Adaptive Modelling, Estimation and Fusion from Data: A Neurofuzzy Approach (Advanced Information Processing)

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This book brings together for the first time the complete theory of data based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive mathematical framework. After introducing the basic theory of data based modelling new concepts including extended additive and multiplicative submodels are developed. All of these algorithms are illustrated with benchmark examples to demonstrate their efficiency. The book aims at researchers and advanced professionals in time series modelling, empirical data modelling, knowledge discovery, data mining and data fusion.

Adaptive Modelling, Estimation and Fusion from Data: A Neurofuzzy Approach (Advanced Information Processing) Review

While i do not deny the contribution at providing a more or less complete treatment of neurofuzzy techniques for data modeling, i'm still wondering where the non-theoretical chapters dealing with how to cope with real data with these techniques are hidden. The few examples in the book are mostly artificial and very limited in their scope. i'm not sure people dealing with data have an interest at reading this book, it's more about neurofuzzy techniques than data modelling.The book edited by Schwefel, Weneger and Weinert entitled "Advances in computational intelligence" published by Springer emphasizes a lot more on fuzzy techniques based on real data although it does not discuss the "neuro" part of "neuro-fuzzy" techniques.Still this book is not bad from a theoretical neuro-fuzzy perspective, but since these techniques are aimed at dealing with real data, i would have hoped a much better treatment of the practical aspects, which it fails to provide. Help other customers find the most helpful reviews Was this review helpful to you?�Yes No Report abuse | PermalinkComment�Comment

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