Investigation Bat Algorithm Based on Artificial Bee Colony and C-means

Investigation Bat Algorithm Based on Artificial Bee Colony and C-means

In this study a Bat algorithm clustering is proposed that is based on Artificial Bee Colony (ABC)and Fuzzy C-means (FCM). When FCM is applied on high dimensional dataset, it usually resultsin local optimal partitioning. In this paper we address this problem and used a recently developedevolutionary technique named Artificial Bee Colony in combination to FCM. Hence, the name isFuzzy Cmeans Bee (FCB) algorithm. The method can detect globally optimal cluster centeroidsbetter than FCM as a most ...

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Prediction of Water Quality of Ajichay River using developed Artificial Neural Network and Supporting Vector Machine Models

Prediction of Water Quality of Ajichay River using developed Artificial Neural Network and Supporting Vector Machine Models

International efforts have been launched to save the endangered Urmia Lake as one of the largest natural lake worldwide. Ajichay River located in East Azarbaijan province, Iran, is one of the main rivers discharging into this lake and, thus, its water quality can directly affect the Urmia Lake ecosystem and life. In this research, we develop and propose two new numerical packages on the basis of Artificial Neural Network (ANN) and Supporting Vector Machine (SVM) models to estimate the monthly ...

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Weighted triangular approximation of fuzzy by artificial bee colony algorithm

Weighted triangular approximation of fuzzy by artificial bee colony algorithm

In this paper , we obtain the nearest triangular approximation to a fuzzy quantity with weighted function by minimization distance between two fuzzy numbers gnisu yb artificial bee colony algorithm( ABC). I important advantage of the ABC method is that this method is capable of greatly reducing the size of computational work while still maintaining high accuracy of the numerical solution and increase Convergence rate . ...

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