Evolutionary computation and its applications. 1. Maximal margin algorithms for pose estimation / Ying Guo and Jiaming Li. 2. Polynomial modeling in a dynamic environment based on a particle swarm optimization / Kit Yan Chan and Tharam S. Dillon. 3. Restoration of half-toned color-quantized images using particle swarm optimization with multi-wavelet mutation / Frank H. F. Leung, Benny C. W. Yeung and Y. H. Chan -- Fuzzy logics and their applications. 4. Hypoglycemia detection for insulin-dependent diabetes mellitus: evolved fuzzy inference system approach / S. H. Ling, P. P. San and H. T. Nguyen -- Neural networks and their applications. 5. Study of limit cycle behavior of weights of perceptron / C. Y. F. Ho and B. W. K. Ling. 6. Artificial neural network modeling with application to nonlinear dynamics / Yi Zhao. 7. Solving Eigen-problems of matrices by neural networks / Yiguang Liu ... [et al.]. 8. Automated screw insertion monitoring using neural networks: a computational intelligence approach to assembly in manufacturing / Bruno Lara, Lakmal D. Seneviratne and Kaspar Althoefer -- Support vector machines and their applications. 9. On the applications of heart disease risk classification and hand-written character recognition using support vector machines / S. R. Alty, H. K. Lam and J. Prada. 10. Nonlinear modeling using support vector machine for heart rate response to exercise / Weidong Chen ... [et al.]. 11. Machine learning-based nonlinear model predictive control for heart rate response to exercise / Yi Zhang ... [et al.]. 12. Intelligent fault detection and isolation of HVAC system based on online support vector machine / Davood Dehestani ... [et al.]
This book focuses on computational intelligence techniques and their applications - fast-growing and promising research topics that have drawn a great deal of attention from researchers over the years. It brings together many different aspects of the current research on intelligence technologies such as neural networks, support vector machines, fuzzy logic and evolutionary computation, and covers a wide range of applications from pattern recognition and system modeling, to intelligent control problems and biomedical applications. Fundamental concepts and essential analysis of various computational techniques are presented to offer a systematic and effective tool for better treatment of different applications, and simulation and experimental results are included to illustrate the design procedure and the effectiveness of the approaches.