Evolving Intelligent Systems.
PART I: METHODOLOGY.
Evolving Fuzzy Systems.
1. Learning Methods for Evolving Intelligent Systems (R. Yager).
2. Evolving Takagi-Sugeno Fuzzy Systems from Data Streams (eTS+) (P. Angelov).
3. Fuzzy Models of Evolvable Granularity (W. Pedrycz).
4. Evolving Fuzzy Modeling Using Participatory Learning (E. Lima, M. Hell, R. Ballini, and F. Gomide).
5. Towards Robust and Transparent Evolving Fuzzy Systems (E. Lughofer).
6. The building of fuzzy systems in real-time: towards interpretable fuzzy rules (A. Dourado, C. Pereira, and V. Ramos).
Evolving Neuro-Fuzzy Systems.
7. On-line Feature Selection for Evolving Intelligent Systems (S. Ozawa, S. Pang, and N. Kasabov).
8. Stability Analysis of an On-Line Evolving Neuro-Fuzzy Network (J. de J. Rubio Avila).
9. On-line Identification of Self-organizing Fuzzy Neural Networks for Modelling Time-varying Complex Systems (G. Prasad, T. M. McGinnity, and G. Leng).
10. Data Fusion via Fission for the Analysis of Brain Death (L. Li, Y. Saito, D. Looney, T. Tanaka, J. Cao, and D. Mandic).
Evolving Fuzzy Clustering and Classification.
11. Similarity Analysis and Knowledge Acquisition by Use of Evolving Neural Models and Fuzzy Decision (G. Vachkov).
12. An Extended version of Gustafson-Kessel Clustering Algorithm for Evolving Data Stream Clustering (D. Filev, and O. Georgieva).
13. Evolving Fuzzy Classification of Non-Stationary Time Series (Y. Bodyanskiy, Y. Gorshkov, I. Kokshenev, and V. Kolodyazhniy).
PART II: APPLICATIONS OF EIS.
14. Evolving Intelligent Sensors in Chemical Industry (A. Kordon et al.).
15. Recognition of Human Grasps by Fuzzy Modeling (R Palm, B Kadmiry, and B Iliev).
16. Evolutionary Architecture for Lifelong Learning and Real-time Operation in Autonomous Robots (R. J. Duro, F. Bellas and J.A. Becerra) 17. Applications of Evolving Intelligent Systems to Oil and Gas Industry (J. J. Macias Hernandez et al.).
- The first self-contained volume that covers the topic of Evolving Intelligent Systems in its entirety, from a systematic methodology to case studies and real industrial applications
- Includes downloadable software resources
- Useful as a source of theoretical approaches (methodology), and as a handbook for techniques, algorithms and case studies for solved practical problems
Part of the IEEE Series on Computational Intelligence