In this paper, stochastic leader gravitational search algorithm (SL-GSA) based on randomized k is proposed. Standard GSA (SGSA) utilizes the best agents without any randomization, thus it is more prone to converge at suboptimal results. Initially, the new approach randomly choses k agents from the set of all agents to improve the global search ability. Gradually, the set of agents is reduced by...

Gravitational Search Algorithm (GSA) is a stochastic population-based metaheuristic designed for solving continuous optimization problems. It has a flexible and well-balanced mechanism for enhancing exploration and exploitation abilities. In this paper, we adapt the structure of GSA for solving the data clustering problems, the process of grouping data into clusters such that the data in each c...

The Gated Single-Assignment (GSA) program representation is an extension of the Static Single Assignment (SSA) representation[CFR91]. GSA was introduced by Ballance, Maccabe and Ottenstein as a part of Program Dependence Web (PDW)[BMO90]. It is a convenient representation for several program analysis and optimization techniques, including constant propagation with conditional branches[WZ91]; eq...

In this paper we describe a web search agent, called Global Search Agent (hereafter GSA for short). GSA integrates and enhances several search techniques in order to achieve significant improvements in the user-perceived quality of delivered information as compared to usual web search engines. GSA features intelligent merging of relevant documents from different search engines, anticipated sele...

The optimization of industrial processes is a critical task for leveraging profitability and sustainability. To ensure the selection optimum process parameter levels in any process, numerous metaheuristic algorithms have been proposed so far. However, many are either computationally too expensive or become trapped pit local optima. counter these challenges, this paper, hybrid called PSO-GSA emp...

Extraction of accurate Photo Voltaic (PV) model parameters is a challenging task for PV simulator developers. To mitigate this challenging task a novel approach using Gravitational Search Algorithm (GSA) for accurate extraction of PV model parameters is proposed in this paper. GSA is a population based heuristic optimization method which depends on the law of gravity and mass interactions. In t...

A new approach is presented applicable in framework of model calibration to observed data. The approach consists of a combination of the Generalized Likelihood Uncertainty Estimation technique (GLUE) and Global Sensitivity Analysis (GSA). The method is based on multiple model evaluations. The GSA is a quantitative, model independent approach and is based on estimating the fractional contributio...

In this paper, the gravitational search algorithm (GSA) is proposed as a method for controlling opening and closing of airplane wing tires. The GSA used to find optimum proportional-integral-derivative (PID) controller, which controls tires during take-off landing. addition, suggested an approach overcoming absence transfer function, usually required design PID. use expected improve system. Two...

the gravitational search algorithm (gsa) is a novel optimization methodbased on the law of gravity and mass interactions. it has good ability to search forthe global optimum, but its searching speed is really slow in the last iterations. sothe hybridization of particle swarm optimization (pso) and gsa can resolve theaforementioned problem. in this paper, a modified pso, which the movement ofpar...

We present a case of a ruptured giant serpentine aneurysm (GSA) of the superior cerebellar artery in a patient with a Chiari II malformation. The fusiform aneurysm was successfully treated with endovascular parent artery occlusion of the GSA by using detachable coils.