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Fuzzy Rule Generation

Name: Fuzzy Rule Generation
Brand: Noor Publishing
SKU: 9783330969339
Price: 12082 HUF
Availability: InStock

Based on Subtractive Clustering and Gradient Descent

Szerző: Zahraa Abed Mohammed

Nyelv:

Kötés: Puha kötésű

Kiadó: Noor Publishing

Elérhetőség: Beszállítói készleten

Küldés 5-8 napon belül

12 082 Ft

In recent years, a wide range of problems are handled by fuzzy models. Fuzzy model prefers on classi...

Információk a könyvről

Szerző

Zahraa Abed Mohammed

Nyelv

Angol

Kötés

Könyv - Puha kötésű

Kiadva

2017

oldal

EAN

9783330969339

Enbook ID

16451737

Kiadó

Noor Publishing

Súly

131

Méretek

150 x 220 x 5

Teljes leírás

In recent years, a wide range of problems are handled by fuzzy models. Fuzzy model prefers on classic models due its ability to deal with imprecise data, model the complex nonlinear problems and acquiring knowledge with these models. Fuzzy rule is a special case of fuzzy modeling, where its working principle is representing the behavior of the system by a set fuzzy if-then classification rules. An intelligent technique has been proposed in this thesis which it depends on a Takagi- Sugeno-Kang (TSK) fuzzy modeling, subtractive clustering method and an efficient gradient descent algorithm. This approach uses subtractive clustering method to extract the fuzzy classification rules from data; the rule's parameters are then optimized by using an efficient gradient descent algorithm. The dataset firstly is divided into main classes, and then the subtractive algorithm is applied for each class. The clusters centers set, and sigma set are generated from this clustering process. To enhance the performance of the system, a gradient descent method is employed which represents the optimization method that it is used to adjust the value of the clusters centers and sigma values.

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Fuzzy Rule Generation

Based on Subtractive Clustering and Gradient Descent

Információk a könyvről

Teljes leírás

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