Fusion of neural networks, fuzzy sets, and genetic algorithms

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Alan F. Murray

Applications of Neural Networks gives a detailed description of 13 practical applications of neural networks, selected because the tasks performed by the neural networks are real and significant. The contributions are from leading researchers in neural networks and, as a whole, provide a balanced coverage across a range of application areas and algorithms. The book is divided into three sections. Section A is an introduction to neural networks for nonspecialists. Section B looks at examples of applications using `Supervised Training'. Section C presents a number of examples of `Unsupervised Training'. For neural network enthusiasts and interested, open-minded sceptics. The book leads the latter through the fundamentals into a convincing and varied series of neural success stories -- described carefully and honestly without over-claiming. Applications of Neural Networks is essential reading for all researchers and designers who are tasked with using neural networks in real life applications.

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A.F. Rocha

"The purpose of this book is to develop neural nets as a strong theory for both brains and machines. The theory is developed in close correlation with the biology of the neuron and the properties of human reasoning. This approach implies the following: - Updating the biology of the artificialneuron. The neurosciences have experienced a tremendous development in the last 50 years. One of the main purposes of the present work is toincorporate this knowledge into a strong model of the artificial neuron. Particular attention is devoted to formalizing the complex chemical processes at the synaptic level. This formal language supports both symbolicreasoning and uncertainty processing. - Investigating the properties of expert reasoning. This kind of reasoning is approximate, partial and non-monotonic, and therefore requires special mathematical tools for its formalization, such as fuzzy set theory and fuzzy logic. Three different intelligent systems developed with this technology are presented and discussed."--PUBLISHER'S WEBSITE.

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Robert J. Jannarone

Many monitoring, forecasting, and control operations occur in settings where relationships among key measurements must be learned quickly. Examples are on-line industrial processes where influent material is not consistent over time, energy load or price forecasting where demand characteristics change rapidly,and health management where relationships among monitored variables must be learned for each patient-treatment combination. The solution presented is a new neuro-computing system that learns in real-time, even when data arrival rates are several million measurements per second. The book describes benefits and features of the system, statistical foundations for the system, and several related models. The book also describes available system software.

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Jim Jubak

A book about science and metaphors ; about how to build a computer ; and a book about how a technology called neural networks is changing the way we think about machines, computers, brains and minds.