Fuzzy logic augmentation of neural and optimization algorithms: theoretical aspects and real applications.

摘要

There have been many recent developments related to fuzzy logic applications. This book, volume 749 in Springer's "Studies in Computational Intelligence" series, contains research papers related to fuzzy logic, neural networks, and metaheuristics for optimization. It covers their use in diverse areas such as intelligent control, robotics, pattern recognition, medical diagnosis, time series prediction, and optimization. The book has seven parts (38 chapters). The first part studies the use of type-2 fuzzy logic in metaheuristics. Its five chapters describe type-2 fuzzy logic applications related to the grey wolf optimizer algorithm, the optimization of neural networks, harmony search, bio-inspired techniques, and evolutionary algorithms. The second part concentrates on the theory and application of neural networks. The four chapters study applications related to biometrics, the melting points of liquids, walking patterns, and pattern recognition. The third part, "Metaheuristics," has five chapters. The applications discussed include the tuning of support vector machine (SVM) classifiers, mathematical optimization, protein folding, particle hydrodynamics, and symbolic regression. The fourth part, "Fuzzy Control," has five chapters. One chapter discusses the problem of determining uncertainty in control applications, while the rest look at applications in mobile robotics.