Items where Subject is "Generalities > Computer Science and Informatics > Artificial Intelligence"

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Number of items at this level: 75.

Budka, M. and Gabrys, B., 2013. Density Preserving Sampling (DPS) for error estimation and model selection. IEEE Transactions on Neural Networks and Learning Systems, 24 (1), pp. 22-34.

Stahl, F. and Jordanov, I., 2012. An Overview of the Use of Neural Networks for Data Mining Tasks. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 2 (3), pp. 193-208.

Tsakonas, A. and Gabrys, B., 2011. Evolving Takagi-Sugeno-Kang fuzzy systems using multi-population grammar guided genetic programming. In: International Conference on Evolutionary Computation Theory and Applications (ECTA'11), 24-26 Oct 2011, Paris, France.

Zliobaite, I., Bifet, A., Pfahringer, B. and Holmes, G., 2011. Active learning with evolving streaming data. In: The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 5-9 September 2011, Athens, Greece.

Budka, M., Gabrys, B. and Musial, K., 2011. On accuracy of PDF divergence estimators and their applicability to representative data sampling. Entropy, 13 (6), pp. 1229-1266.

Zliobaite, I., 2011. Combining similarity in time and space for training set formation under concept drift. Intelligent Data Analysis, 15 (4), pp. 589-611.

Zliobaite, I., 2011. Identifying hidden contexts. In: PAKDD2011: The 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 24-27 May 2011, Shenzhen, China. (Unpublished)

Schierz, A. C., Budka, M. and Apeh, E., 2011. Winners’ notes. Using Multi-Resolution Clustering for Music Genre Identification. TunedIT.

Apeh, E. T., Gabrys, B. and Schierz, A. C., 2011. Customer profile classification using transactional data. In: Third World Congress on Nature and Biologically Inspired Computing (NaBIC), 19-21 Octpber 2011, Salamanca Spain. IEEE, pp. 37-43.

Zliobaite, I., 2010. Change with delayed labeling: when is it detectable? In: The 5th International Workshop on Chance Discovery - IWCD5 in IEEE ICDM'10, pp. 843-850.

Zliobaite, I. and Pechenizkiy, M., 2010. Learning with actionable attributes: attention – boundary cases! In: The 2010 ICDM Workshop on Domain Driven Data Mining, pp. 1021-1028.

King, R. D., Schierz, A. C., Clare, A., Rowland, J., Sparkes, A., Nijssen, S. and Ramon, J., 2010. Inductive queries for a drug designing robot scientist. In: Dzeroski, S., Goethals, B. and Panov, P., eds. Inductive Databases and Constraint-Based Data Mining. Springer, pp. 421-451.

Rowe, N., Atfield-Cutts, S., Davies, P. and Newell, D., 2010. Implementation and Evaluation of an Adaptive Multimedia Presentation System (AMPS) with Contextual Supplemental Support Media. In: MMEDIA 2010: The Second International Conferences on Advances in Multimedia, 13-19 June 2010, Athens/Glyfada, Greece. (Submitted)

Lemke, C. and Gabrys, B., 2010. Meta-learning for time series forecasting and forecast combination. Neurocomputing, 73 (10-12), pp. 2006-2016.

Budka, M., Gabrys, B. and Ravagnan, E., 2010. Robust predictive modelling of water pollution using biomarker data. Water Research, 44 (10), pp. 3294-3308.

Budka, M. and Gabrys, B., 2010. Correntropy–based density–preserving data sampling as an alternative to standard cross–validation. In: ICJNN 2010: International Joint Conference on Neural Networks. IEEE, pp. 1-8.

Budka, M. and Gabrys, B., 2010. Correntropy–based density–preserving data sampling as an alternative to standard cross–validation. In: World Congress on Computational Intelligence (WCCI 2010), 18-23 July 2010, Barcelona, Spain, pp. 1-8.

Smith, P. and Isley, V., 2010. Lost Calls of Cloud Mountain Whirligigs (view 2, left & right). Computer generated.Istanbul, Turkey: UNSPECIFIED.

Isley, V. and Smith, P., 2009. Lost Calls of Cloud Mountain Whirligigs (view 1, left & right). Computer generated.Berlin, Germany: [DAM]Berlin.

Tong, D. L., Phalp, K. T., Schierz, A. C. and Mintram, R., 2009. Innovative Hybridisation of Genetic Algorithms and Neural Networks in Detecting Marker Genes for Leukaemia Cancer. In: 4th IAPR International Conference in Pattern Recognition for Bioinformatics, 7-9 September 2009, Sheffield, UK.

