نتایج جستجو برای: sigmoid based membership function

تعداد نتایج: 3923858  

Neural network is one of the new soft computing methods commonly used for prediction of the thermodynamic properties of pure fluids and mixtures. In this study, we have used this soft computing method to predict the coefficients of the Antoine vapor pressure equation. Three transfer functions of tan-sigmoid (tansig), log-sigmoid (logsig), and linear were used to evaluate the performance of diff...

Journal: :Neurocomputing 2007
Cheng-Jian Lin I-Fang Chung Cheng-Hung Chen

In this paper, an entropy-based quantum neuro-fuzzy inference system (EQNFIS) for classification applications is proposed. The EQNFIS model is a five-layer structure, which combines the traditional Takagi-Sugeno-Kang (TSK). Layer 2 of the EQNFIS model contains quantum membership functions, which are multilevel activation functions. Each quantum membership function is composed of the sum of sigm...

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه فردوسی مشهد - دانشکده مهندسی 1389

abstract type-ii fuzzy logic has shown its superiority over traditional fuzzy logic when dealing with uncertainty. type-ii fuzzy logic controllers are however newer and more promising approaches that have been recently applied to various fields due to their significant contribution especially when the noise (as an important instance of uncertainty) emerges. during the design of type- i fuz...

In this paper, a new approach is proposed in order to select an optimal membership function for inputs of wind speed prediction system. Then using a fuzzy method and the stochastic characteristics of wind speed in the previous year, the wind speed modeling is performed and the wind speed for the future year will be predicted. In this proposed method, the average and the standard deviation of in...

2006
Yi-kun Tao Jun Meng

During the procedure of fuzzy modeling, we use various methods to update the parameters of membership functions and the shapes of MFs change during the training procedure. So it is obvious that the shape and the distribution of MFs (not a single MF) must implicate some kinds of knowledge of target function (the function to fit) or the problem we try to model. This paper introduced the entropy E...

1995
Taner Bilgiç I. Burhan Türkşen

This chapter presents a review of various interpretations of the fuzzy membership function together with ways of obtaining a membership function. We emphasize that different interpretations of the membership function call for different elicitation methods. We try to make this distinction clear using techniques from measurement theory. 3.

Journal: :IJFSA 2015
Asit Dey Madhumangal Pal

This paper presents a method to construct more general fuzzy complex numbers and sets from ordinary fuzzy complex numbers by introduced the ordered sequences of membership functions. It is concluded that multifuzzy complex set is an extension of Buckley fuzzy complex set. Also, two types of multi-fuzzy complex numbers based on the forms z x iy = + and z re = θ are investigated. Multi-Fuzzy Comp...

2008
Zhongfeng Qin Xin Gao

In this paper, we consider fractional Liu process. First, the membership functions, expected values and variances of arithmetic and geometric fractional Liu process are given. Then we suppose that stock price follows geometric fractional Liu process and formulate fractional Liu’s stock model. Based on this model, European option pricing formulas are obtained.

     In this study, the predictive performance of three Artificial Neural Networks (ANNs), i.e. Co-Active NeuroFuzzy Inference System (CANFIS), Multi-Layer Perceptron (MLP) and MLP integrated with Genetic Algorithm (GA) in the Zoshk-Abardeh watershed were compared. In this study, three scenarios were considered and simulated in each model. In order to simulate the scenario S1 water flow were fe...

2012
Satyendra Nath Mandal

Many researchers have used fuzzy logic system to predict the time series data. In fuzzy system, the crisp data are converting into fuzzy data based on membership function. The futuristic data is predicted using previous data and fuzzy relation. But, in fuzzy system, there are many existing and derived membership functions which are used to fuzzify data. In this paper, an effort has been made to...

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