(4), 2003, 1-26.
Saeed, K. A., Hwang, Y., and Yi, M. Y.
16. An Exploratory Study of Operant Conditioning Theory as a Predictor of Online Product Selection
Journal of Electronic Commerce in Organizations, 1(1), 2003, 42-54

V. Perotti, P. Sorce, S. Widrick
17. Influencing the online consumer's behavior: the Web experience

Internet Research: Electronic Networking Applications and Policy, 1, vol. 14(2), 2004, 111-126

Constantinides, E.

18. Online Shopping for Positive and Negative Reinforcement Products

In Mehdi Khosrow-Pour, D.B.A. (Ed.), The Social and Cognitive Impacts of e-Commerce on Modern Organizations, Chapter 1, Idea Group Inc. (2004)

Patricia Sorce, Victor Perotti, Stanley Widrick

19. A meta-analysis approach toward the development of an integrative framework for online consumer behaviour research

In M.A. Mahmood (Ed.), Advanced Topics in End User Computing (Vol.3), Idea Group Inc., 2004.

Saeed, K.A., Hwang, Y., and Yi, M.Y.

20. Identifying purchase perceptions that affect consumers’ Internet buying

In N. Shin (Ed.) Strategies for Generating E-Business Returns on Investment, Idea Group Inc., 2004, pp. 235-253.

T.W. Dillon, and H.L. Reif

21. Factors Influencing Consumers’ E-Commerce Commodity Purchases

Information Technology, Learning, and Performance Journal, 22(2), 2004, 1-12

T.W. Dillon, and H.L. Reif

22. Attitude and age differences in online buying
International Journal of Retail & Distribution Management, 33 (2), 2005, 122-132.
Patricia Sorce, Victor Perotti, and Stanley Widrick

23. Web-based shopping: consumers’ attitudes towards online shopping in New Zealand

Journal of Electronic Commerce Research, 6 (2), 2005

Gurvinder S Shergill and Zhaobin Chen

24. A critical review of online consumer behavior: Empirical research

Journal of Electronic Commerce in Organizations, 3(4), 2005, 1-19.

Cheung, C.M.K., Chan, G.W.W., Limayem, M.

25. What Makes Customers Shop Online?
In Electronic Customer Relationship Management, Fjermestad, J. and Romano, N. (eds), Series of Advances in Management Information Systems (AMIS), 2006, M.E. Sharpe.
N. Li and P. Zhang

 

Vellido, A. (2000) A Methodology for the Characterization of B2C E-Commerce. PhD Thesis

 

1. Profiling internet users based on their propensity to adopt online shopping

Asia Pacific Advances in Consumer Research, 5, 2002, 30-39

Malaika Brengman, Maggie Geuens

2. Segmenting Internet shoppers based on their Web-usage-related lifestyle: a cross-cultural validation

Journal of Business Research, 58(1), 2005, 79-88.

Malaika Brengman, Maggie Geuens, Bert Weijters, Scott M. Smith and William R. Swinyard

3. Medición de las actitudes de los internautas respecto a la compra on-line. Segmentación en base a actitudes y caracterización de los segmentos identificados.

Economic Analysis Working Papers (Edited by Association of Economists of La Coruña) Vol.4(4), 2005

Lidia Andrades Caldito

 

Vellido, A., Lisboa, P.J.G. and Meehan, K. (2000) The Generative Topographic Mapping as a principled model for data visualization and market segmentation: an electronic commerce case study. International Journal of Computers, Systems, and Signals. 1(2), 119-138.

 

1. Bibliography of Self-Organizing Map (SOM) Papers: 1998-2001 Addendum.

Neural Computing Surveys, 3, 2002, 1-156.

Merja Oja, Samuel Kaski and Teuvo Kohonen

2. [SELF-CITATION] On the improvement of brain tumour data clustering using class information. In Proc. of the 3rd European Starting AI Researcher Symposium (STAIRS'06), Riva del Garda, Italy.  

Cruz, R., Vellido, A.

 

 

Vellido, A., Lisboa, P.J.G. & Meehan, K. (2000) Segmenting the e-commerce market using the Generative Topographic Mapping. In Proceedings of the MICAI-2000, 470-481. Acapulco, México.

