نتایج جستجو برای: we designed a fuzzy inference system employees
تعداد نتایج: 14091109 فیلتر نتایج به سال:
in this paper, we consider the production possibility set with n production units such that the following four principles that governs: inclusion observations, conceivability, immensity and convexity. our goal is to estimate the output of a same and new production unit with existing production possibility and amount of input is specified. so, initially we find the interval changes of each input...
suitable soil structure is important for crop growth. one of the main characteristics of soil structure is the size of soil aggregates. there are several ways of showing the stability of soil aggregates, among which the determination of the median weight diameter of soil aggregates is the most common method. in this paper, a method based on adaptive neuro fuzzy inference system (anfis) was used...
Distributed flexible AC- transmission system (D-FACTS) is a recently advanced FACTS device with high flexibility and smaller size. The DPFC can control power flow in transmission lines, regulate bus voltages and it can also enhance stability margin in power grids. Adaptive-neural network-based fuzzy inference system (ANFIS) combines features of artificial neural network and fuzzy controller. Th...
in this thesis, we exploit a simple and suitable method for immobilization of copper(ii) complex of 4?-phenyl-terpyridine on activated multi-walled carbon nanotubes [amwcnts-o-cu(ii)-phtpy]. this nanostructure was characterized by various physico-chemical techniques. to ensure the efficiency and fidelity of copper species, the implementation of three-component strategies in click-chemistry all...
In this paper, an Adaptive Neuro Fuzzy Inference System (ANFIS) based control is proposed for the tracking of a Micro-Electro Mechanical Systems (MEMS) gyroscope sensor. The ANFIS is used to train parameters of the controller for tracking a desired trajectory. Numerical simulations for a MEMS gyroscope are looked into to check the effectiveness of the ANFIS control scheme. It proves that the sy...
support vector regression (svr) is a learning method based on the support vector machine (svm) that can be used for curve fitting and function estimation. in this paper, the ability of the nu-svr to predict the catalytic activity of the fischer-tropsch (ft) reaction is evaluated and the result is compared with two other prediction techniques including: multilayer perceptron (mlp) and subtractiv...
modeling of stream flow–suspended sediment relationship is one of the most studied topics in hydrology due to itsessential application to water resources management. recently, artificial intelligence has gained much popularity owing toits application in calibrating the nonlinear relationships inherent in the stream flow–suspended sediment relationship. thisstudy made us of adaptive neuro-fuzzy ...
In this paper we present KERNEL, a neuro-fuzzy system for the extraction of knowledge directly from data, and a toolbox developed in the Matlab environment for its implementation. The KERNEL system belongs to the novel approach which concerns the use and representation of explicit knowledge within the neurocomputing paradigm: the Knowledge Based Neurocomputing. A specific neural network is desi...
this paper introduces an indirect adaptive fuzzy sliding mode controller as a power system stabilizer for damping local and inter-area modes of oscillations of multi-machine power systems. this controller is designed based on the combination of sliding mode controller and the fuzzy logic systems. the fuzzy systems are used to approximate the unknown functions of power system model. generator sp...
The present article discusses and presents a new comprehensive approach aimed at measuring the maturity and quality of software processes. This method has been designed on the basis of Software Capability Maturity Model (SW-CMM) and the Multi-level Fuzzy Inference Model and is used as a measurement and analysis tool. Among the most important characteristics of this method one can mention simple...
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