نتایج جستجو برای: genetic algorithm fuzzy clustering ipri masloweconomic performance

تعداد نتایج: 2300380  

2008
Dimitrios K. Iakovidis Nikos Pelekis Evangelos E. Kotsifakos Ioannis Kopanakis

Intuitionistic fuzzy sets are generalized fuzzy sets whose elements are characterized by a membership, as well as a non-membership value. The membership value indicates the degree of belongingness, whereas the nonmembership value indicates the degree of non-belongingness of an element to that set. The utility of intuitionistic fuzzy sets theory in computer vision is increasingly becoming appare...

Multicast routing is one of the most important services in Multi Radio Multi Channel (MRMC) Wireless Mesh Networks (WMN). Multicast routing performance in WMNs could be improved by choosing the best routes and the routes that have minimum interference to reach multicast receivers. In this paper we want to address the multicast routing problem for a given channel assignment in WMNs. The channels...

2009
Tomoyuki Kuwata Mika Sato-Ilic

The purpose of this paper is to improve the performance of the kernel fuzzy clustering model by introducing a self-organized algorithm. A conventional kernel fuzzy clustering model is defined as a model which is an improved additive fuzzy clustering. The purpose of this conventional model is to obtain a clearer result by consideration of the interaction of clusters. This paper proposes a fuzzy ...

This paper proposes the exchange market algorithm (EMA) to solve the combined economic and emission dispatch (CEED) problems in thermal power plants. The EMA is a new, robust and efficient algorithm to exploit the global optimum point in optimization problems. Existence of two seeking operators in EMA provides a high ability in exploiting global optimum point. In order to show the capabilities ...

Journal: :Pattern Recognition 1991
Shokri Z. Selim K. Alsultan

In this paper we discuss the solution of the clustering problem usually solved by the K-means algorithm. The problem is known to have local minimum solutions.A simulated annealing algorithm for the clustering problem. The solution of the clustering problem usually solved by the K-means algorithm.In this paper, we explore the applicability of simulated annealing. Clustering problem is investigat...

2014

The main aspiration of Grid Computing is to aggregate the maximum available idle computing power of the distributed resources, and provide well-organized services to users. An efficient grid resource allocation is very much essential to achieve this aspiration. Researchers had proposed many grid scheduling mechanisms in the past to fulfill this aspiration, but, these are mostly based on traditi...

Journal: :journal of ai and data mining 2015
a. ghaffari s. nobahary

wireless sensor networks (wsns) consist of a large number of sensor nodes which are capable of sensing different environmental phenomena and sending the collected data to the base station or sink. since sensor nodes are made of cheap components and are deployed in remote and uncontrolled environments, they are prone to failure; thus, maintaining a network with its proper functions even when und...

2015
Shutao GAO

Mono-nuclear kernel function is presented in this paper based on the fuzzy c-means clustering algorithm for data clustering to do the improvement in the field of data mining, puts forward the fuzzy c-means clustering algorithm based on multiple kernel function (MKFCM) algorithm. Under fully unsupervised learning method, a set of Gaussian kernel function combination are assigned different weight...

2013
Parisut Jitpakdee Pakinee Aimmanee Bunyarit Uyyanonvara

Firefly algorithm is a swarm-based algorithm that can be used for solving optimization problems. In this paper, we focus on image clustering algorithm using the fuzzy set of possible solution is incorporated into the original firefly to improve the performance. The movement of the firefly still follows the original pattern but they are updated according fuzzy c-means algorithm. All method, k-me...

ژورنال: محاسبات نرم 2017

This study presents a novel intelligent Fuzzy Genetic Differential Evolutionary model for the optimization of a fuzzy expert system applied to heart disease prediction in order to reduce the risk of heart disease. To this end, a fuzzy expert system has been proposed for the prediction of heart disease. The proposed model can be used as a tool to assist physicians. In order to: (1) tune the para...

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