 

1. Bibliography of Self-Organizing Map (SOM) Papers: 1998-2001 Addendum.

Neural Computing Surveys, 3, 2002, 1-156.

Merja Oja, Samuel Kaski and Teuvo Kohonen

 

 

Lisboa, P. J. G. and Vellido, A. (2000) Business Applications of Neural Networks. In P. J. G. Lisboa, B. Edisbury and A. Vellido (Eds.) Business Applications of Neural Networks: The State-of-the-Art of Real-World Applications, pp.vii-xxii. Singapore: World Scientific.

 

1. Data mining and Neural Networks from a Commercial Perspective

In Procs. of the ORSNZ Conference Twenty Naught One, University of Canterbury, Christchurch, NZ, 2001.

P.A. Cerny

2. Modelling and Trading the EUR/USD Exchange Rate: Do Neural Network Models Perform Better?

CIBEF working papers. Liverpool Business School, UK, 2002.

C.L. Dunis and M. Williams

3. [SELF-CITATION] Probability Distributions, Trading Strategies and Leverage: An Application of Gaussian Mixture Models

CIBEF working papers. Liverpool Business School, UK, 2003.

A. Lindemann, C.L. Dunis, and P.J.G. Lisboa

4. Applications of Advanced Regression Analysis for Trading and Investment

In C.L. Dunis, P. Naim, and J. Laws (Eds.) Applied Quantitative Methods for Trading and Investment, John Wiley & Sons, 2003

C.L. Dunis and M. Williams

5. [SELF-CITATION] Probability distributions, trading strategies and leverage: an application of Gaussian mixture models

Journal of Forecasting, 23(8), 2004, 559-585.

A. Lindemann, C.L. Dunis, and P.J.G. Lisboa

6. An intelligent information infrastructure to support the streamlining of integrated logistics workflow

Expert Systems, 21(3), 2004, 123-137.

G.T.S. Ho, H.C.W. Lau, W.H. Ip and A. Ning

7. [SELF-CITATION] Level estimation, classification and probability distribution architectures for trading the EUR/USD exchange rate

Neural Computing and Applications, 14(3), 2005, 256-271.

A. Lindemann, C.L. Dunis, and P.J.G. Lisboa

8. [SELF-CITATION] Probability distributions and leveraged trading strategies: an application of Gaussian mixture models to the Morgan Stanley Technology Index Tracking Fund

Quantitative Finance, 5(5), 2005, 459-474.

A. Lindemann, C.L. Dunis, and P.J.G. Lisboa

9. [SELF-CITATION] Probability distribution architectures for trading silver

Neural Network World, 15(5), 2005, 437-470.

A. Lindemann, C.L. Dunis, and P.J.G. Lisboa

10. Knowledge acquisition and revision using neural networks: an application to a cross-national study of brand image perception

Journal of the Operational Research Society, 57(3), 2006, 231-240.

Setiono, R; Pan, S-L; Hsieh, M-H; Azcarraga, A

 

 

Vellido, A., Lisboa, P.J.G., and Vaughan, J. (1999) Neural networks in business: a survey of applications (1992-1998). Expert Systems with Applications

 

1. [SELF-CITATION] Segmentation of the on-line shopping market using neural networks

Expert Systems with Applications, 17(4),1999, 303-314

A. Vellido, P. J. G. Lisboa and K. Meehan

2. The development of a decision model for liquidity analysis .

Expert Systems with Applications, 19(4), 2000, 271-278

Sheng-Tun Li, Li-Yen Shue and Weissor Shiue.
3. Developing a neural network approach for intelligent scheduling in GUESS
Expert Systems, 17(4), 2000, 185-190.

Liebowitz J, Rodens I, Zeide J, et al.

4. Artificial neural networks in accounting and finance: modeling issues

International Journal of Intelligent Systems in Accounting, Finance & Management, 9(2), 2000, 119-144.

James R. Coakley and Carol E. Brown  

5. Bankruptcy prediction for credit risk using neural networks: A survey and new results
IEEE Transactions on Neural Networks, 12(4), 2001, 929-935.

Atiya, A.F.
6. The Kohonen self-organizing map: an application to the study of strategic groups in the UK hotel industry
Expert Systems, 18 (1), 2001, 19-31.

Curry B, Davies F, Phillips P, et al.