Eastwood, M. and Gabrys, B., 2009. A Non-Sequential Representation of Sequential Data for Churn Prediction. In: Knowledge-Based and Intelligent Information and Engineering Systems: 13th International Conference, KES 2009, Santiago, Chile, September 28-30, 2009, Proceedings, Part I. Heidelberg: Springer, pp. 209-218.

Kadlec, P. and Gabrys, B., 2009. Self-Adapting Soft Sensor for On-Line Prediction. In: Köppen, M., Kasabov, N. and Coghill, G., eds. Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part I. Heidelberg: Springer, pp. 1172-1179.

Atfield-Cutts, S., Davies, P., Rowe, N. and Newell, D., 2009. Multimedia Presentation System with Contextual Support BU & Bournemouth and Poole College. In: Education Enhancement Conference 2009, 21 May 2009, Bournemouth University.

Budka, M. and Gabrys, B., 2009. Electrostatic Field Classifier for Deficient Data. In: Kurzynski, M. and Wozniak, M., eds. Computer Recognition Systems 3. Heidelberg: Springer, pp. 311-318.

Kadlec, P., Gabrys, B. and Strandt, S., 2009. Data-driven Soft Sensors in the Process Industry. Computers and Chemical Engineering, 33 (4), pp. 795-814.

Lemke, C., Riedel, S. and Gabrys, B., 2009. Dynamic Combination of Forecasts Generated by Diversification Procedures Applied to Forecasting of Airline Cancellations. In: 2009 IEEE Symposium on Computational Intelligence for Financial Engineering Proceedings. Nashville: IEEE, pp. 85-91.

Kadlec, P. and Gabrys, B., 2009. Evolving on-line prediction model dealing with industrial data sets. In: 2009 IEEE Workshop on Evolving and Self-Developing Intelligent Systems Proceedings. Nashville: IEEE, pp. 24-31.

Kuncheva, L. and Zliobaite, I., 2009. On the Window Size for Classification in Changing Environments. Intelligent Data Analysis, 13 (6), pp. 861-872.

Schierz, A. C., 2009. Virtual Screening of Bioassay Data. Journal of Cheminformatics, 1 (21).

Riedel, S., 2008. Forecast combination in revenue management demand forecasting. Doctorate Thesis (Doctorate). Bournemouth University.

Kadlec, P. and Gabrys, B., 2008. Application of Computational Intelligence Techniques to Process Industry Problems. In: Nguyen, N.T., Kolaczek, G. and Gabrys, B., eds. Knowledge Processing and Reasoning for Information Society. Warsaw, Poland: EXIT Publishing House, pp. 305-322.

Eastwood, M. and Gabrys, B., 2008. Building Combined Classifiers. In: Nguyen, N.T., Kolaczek, G. and Gabrys, B., eds. Knowledge Processing and Reasoning for Information Society. Warsaw, Poland: EXIT Publishing House, pp. 139-163.

Lemke, C. and Gabrys, B., 2008. Do We Need Experts for Time Series Forecasting? In: 16th European Symposium on Artificial Neural Networks (ESANN'2008), April 2008, Bruges, Belgium, pp. 253-258.

Lemke, C. and Gabrys, B., 2008. Forecasting and Forecast Combination in Airline Revenue Management Applications. In: Nguyen, N.T., Kolaczek, G. and Gabrys, B., eds. Knowledge Processing and Reasoning for Information Society. Warsaw, Poland: EXIT Publishing House, pp. 231-247.

Kadlec, P. and Gabrys, B., 2008. Gating Artificial Neural Network Based Soft Sensor. In: Nguyen, N. T. and Katarzyniak, R., eds. New Challenges in Applied Intelligence Technologies. Berlin: Springer-Verlag, pp. 193-202.

Kadlec, P. and Gabrys, B., 2008. Learnt Topology Gating Artificial Neural Networks. In: Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on. IEEE, pp. 2604-2611.

Lemke, C. and Gabrys, B., 2008. On the Benefit of Using Time Series Features for Choosing a Forecasting Method. In: 2nd European Symposium on Time Series Prediction, 17-19 Sep 2008, Porvoo, Finland.

Tsakonas, A. and Dounias, G., 2008. Predicting Defects in Software Using Grammar-Guided Genetic Programming. In: Darzentas, J., Vouros , G., Vosinakis, S. and Arnellos, A., eds. Artificial Intelligence: Theories, Models and Applications: 5th Hellenic Conference on AI, SETN 2008, Syros, Greece, October 2-4, 2008, Proceedings. Berlin-Heidelberg: Springer-Verlag, pp. 413-418.

