نتایج جستجو برای: grey wolf optimizer
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The recent techniques built on cloud computing for data processing is scalable and secure, which increasingly attracts the infrastructure to support big applications. This paper proposes an effective anonymization based privacy preservation model using k-anonymization criteria Grey wolf-Cat Swarm Optimization (GWCSO) attaining in data. technique processed by adapting k- duplicating k records fr...
The present research proposes a new particle swarm optimization-based metaheuristic algorithm entitled “search in forest optimizer (SIFO)” to solve the global optimization problems. is designed based on organized behavior of search teams looking for missing persons forest. According SIFO optimizer, number each including several experts field spread out across and gradually move same direction b...
Meta-heuristic Algorithms (MA) are widely accepted as excellent ways to solve a variety of optimization problems in recent decades. Grey Wolf Optimization (GWO) is a novel Meta-heuristic Algorithm (MA) that has been generated a great deal of research interest due to its advantages such as simple implementation and powerful exploitation. This study proposes a novel GWO-based MA and two extra fea...
This paper deals with automatic generation control of multi area power system using a Fuzzy PID controller. The controller parameters are optimized by Grey Wolf Optimizer (GWO) algorithm. Initially, Hydro-Thermal-Gas two area power systems is considered and superiority of the proposed controller is verified by comparing the results with GWO optimized classical PID controller as well as recently...
The computational complexity grows exponentially for multi-level thresholding (MT) with the increase of the number of thresholds. Taking Kapur’s entropy as the optimized objective function, the paper puts forward the modified quick artificial bee colony algorithm (MQABC), which employs a new distance strategy for neighborhood searches. The experimental results show that MQABC can search out the...
A Novel Hybrid Method of Global Optimization Based on the Grey Wolf Optimizer and the Bees Algorithm
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