7. Investigating the information content of non-cash-trading index futures using neural networks 

Expert Systems with Applications, 22(3), 2002, 225-234.

Tian-Shyug Lee and Nen-Jing Chen

8. Credit scoring using the hybrid neural discriminant technique

Expert Systems with Applications, 23(3), 2002, 245-254.

Tian-Shyug Lee, Chih-Chou Chiu, Chi-Jie Lu and I-Fei Chen
9. Design of manufacturing systems by a hybrid approach with neural network metamodelling and stochastic local search
International Journal of Production Research, 40(1), 2002, 71-92.

Chen MC, Yang TH

10. Integration of ART2 Neural Network and Genetic K-means Algorithm for Analyzing the Browsing Paths in Electronic Commerce

In Proceedings of the 4th International Conference on Electronic Commerce (ICEC), Hong Kong, 2002.

R. J. Kuo, C. L. Liao, T.-L. Hua and C. Tua

11. Neural networks and non-linear statistical methods: an application to the modelling of price-quality relationships

Computers and Operations Research, 29(8), 2002, 951-969.

12. Evolution of Artificial Neural Networks in Business Applications: An Empirical Investigation Using a Growth Model

International Journal of Management & Decision Making, 3(1), 2002, 19-34

Quaddus, M.A., and Khan, M.S.

13. Applying neural network in hydrotreating process

World Petroleum Congress Proceedings, 2002, 13-23

Da Silva, R.M.C.F., De Oliveira, L.V., De Souza Aires, J.S.

14. Data mining by using the integration of neural network and discriminant analysis

Journal of the Chinese Institute of Industrial Engineers 19(2), 2002, 9-22.

Chiu, C.-C., Lee, T.-S., Chou, Y.-C., Lu, C.-J.

15. Construction of Enterprise Distress Diagnosis Model by Using the Integration of Neural Network and Classification and Regression Trees Approach

Web Journal of Chinese Management Review, 5(4), 2002, 55-82.

Chiu, C.-C., Chien, T.-N

16. The commercial use of segmentation and predictive modeling techniques for database marketing in the Netherlands

Decision Support Systems, 34(4), 2003, 471-481.

Peter C. Verhoef, Penny N. Spring, Janny C. Hoekstra and Peter S. H. Leeflang

17. Credit scoring and rejected instances reassigning through evolutionary computation techniques

Expert Systems with Applications, 24(4), 2003, 433-441.
Mu-Chen Chen and Shih-Hsien Huang

18. Expert systems in business: applications and future directions for the operations researcher

Industrial Management & Data Systems, 103(5), 2003.

Metaxiotis, K; Psarras, John
19. A neural network model for bankruptcy prediction
Dynamics of Continuous Discrete and Impulsive Systems-Series B-Applications & Algorithms, Suppl. SI 2003, 230-237

Chen X, Qi H, Li W

20. Model Development Techniques and Evaluation Methods for Prediction and Classification of Consumer Risk in the Credit Industry

In P. Zhang (ed.). Neural Networks for Business Forecasting. IRM Press: Hershey, PA. (2003)

Nargundkar, Satish  and Priestley, Jennifer

21. Assessment of Model Development Techniques and Evaluation Methods for Binary Classification in the Credit Industry

DSI 2003 National Conference, Washington DC (November 2003)

Nargundkar, Satish  and Priestley, Jennifer

22. La estimación de la función educativa en valor añadido mediante redes neuronales: una aplicación para el caso español

Working paper 5. Instituto de Estudios Fiscales. Ministerio de Economía y Hacienda. España. 2003.

Daniel Santín González

23. Eficiencia Técnica y Redes Neuronales: Un Modelo para el Cálculo del Valor Añadido en Educación

Phd Thesis, Universidad Complutense de Madrid, 2003

Daniel Santín González

24. The South-East Asia Crisis, Neural Networks and Market Behavior: An Exploratory Study

Review of Pacific Basin Financial Markets and Policies, 6(3), 2003, 349-379.

C. Scott

25. The Use of a Bayesian Confidence Propagation Neural Network in Pharmacovigilance

PhD Thesis. Umea University, Sweden, (2003)

Andrew Bate

26. Artificial Neural Networks in Auditing: State of the Art

Technical report. Turku Centre for Computer Science, Finland, 2003

E. Koskivaara

27. Sawtooth feature extraction of leaf edge based on Support Vector Machine

International Conference on Machine Learning and Cybernetics 5, 2003, 3039-3044.