Ruta, D. and Gabrys, B., 2007. Reducing Spatial Data Complexity for Classification Models. In: Maroulis, G. and Simos, T.E., eds. Computational Methods in Science and Engineering: Theory and Computation: Old Problems and New Challenges (AIP Conference Proceedings). Melville, N.Y.: American Institute of Physics, pp. 603-613.

Riedel, S. and Gabrys, B., 2007. Dynamic Pooling for the Combination of Forecasts Generated Using Multi Level Learning. In: Neural Networks, 2007. IJCNN 2007. International Joint Conference on, 12-17 Aug. 2007, Orlando, FL,, pp. 454-459.

Isley, V. and Smith, P., 2007. Ornamental Bug Garden 002. Screen based computational art work.Southampton, UK: boredomresearch.

Tsakonas, A. and Dounias, G., 2007. Evolving Neural-Symbolic Systems Guided by Adaptive Training Schemes: Applications in Finance. Applied Artificial Intelligence, 21 (7), pp. 681-706.

Kadlec, P. and Gabrys, B., 2007. Nature-Inspired Adaptive Architecture for Soft Sensor Modelling. In: NiSIS'2007 Symposium: 3rd European Symposium on Nature-inspired Smart Information Systems, 26- 27 November 2007, St Julian's, Malta.

Ruta, D. and Gabrys, B., 2007. Neural Network Ensembles for Time Series Prediction. In: Neural Networks, 2007. IJCNN 2007. International Joint Conference on, 12-17 Aug. 2007, Orlando, FL,, pp. 1204-1209.

Lemke, C. and Gabrys, B., 2007. Review of Nature-Inspired Forecast Combination Techniques. In: NiSIS'2007 Symposium: 3rd European Symposium on Nature-inspired Smart Information Systems, 26- 27 November 2007, St Julian's, Malta.

Eastwood, M. and Gabrys, B., 2006. Lambda as a Complexity Control in Negative Correlation Learning. In: NiSIS'2006 Symposium : 2nd European Symposium on Nature-inspired Smart Information Systems, 29 November - 1 December 2006, Puerta de la Cruz, Tenerife, Spain.

Baruque, B., Corchado, E., Gabrys, B., Herrero, Á., Rovira, J. and Gonzalez, J., 2006. Unsupervised Ensembles Techniques for Visualization. In: NiSIS'2006 Symposium : 2nd European Symposium on Nature-inspired Smart Information Systems, 29 November - 1 December 2006, Puerta de la Cruz, Tenerife, Spain.

Bobeva, M., 2005. A Framework for Information Architecture for Business Networks. Doctorate Thesis (Doctorate). Bournemouth University.

Gunstone, R. E. and Lee, M.H., 2005. A Lens-Calibrated Active Marker Metrology System. In: TAROS 2005: The 2005 Towards Autonomous Robotic Systems Conference, 12-14 September, 2005, Imperial College, London, pp. 73-80.

Riedel, S. and Gabrys, B., 2005. Evolving Multilevel Forecast Combination Models - An Experimental Study. In: NiSIS'2005 (Nature-Inspired Smart information Systems) Symposium, 4- 5 October 2005, Albufeira, Portugal.

Ruta, D. and Gabrys, B., 2005. Nature-Inspired Learning Models. In: NiSIS'2005 (Nature-Inspired Smart Information Systems) Symposium, 4 - 5 October 2005, Albufeira, Portugal.

Gabrys, B. and Petrakieva, L., 2004. Selective sampling for combined learning from labelled and unlabelled data. In: Lotfi, A. and Garibaldi, J.M., eds. Applications and science in soft computing. London: Springer, pp. 139-148.

Riedel, S. and Gabrys, B., 2003. Adaptive Mechanisms in an Airline Ticket Demand Forecasting System. In: EUNITE'2003 Conference: European Symposium on Intelligent Technologies, Hybrid Systems and their implementation on Smart Adaptive Systems, 10 - 12 July 2003, Oulu, Finland.

Tsakonas, A., Nikolaidis, E. and Dounias, G., 2003. Application of Fundamental Analysis and Computational Intelligence in Dry Cargo Freight Market. In: Eunite 2003. Third European Symposium on Intelligent Technologies, Hybrid Systems and their implementation on Smart Adaptive Systems. Proceedings. Verlag-Meinz Publications.

Tsakonas, A. and Dounias, G., 2003. Decision Making in the Medical Domain: Comparing the Effectiveness of GP-Generated Fuzzy Intelligent Structures. In: Eunite 2003. Third European Symposium on Intelligent Technologies, Hybrid Systems and their implementation on Smart Adaptive Systems. Proceedings. Verlag-Meinz Publications.

