Lakhmi C.Jain and N.M. Martin – Fusion of Neural Networks Fuzzy Systems and Genetic Algorithms

Artificial neural networks can mimic the biological information-processing mechanism. A basis for human reasoning is provided by fuzzy logic. Neural networks show promise in solving problems, but there is no definitive theoretical basis for their design. It’s not like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it Neural net, fuzzy system, and evolutionary computing are included in the fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms to help readers handle complexity by offsetting the merits of one paradigm by the merits of another. It’s not like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it’s like it Specific projects where fusion techniques have been applied are presented in this book. The design of a fuzzy-neural controller is the beginning of the chapters. The application of expert systems, neural networks, fuzzy control, and evolutionary computing techniques are discussed in the remaining chapters. Specific applications are included. direct frequencies. The systems are called electro-hydraulic. Motor control. The control of the toast. Speech recognition. The vehicle route. fault diagnosis Asynchronous Transfer Mode is used for communications networks. Hard-of-hearing people can use telephones. The control of gas turbine aero-engines. The design of telecommunications systems. The benefits of fusion techniques in industrial applications are covered in the spectrum of applications.