Qi, H.-N., Yang, J.-G.

28. Mining the customer credit using classification and regression tree and multivariate adaptive regression splines

Proceedings of the International Conference on Information and Knowledge Engineering, 2, 2003, 533-538.

29. Neural networks as a decision maker for stock trading: A technical analysis approach

International Journal of Smart Engineering System Design 5 (4), 2003, 313-325

Thawornwong, S., Enke, D., Dagli, C.

30. A survey of data mining

Journal of Southwest University for Nationalities (Natural Science Edition), 2003, 29(3), 328-330.

贺清碧  胡久永

31. Applying the Hybrid Neural Network Model to Diagnose the Enterprise Distress—Consideration of Intellectual Capital Indicator

演化式類神經網路在企業危機診斷 上之應用智慧資本指標的考量, 2004, 1-22.

Chih-Chou Chiu Te-Nien Chien Ling-Jing Kao

32. Visualization of patterns in accounting data with Self-Organizing Maps

In A. Anandarajan, C.A. Srinivasan, and M. Anandarajan (Eds.) Business Intelligence Techniques, Springer, 2004, 133-148

E. Koskivaara

33. Artificial Neural Networks for Analytical Review in Auditing

PhD thesis, Turku School of Economics and Business Administration, 2004

E. Koskivaara

34. The adaptive selection of financial and economic variables for use with artificial neural networks
Neurocomputing, 56, 2004, 205-232.

Suraphan Thawornwong and David Enke

35. Modeling consideration sets and brand choice using artificial neural networks

European Journal of Operational Research, 154(1), 2004, 206-217
Björn Vroomen, Philip Hans Franses and Erjen van Nierop

36. Mining the breast cancer pattern using artificial neural networks and multivariate adaptive regression splines

Expert Systems with Applications, 27(1), 2004, 133-142

Shieu-Ming Chou, Tian-Shyug Lee, Yuehjen E. Shao and I-Fei Chen

37. Artificial neural networks in analytical review procedures

Managerial Auditing Journal, 19 (2), 2004

Koskivaara, Eija
38. Integration of self-organizing feature maps and genetic-algorithm-based clustering method for market segmentation
Journal of Organizational Computing and Electronic Commerce, 14 (1), 2004 , 43-60

Kuo RJ, Chang K, Chien SY

39. An integrated data mining and behavioral scoring model for analyzing bank customers

Expert Systems with Applications, 27(4), 2004, 623-633

Hsieh, N.-C.

40. Business Forecasting with Artificial Neural Networks: An Overview

In Neural Networks in Business Forecasting, Idea Group, Inc., 2004

Zhang, G.P.

41. Integration of Self-Organizing Feature Maps and Genetic-Algorithm-Based Clustering Method for Market Segmentation

Journal of Organizational Computing and Electronic Commerce, 14(1), 2004, 43–60

R.J. Kuo, K. Chang, and S.Y.Chien

42. Toward Global Optimization of Case-Based Reasoning Systems for Financial Forecasting

Applied Intelligence, 21(3), 2004, 239-249.

K.-J. Kim

43. Redes neuronales y eficiencia: aplicación al servicio de recogida de basuras

XI Encuentro de Economía Pública, Barcelona, 5-6 Febrero 2004

F.J. Delgado Rivero

44. Differential Evolution and Sparse Neural Networks

11ème Rencontre Internationale Approches Connexionnistes en Sciences Economiques et de Gestion (ACSEG), Novembre 2004, Lille, France.

P.H. Morgan

45. Applying neural networks in quality function deployment process for conceptual design

Journal of the Chinese Institute of Industrial Engineers, 21(6), 2004,  587-596

Chou, Y.-Ch.

46. Invariant Object Recognition Based on Elastic Graph Matching

Chapter 11: NORN predictor – Stock price prediction using a neural oscillatory-based recurrent network, 2004

R. Lee and J. Liu

47. The impact of political instability on the tourism industries of selected Mediterranean destinations: a neural network approach

In D. Hall (Ed.) Tourism and Transition: Governance, Transformation and Development, CABI Publishing, 2004, 147-168.