Ruta, D. and Gabrys, B., 2003. Set analysis of coincident errors and its applications for combining classifiers. In: Chen, D. and Cheng, X., eds. Pattern Recognition and String Matching. Dordrecht; Boston: Kluwer Academic, pp. 647-672.

Gabrys, B., 2002. Combining Labelled and Unlabelled Data in the Design of Pattern Classification Systems. In: Hybrid Methods for Adaptive Systems (HMAS'2002) Workshop, 20 September 2002, Albufeira, Portugal.

Gabrys, B., 2002. Combining Neuro-Fuzzy Classifiers for Improved Generalisation and Reliability. In: Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on, May 12-17, 2002, Hilton Hawaiian Village Hotel, Honolulu, Hawaii, pp. 2410-2415.

Tsakonas, A. and Dounias, G., 2002. Hierarchical Classification Trees Using Type-Constrained Genetic Programming. In: First International IEEE on Intelligent Systems, 2002. Proceedings. Vol.3. IEEE, pp. 3-7.

Ruta, D. and Gabrys, B., 2001. Analysis of the Correlation Between Majority Voting Error and the Diversity Measures in Multiple Classifier Systems. In: Soft Computing and Intelligent Systems for Industry: Proceedings and Scientific Program : Fourth International ICSC Symposium 2001, 26-29 June, 2001, Paisley, Scotland, p. 50.

Gabrys, B., 2001. Data Editing for Neuro-Fuzzy Classifiers. In: Fourth International ICSC Symposium: Proceedings of the SOCO/ISFI’2001 Conference, June 26 - 29, 2001, Paisley, Scotland, p. 77.

Gabrys, B., 2001. Learning Hybrid Neuro-Fuzzy Classifier Models From Data: To Combine or Not to Combine? In: EUNITE'2001 Conference: European Symposium on Intelligent Technologies, Hybrid Systems and their Implementation on Smart Adaptive Systems, 13-14 December 2001, Puerto de la Cruz, Tenerife, Spain.

Gabrys, B., 2000. Agglomerative Learning for General Fuzzy Min-Max Neural Network. In: IEEE International Workshop on Neural Networks for Signal Processing, 11-13 December 2000, Sydney, Australia, pp. 692-701.

Vasilko, M., 2000. Design synthesis for dynamically reconfigurable logic systems. Doctorate Thesis (Doctorate). Bournemouth University.

Gabrys, B., 2000. Pattern classification for incomplete data. In: Knowledge-Based Intelligent Engineering Systems and Allied Technologies, 2000. Proceedings. Fourth International Conference on, 30 August -1 September 2000, Brighton, England, pp. 454-457.

Gabrys, B. and Bargiela, A., 2000. General fuzzy min-max neural network for clustering and classification. Neural Networks, IEEE Transactions on, 11 (3), pp. 769-783.

Rogers, P. A. P., 2000. The Baby project: processing character patterns in textual representations of language. Doctorate Thesis (Doctorate). Bournemouth University.

Ruta, D. and Gabrys, B., 2000. An Overview of Classifier Fusion Methods. Computing and Information Systems, 7 (1), pp. 1-10.

Fyfe, C. and Gabrys, B., 1999. E-insensitive Unsupervised Learning. In: International Conference on Neural Networks and Artificial Intelligence (ICNNAI'99), October 1999, Brest, Belarus, pp. 10-18.

Gabrys, B. and Bargiela, A., 1999. Analysis of Uncertainties in Water Systems Using Neural Networks. Measurement + Control, 32 (5), pp. 145-147.

Vine, D. S. G., 1998. Time-domain concatenative text-to-speech synthesis. Doctorate Thesis (Doctorate). Bournemouth University.

Gabrys, B. and Bargiela, A., 1997. Integrated Neural Based System for State Estimation and Confidence Limit Analysis in Water Networks. In: The 8th European Simulation Symposium, Ess 96. Society for Computer Simulation, pp. 398-402.

Eves, B., 1997. The Colour concept generator: a computer tool to propose colour concepts for products. Doctorate Thesis (Doctorate). Bournemouth University.

Gabrys, B. and Bargiela, A., 1995. Neural Simulation of Water Systems for Efficient State Estimation. In: The European Simulation and Modelling Conference (ESM'95), June 5-7, 1995, Prague, Czech Republic, pp. 775-779.

Browning, A. W., 1990. A Mathematical Model To Simulate Small Boat Behaviour. Doctorate Thesis (Doctorate). Bournemouth University.

This list was generated on Tue Sep 1 16:49:23 2015 IST.