Над 4 милиона заглавия на английски и други езици! Открийте новата си история още днес! Безплатна доставка за поръчки над 69.99€

Виж статуса на поръчката

Свържете се с нас

Fuzzy Cognitive Maps for Applied Sciences and Engineering

From Fundamentals to Extensions and Learning Algorithms

Автор: Elpiniki I. Papageorgiou

Език:

Корици: С меки корици

Издател: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Наличност: Външен склад

Изпращаме след 5-8 дни

105.32 € 205.99 лв

Fuzzy Cognitive Maps (FCM) constitute cognitive models in the form of fuzzy directed graphs consisti...

Информация за книгата

Автор

Elpiniki I. Papageorgiou

Език

Английски език

Корици

Книга - С меки корици

Издадена

2016

страници

395

EAN

9783662522141

ISBN

3662522144

Enbook ID

16083130

Издател

Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Теглоt

869

Размери

155 x 235 x 23

Пълно описание

Fuzzy Cognitive Maps (FCM) constitute cognitive models in the form of fuzzy directed graphs consisting of two basic elements: the nodes, which basically correspond to " concepts" bearing different states of activation depending on the knowledge they represent, and the " edges" denoting the causal effects that each source node exercises on the receiving concept expressed through weights. Weights take values in the interval [-1,1], which denotes the positive, negative or neutral causal relationship between two concepts. An FCM can be typically obtained through linguistic terms, inherent to fuzzy systems, but with a structure similar to the neural networks, which facilitates data processing, and has capabilities for training and adaptation. During the last 10 years, an exponential growth of published papers in FCMs was followed showing great impact potential. Different FCM structures and learning schemes have been developed, while numerous studies report their use in many contexts with highly successful modeling results. The aim of this book is to fill the existing gap in the literature concerning fundamentals, models, extensions and learning algorithms for FCMs in knowledge engineering. It comprehensively covers the state-of-the-art FCM modeling and learning methods, with algorithms, codes and software tools, and provides a set of applications that demonstrate their various usages in applied sciences and engineering.