A. Theocharous

48. Sawtooth identification and counting of leaf edge based on SVM

Proceedings of the International Conference on Artificial Intelligence, IC-AI'04, 2, 2004, 990-995.

Qi, H., Yang, J., Lin, J.

49. Mining the customer credit using artificial neural networks and multivariate adaptive regression splines

Proceedings of the International Conference on Artificial Intelligence, IC-AI'04, 1, 2004, 133-139.

Lee, T.-S., Chen, I.-F.

50. A machine learning approach to generate rules for process fault diagnosis

Journal of Chemical Engineering of Japan, 37 (6), 2004, 691-697.

Shastri, S., Lam, C.-P., Werner, B.

51. Efficiency in Public Sector: A Neural Network Approach

10th International Conference on Computing in Economics and Finance, Amsterdam, 2004

Delgado, F.J.

52. Hybrid mining approach in the design of credit scoring models

Expert Systems with Applications, 28(4), 2005, 655-665.

Hsieh, N.-C.

53. A two-stage hybrid credit scoring model using artificial neural networks and multivariate adaptive regression splines

Expert Systems with Applications, 28(4), 2005, 743-752.

T.-S. Lee and I.-F. Chen

54. Measuring efficiency with neural networks. An application to the public sector

Economics Bulletin, 3(15), 2005, 1−10.

Delgado, F.J.

55. Medición de eficiencia con redes neuronales artificiales. Una explicación al servicio

de recogida de basuras.

Cuadernos de Economía y Dirección de la Empresa, 25, 2005, 53-82

Delgado, F.J.

56. The use of data mining and neural networks for forecasting stock market returns

                Expert Systems with Applications, 29(4), 2005, 927-940

                David Enke and Suraphan Thawornwong

57. The evaluation of consumer loans using support vector machines
Expert Systems with Applications, 30(4), 2006, 772-782
Sheng-Tun Li, Weissor Shiue and Meng-Huah Huang

58. Subscription fraud prevention in telecommunications using fuzzy rules and neural networks
Expert Systems with Applications, In Press, Uncorrected Proof, Available online 4 October 2005.
P.A. Estévez, C.M. Held and C.A. Pérez

59. The optimisation of neural network parameters using Taguchi's design of experiments approach: An application in manufacturing process modelling.

Neural Computing and Applications, 14 (4), 2005, 337-344.

Sukthomya, W., Tannock, J.

60. Construction of clustering and classification models by integrating Fuzzy ART, CART and neural network approaches

Journal of the Chinese Institute of Industrial Engineers 22 (2), 2005, 171-188.

Chiu, C.-C., Tien, C.-C., Chou, Y.-C.

61. The training of neural networks to model manufacturing processes

Journal of Intelligent Manufacturing, 16 (1), 2005, 39-51.

Sukthomya, W., Tannock, J.

62. Integration of self-organizing feature maps neural network and genetic K-means algorithm for market segmentation
Expert Systems with Applications, 30(2), 2006 , 313-324.
R.J. Kuo, Y.L. An, H.S. Wang and W.J. Chung

63. Mining the customer credit using classification and regression tree and multivariate adaptive regression splines

Computational Statistics & Data Analysis, 50(4), 2006, 1113-1130

Tian-Shyug Lee, Chih-Chou Chiu, Yu-Chao Chou and Chi-Jie Lu

64. The evaluation of consumer loans using support vector machines

Expert Systems with Applications, 30(4), 2006, 772-782.

Li, S.-T., Shiue, W., Huang, M.-H.

65. Subscription fraud prevention in telecommunications using fuzzy rules and neural networks

Expert Systems with Applications, 31(2), 2006, 337-344

Estévez, P.A., Held, C.M. and Perez, C.A.

66. The history and trend of methods of credit risk measurement

Forecasting, 25(1), 2006, 36-41

Wang, Xian-quan, Li Yi-jun

67. A short-term capacity trading method for semiconductor fabs with partnership.

Expert Systems with Applications, In press

M.-C. Wu and W.-J. Chang

68. Gas-phase exposure history derived from material-phase concentration profiles

Atmospheric Environment, In Press (2007)

G.C. Morrison, J.C. Little, Y. Xu, M. Rao and D. Enke


  

Vellido, A., Lisboa, P. J., & Meehan, K. (1999). Segmentation of the online shopping market using neural networks. Expert Systems with Applications.

