Fuzzy logic and artificial neural network for hydrological modeling: a case study of Brahmaputra basin in India par Deka, Paresh Chandra, Chandramoulli, V: New paperback (2011)

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Titre: Fuzzy logic and artificial neural network for hydrological modeling: a case study of Brahmaputra basin in India
�diteur: LAP LAMBERT Academic Publishing
Date de parution: 2011
Langue: anglais
ISBN � 10 chiffres: 3846542245
ISBN � 13 chiffres: 9783846542248
Reliure: paperback
�tat de l'article: New
Type de livre: book

A propos de ce titre

Synopsis

The combination of Artificial Neural Network and Fuzzy Logic are probably the most attractive techniques among the researchers in recent times which is capable of handling non-linear, imprecise, fuzzy, noisy and probabilistic information to solve complex problem in efficient manner. Hybrid systems are designed to take advantage of the strengths of each system and avoid the limitations of each system. It is natural for neural networks to learn but it is cumbersome for a fuzzy system to learn. Hence a combination of the two would result in a rule- based system that can learn and adapt. This book, therefore, provide a comprehensive and integrated approach using Fuzzy logic and Artificial neural network techniques in modeling selected hydrological problems related to International river Brahmaputra within India. Four different hydrological problems are modeled using the proposed fuzzy – neural network approach for examining the usefulness of it. This comprehensive real time hydrological modelling study should be especially useful to the Hydrologist, civil engineers, agriculturists, students, field engineers and related governmental as well as non-governmental organisations.

Pr�sentation de l'�diteur

The combination of Artificial Neural Network and Fuzzy Logic are probably the most attractive techniques among the researchers in recent times which is capable of handling non-linear, imprecise, fuzzy, noisy and probabilistic information to solve complex problem in efficient manner. Hybrid systems are designed to take advantage of the strengths of each system and avoid the limitations of each system. It is natural for neural networks to learn but it is cumbersome for a fuzzy system to learn. Hence a combination of the two would result in a rule- based system that can learn and adapt. This book, therefore, provide a comprehensive and integrated approach using Fuzzy logic and Artificial neural network techniques in modeling selected hydrological problems related to International river Brahmaputra within India. Four different hydrological problems are modeled using the proposed fuzzy – neural network approach for examining the usefulness of it. This comprehensive real time hydrological modelling study should be especially useful to the Hydrologist, civil engineers, agriculturists, students, field engineers and related governmental as well as non-governmental organisations.

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