نتایج جستجو برای: various neural network and fuzzy logic models established for neural network and fuzzy logic

تعداد نتایج: 19232728  

In this work, an artificial neural network (ANN) model along with a combination of adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO) i.e. (PSO-ANFIS) are proposed for modeling and prediction of the propylene/propane adsorption under various conditions. Using these computational intelligence (CI) approaches, the input parameters such as adsorbent shape (S<su...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه تربیت مدرس 1389

abstract: country’s fiber optic network, as one of the most important communication infrastructures, is of high importance; therefore, ensuring security of the network and its data is essential. no remarkable research has been done on assessing security of the country’s fiber optic network. besides, according to an official statistics released by ertebatat zirsakht company, unwanted disconnec...

2011
Lai Zheng Xianghai Meng

Road accident prediction plays an important role in accessing and improving the road safety. Besides the conventional generalized linear regression, the prediction approaches based on fuzzy logic and neural networks have increasingly been proven to have a significant accident-predicting capability in recent years. However, fuzzy logic and neural network have their respective limitations. For ex...

1998
Yanqing Zhang Abraham Kandel

compensatory genetic fuzzy neural networks and their applications neural networks fuzzy logic and genetic algorithms by rajasekaran and g a v pai ebook free download nonlinear workbook chaos fractals cellular automata neural networks genetic algorithms gene expression programming wavelets fuzzy logic with c java and symbolicc programs applications of neural networks in environment energy and he...

Abazar Solgi, Feridon Radmanesh Heidar Zarei Vahid Nourani

Awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. Therefore, the present study two hybrid models, Wavelet- Adaptive Neural Fuzzy Interference System (WANFIS) and Wavelet- Artificial Neural Network (WANN) are used for flow prediction of Gamasyab River (Nahavand, Hamedan, Iran...

Journal: :international journal of industrial mathematics 0
a. jafarian department of mathematics, urmia branch, islamic azad university, urmia, iran. s. measoomy nia department of mathematics, urmia branch, islamic azad university, urmia, iran.

this paper intends to offer a new iterative method based on arti cial neural networks for finding solution of a fuzzy equations system. our proposed fuzzi ed neural network is a ve-layer feedback neural network that corresponding connection weights to output layer are fuzzy numbers. this architecture of arti cial neural networks, can get a real input vector and calculates its corresponding fu...

The ever-growing use of various vehicles for transportation, on the one hand, and the statistics ofsoaring road accidents resulting from human error, on the other hand, reminds us of the necessity toconduct more extensive research on the design, manufacturing and control of driver-less intelligentvehicles. For the automatic control of an autonomous vehicle, we need its dynamic...

Abazar Solgi, Feridon Radmanesh Heidar Zarei Vahid Nourani

Awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. Therefore, the present study two hybrid models, Wavelet- Adaptive Neural Fuzzy Interference System (WANFIS) and Wavelet- Artificial Neural Network (WANN) are used for flow prediction of Gamasyab River (Nahavand, Hamedan, Iran...

Journal: :Int. J. Intell. Syst. 1996
Wangming Wu Hoon heng Teh Bo Yuan

Reasoning with propositional knowledge based on fuzzy neural logic" (1996). In this article, a new kind of reasoning for propositional knowledge, which is based on the fuzzy neural logic initialed by Teh, is introduced. A fundamental theorem is presented showing that any fuzzy neural logic network can be represented by operations: bounded sum, complement, and scalar product. Propositional calcu...

2012
Venus Marza Amin Seyyedi Luiz Fernando Capretz

Software estimation accuracy is among the greatest challenges for software developers. This study aimed at building and evaluating a neuro-fuzzy model to estimate software projects development time. The forty-one modules developed from ten programs were used as dataset. Our proposed approach is compared with fuzzy logic and neural network model and Results show that the value of MMRE (Mean of M...

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