 

1. [SELF-CITATION] Bias reduction in skewed binary classification with Bayesian neural networks

Neural Networks, 13(4-5), 2000, 407-410

P. J. G. Lisboa, A. Vellido and H. Wong

2. Mining association rules procedure to support on-line recommendation by customers and products fragmentation. Expert Systems with Applications, 20(4), 2001, 325-335

S. Wesley Changchien and Tzu-Chuen Lu

3. The cluster-indexing method for case-based reasoning using self-organizing maps and learning vector quantization for bond rating cases

Expert Systems with Applications, 21(3), 2001, 147-156
Kyung-Sup Kim and Ingoo Han

4. Applying AI technology and rough set theory for mining association rules to support crime management and fire-fighting resources allocation

Journal of Information, Technology and Society, 2002(2), 65-78

Show-Chin Lee, Mu-Jung Huang.

5. Distance matrix based clustering of the Self-Organizing Map

In José R. Dorronsoro, editor, Artificial Neural Networks - ICANN 2002, LNCS, 2415, 951-956, Madrid, Spain, 2002. Springer.

Juha Vesanto and Mika Sulkava

6. Market segmentation via structured click stream analysis

Industrial Management & Data Systems, 102(9), 2002

Wen, Kuang-Wei; Peng, Kuo-Fang

7. Bibliography of Self-Organizing Map (SOM) Papers: 1998-2001 Addendum.

Neural Computing Surveys, 3, 2002, 1-156.

Merja Oja, Samuel Kaski and Teuvo Kohonen

8. An Automated Report Generation Tool for the Data Understanding Phase

In A. Abraham and M. Köppen (eds.) Hybrid Information Systems, Physica Verlag, Heidelberg,  611-626, 2002.

Juha Vesanto and Jaakko Hollmen

9. Neural Networks: an introduction

In Jatinder N.D. Gupta, Kate A. Smith (Eds.), Neural Networks in Business, Chapter 1. Idea Group Inc. (2002)

Kate A. Smith

10. Evolution of Artificial Neural Networks in Business Applications: An Empirical Investigation Using a Growth Model

International Journal of Management & Decision Making, 3(1), 2002, 19-34.

Quaddus, M.A., and Khan, M.S.

11. Application of data mining to customer relationship management - The case of cosmetics

Journal of the Chinese Institute of Industrial Engineers, 19 (6), 2002, pp.45-59.

Chang, P.-C., Tsai, J.-Y., Hsieh, J.-C.

12. Forecast model for stock market based on artificial neural networks

Journal of Jilin University (Information Science Edition), 2002, 20(4), 68-70.

孙丹  张秀艳

13. Classification of consumers’ perceived risk: sources versus consequences

In Proc. of the 6th Pacific Asian Conference on Information Systems (PACIS 2002), 2002, 540-554

Nena Lim

14. The collaborative filtering recommendation based on SOM cluster-indexing CBR

Expert Systems with Applications, 25(3), 2003, 413-423

Tae Hyup Roh, Kyong Joo Oh and Ingoo Han

15. Consumers’ perceived risk: sources versus consequences

Electronic Commerce Research and Applications, 2(3), 2003, 216-228

Nena Lim

16. The Use of a Bayesian Confidence Propagation Neural Network in Pharmacovigilance

PhD Thesis. Umea University, Sweden (2003)

Andrew Bate

17. Applying AI technology and rough set theory to mine association rules for supporting knowledge management

In Proc. of the International Conference on Machine Learning and Cybernetics (ICMLC), 2003, 1820- 1825 Vol.3.

Zhe Huang and Yun-Quan Hu

18. Economic and Competitive Environment Analysis in the Formulation of Strategy: A Decision-Oriented Study Utilizing Self-Organizing Maps

PhD Thesis, Turku School of Economics and Business Administration. Finland (2004)

Aapo Länsiluoto

19. Internet market segmentation – an exploratory study of critical success factors

Marketing Intelligence & Planning, 2004, 22(6) 601-622

Tom M.Y. Lin, Pin Luarn and Peter K.Y. Lo

20. Unsupervised MRI tissue classification by support vector machines

Proceedings of the IASTED International Conference on Biomedical Engineering, 2004, 88-91.

