نتایج جستجو برای: then fuzzy rules achieved during the training process in multi adaptive neuro
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This work is an attempt to illustrate the usage and effectiveness of soft computing techniques in the estimation and control of multi input and multi output systems. This paper focuses on neuro-fuzzy system ANFIS (Adaptive Neuro Fuzzy Inference system). An Adaptive Network based Fuzzy Interference System architecture extended to cope with multivariable systems has been used. The performance of ...
abstract nowadays, the science of decision making has been paid to more attention due to the complexity of the problems of suppliers selection. as known, one of the efficient tools in economic and human resources development is the extension of communication networks in developing countries. so, the proper selection of suppliers of tc equipments is of concern very much. in this study, a ...
In this paper, a novel method of hybrid filter for denoising digital images corrupted by mixed noise has been presented. The proposed design of hybrid filter utilizes the concept of neuro fuzzy network and spatial domain filtering. This method incorporates improved adaptive wiener filter and adaptive median filter to reduce white Gaussian noise and impulse noise respectively. Selection of filte...
abstract: in the paper of black and scholes (1973) a closed form solution for the price of a european option is derived . as extension to the black and scholes model with constant volatility, option pricing model with time varying volatility have been suggested within the frame work of generalized autoregressive conditional heteroskedasticity (garch) . these processes can explain a number of em...
In this article, a new type-2 fuzzy-based modeling approach is proposed to assess human operators’ psychophysiological states for both safety and reliability of human–machine interface systems. Such technique combines fuzzy sets with state tracking update the rule base through Bayesian process. These configurations successfully lead an adaptive, robust, transparent computational framework that ...
ANFIS systems have been much considered due to their acceptable performance in terms of creation of fuzzy classifier and training. One main challenge in designing an ANFIS system is to achieve an efficient method with high accuracy and appropriate interpreting capability. Undoubtedly, type and location of membership functions and the way an ANFIS network is trained are of considerable effect on...
This study seeks to develop a fuzzy expert system to help managers in assessing their effectiveness and position of their business on the manufacturing excellence track. Assessment process is multi-dimensional in nature and there is a relationship between the different variables of the system. In addition, both quantitative and qualitative variables as well as the uncertainty in the statements ...
abstract this research is about a longitudinal case study of english morpheme acquisition by a persian speaking child l2 learner of english (2 .9-3).the goal of this research has been discovery of the child ‘s ability in acquiring of english morphemes in a persian context while only one person (the child’ s father)has been talking to her.this child has also been exposed to english languag...
Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used. First,...
Neuro-fuzzy classi cation systems allow to derive fuzzy classi ers by learning from data. The obtained fuzzy rule bases are sometimes hard to interpret, even if the learning method uses constraints to ensure an appropriate fuzzy partitioning of the input domains. This paper describes an approach to build more expressive rules by performing boolean transformations during and after the learning p...
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