Karp, E., Vigário, R.

21. Independent component analysis decomposition of structural MRI

Proceedings of the IASTED International Conference on Biomedical Engineering, 2004, 83-87.

Karp, E., Gävert, H., Särelä, J., Vigário, R.

22. Customer Segmentation based on Model of Multiple Classifiers Syncretizing

Management Sciences in China, 2004, 17(2), 64-67.

叶强  邹鹏  尚维

23. Segmenting Internet shoppers based on their Web-usage-related lifestyle: a cross-cultural validation

Journal of Business Research, 58(1), 79-88, (2005)

Malaika Brengman, Maggie Geuens, Bert Weijters, Scott M. Smith and William R. Swinyard

24. Market Basket Analysis by Means of a Growing Neural Network

The International Review of Retail, Distribution and Consumer Research, 15(2), 2005, 151-169.

Decker, R.

25. Extracting salient dimensions for automatic SOM labelling

IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews 35(4), 2005, 595-600.

Azcarraga, A.P., Hsieh, M.-H., Pan, S.L., Setiono, R.

26. Using a clustering genetic algorithm to support customer segmentation for personalized recommender systems

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) LNAI 3397, 409-415.

Kim, K.-J., Ahn, H.

27. Logistics enterprise classifying model

Journal of Traffic and Transportation Engineering, 5 (2), 2005, 117-121.

Mao, H.-J., Zhang, Y., Li, X.-H.

28. Computer assisted customer churn management: State-of-the-art and future trends

Computers & Operations Research, In Press (2006)

John Hadden, Ashutosh Tiwari, Rajkumar Roy and Dymitr Ruta

29. [SELF-CITATION] Exploring the ecological status of human altered streams through Generative Topographic Mapping

Environmental Modelling & Software, In press (2007)

A. Vellido, E. Martí, J. Comas, I. Rodríguez-Roda and F. Sabater

30. Market segmentation based on hierarchical self-organizing map for markets of multimedia on demand

Expert Systems with Applications, In press (2007)

Chihli Hung and Chih-Fong Tsai

31. Knowledge discovery in financial investment for forecasting and trading strategy through wavelet-based SOM networks

Expert Systems with Applications, In press (2007)

Sheng-Tun Li and Shu-Ching Kuo

32. Searching customer patterns of mobile service using clustering and quantitative association rule

Expert Systems with Applications, In press (2007)
So Young Sohn and Yoonseong Kim


 

Lisboa P.J.G., Kirby S.P.,Vellido A., Lee Y.Y., and El-Deredy W. (1998) Assessment of statistical and neural networks methods in NMR spectral classification and metabolite selection. NMR in Biomedicine.

 

1. [SELF-CITATION] Neural networks in practice - An example from magnetic resonance spectroscopy

IEE Colloquium (Digest) 514, pp. 5/1-5/5.

Lee, Y.Y.B., Vellido, A., El-Deredy, W., Kirby, S.P.J., Lisboa, P.J.G.

2. The calculation of sensitometric properties of 1,2,4-triazolo[1,5-a]pyrimidines by use of a neural network 
Journal fur Praktische Chemie-Chemiker-Zeitung, 341 (5), 1999, 449-454

Meusinger R, Fischer G, Moros R

3. Classification of clinical autofluorescence spectra of oral leukoplakia using an artificial neural network: a pilot study 
Oral Oncology, 36(3), 2000, 286-293
H. J. van Staveren, R. L. P. van Veen, O. C. Speelman, M. J. H. Witjes, W. M. Star and J. L. N. Roodenburg

4. [SELF-CITATION] Robust methodology for the discrimination of brain tumours from in vivo magnetic resonance spectra

Proceedings of MEDSIP, Bristol, 88-95, 2000. Keynote address.

Lee, Y.Y.B., Huang, Y., El-Deredy, W., Lisboa, P.J.G. and Harris, P.

5. Nonhistological Diagnosis of Human Cerebral Tumors by 1H Magnetic Resonance Spectroscopy and Amino Acid Analysis

Clinical Cancer Research, 6, 2000, 3983-3993

J.M. Roda, J.M. Pascual, F. Carceller, F. González-Llanos, A. Pérez-Higueras, J. Solivera, L. Barrios and S. Cerdán

6. Pattern recognition methods and applications in biomedical magnetic resonance
Progress in Nuclear Magnetic Resonance Spectroscopy, 39(1), 2001, 1-40
J. C. Lindon, E. Holmes and J. K. Nicholson

7. Automated Mode-of-Action Detection by Metabolic Profiling
Biochemical and Biophysical Research Communications, 286(1), 2001, 150-155
Nelly Aranìbar, Bijay K. Singh, Gerald W. Stockton and Karl-Heinz Ott

8. Data mining of spectroscopic data for biomarker discovery

Current Opinion in Drug Discovery and Development 4 (3), 2001, 325-331.

Norton, S.M., Huyn, P., Hastings, C.A., Heller, J.C.

9. Metabonomics classifies pathways affected by bioactive compounds. Artificial neural network classification of NMR spectra of plant extracts

Phytochemistry, 62(6), 2003, 971-985

Karl-Heinz Ott, Nelly Araníbar, Bijay Singh and Gerald W. Stockton

10. [SELF-CITATION] Tumour grading from magnetic resonance spectroscopy: a comparison of feature extraction with variable selection

Statistics in Medicine 22(1), 2003, 147-164

Y. Huang, P.J.G. Lisboa , W. El-Deredy

11. Visualizing metabolic changes in breast-cancer tissue using 1H-NMR spectroscopy and Self-Organizing Maps

NMR in Biomedicine, 16(1), 2003, 1-11

Olaf Beckonert, Jürgen Monnerjahn, Ulrich Bonk, and Dieter Leibfritz

12. Proton MR CSF analysis and a new software as predictors for the differentiation of meningitis in children

NMR in Biomedicine, 18(4), 2005, 213-225

Arunachalam Subramanian, Abhishek Gupta, Swapnil Saxena, Ashish Gupta, Raj Kumar, Anjali Nigam, Rashmi Kumar, Sudhir K. Mandal, and Raja Roy

13. A robust clustering approach for NMR spectra of natural product extracts

Magnetic Resonance in Chemistry, 43, 2005, 359-365

G.K. Pierens, M.E. Palframan, C.J. Tranter, A.R. Carroll and R.J. Quinn

14. Optimal classification of long echo time in vivo magnetic resonance spectra in the detection of recurrent brain tumors

NMR in Biomedicine, 2006, in press

B.H. Menze, M.P. Lichy, P. Bachert, B.M. Kelm, H.-P. Schlemmer, F.A. Hamprecht

 

Lisboa, P.J.G., Wong, H., Vellido, A., Kirby, S.P.J., Harris, P. and Swindell, R. (1998) Survival of Breast Cancer Patients Following Surgery: a Detailed Assessment of the Multi-Layer Perceptron and Cox’s Proportional Hazard Model. In Proceedings of the World Congress on Computational Intelligence, IJCNN, 112-116.

 

1. Sparse bayesian kernel survival analysis for modeling the growth domain of microbial pathogens 

IEEE Transactions on Neural Networks, 17(2), 2006, 471-481.

Cawley, G.C., Talbot, N.L.C., Janacek, G.J., Peck, M.W.

 

 

Lisboa, P.J.G, Branston, N.M., El-Deredy, W., and Vellido, A. (1997). Tissue Characterisation with NMR Spectroscopy; Current State and Future Prospects for the Application of Neural Networks Analysis. In: Proceedings of the IEEE/INNS International Joint Conference on Neural Networks, Houston, pp.1385-1390

 

1. Applications of artificial neural network in AIDS research and therapy

Current Pharmaceutical Design, 8(8), 2002, 659-670.

Sardari, S., Sardari, D.

2. Metabonomics classifies pathways affected by bioactive compounds. Artificial neural network classification of NMR spectra of plant extracts

Phytochemistry, 62(6), 2003, 971-985

Karl-Heinz Ott, Nelly Araníbar, Bijay Singh and Gerald W. Stockton

3. A robust clustering approach for NMR spectra of natural product extracts

Magnetic Resonance in Chemistry, 43, 2005, 359-365

G.K. Pierens, M.E. Palframan, C.J. Tranter, A.R. Carroll and R.J. Quinn

 

Last updated 28/11/06