Search Results - (( pareto distribution a algorithm ) OR ( parameter optimization method algorithm ))
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…The first proposed approach is a multi-objective fuzzy linear programming optimization (MFLP) algorithm to solve the MOOPF problem. …”
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Slice sampler algorithm for generalized pareto distribution
Published 2018“…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…In addition, a novel external elitist repository is developed to conserve discovered non-dominated solutions and to produce true and well-distributed Pareto optimal fronts. …”
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Enhanced Micro Genetic Algorithm-Based Models For Multi-Objective Optimization
Published 2014“…Besides that, the quality of good MOP solutions needs to strike a balance between convergence and diversity against the true Pareto front (i.e. distribution of the ideal Pareto optimal solutions). …”
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Multi-objective spiral dynamic algorithms-based for a better accuracy and diversity
Published 2019“…The produced Pareto front curve is a measure of how good the solution produced by the algorithm is. …”
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Location and sizing of distributed generation photovoltaic (DGPV) via multi-objective pareto algorithm
Published 2023Conference Paper -
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Multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system
Published 2020“…The third scenario outperforms other scenarios in terms of coverage and convergence of the distribution of solution to the Pareto front. As a conclusion, The MS-MOSS algorithm is found to be very effective in sizing of SAPV system.…”
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NSGA-III algorithm for optimizing robot collaborative task allocation in the internet of things environment
Published 2024“…A genetic algorithm based on speed invariant and the elite algorithm is proposed to solve the multi-TSP assignment problem. …”
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Advanced Pareto front non-dominated sorting multi-objective particle swarm optimization for optimal placement and sizing of distributed generation
Published 2016“…This paper proposes an advanced Pareto-front non-dominated sorting multi-objective particle swarm optimization (Advanced-PFNDMOPSO) method for optimal configuration (placement and sizing) of distributed generation (DG) in the radial distribution system. …”
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Advanced Pareto front non-dominated sorting multi-objective particle swarm optimization for optimal placement and sizing of distributed generation
Published 2016“…This paper proposes an advanced Pareto-front non-dominated sorting multi-objective particle swarm optimization (Advanced-PFNDMOPSO) method for optimal configuration (placement and sizing) of distributed generation (DG) in the radial distribution system. …”
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Optimization of turning parameters using genetic algorithm method
Published 2008“…This study about development of optimization for turning parameters based on the Genetic Algorithm (GA). …”
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Undergraduates Project Papers -
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Parameters optimization of surface grinding process with particles swarm optimization, gravitational search, and sine cosine algorithms: a comparative analysis
Published 2018“…The efficiency of the three algorithms are evaluated and compared with previous results obtained by other optimization methods on similar studies. …”
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Optimization of PID parameters for hydraulic positioning system utilizing variable weight Grey-Taguchi and particle swarm optimization
Published 2014“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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Optimization of turning parameters using ant colony optimization
Published 2008“…The project objectives are to develop Ant Colony Optimization (ACO) algorithm for CNC turning process and to optimize turning parameters for minimized production cost per unit. …”
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Undergraduates Project Papers -
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Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail
Published 2014“…Trial and error often serves as the best method to determine the parameter. Therefore, a good optimization technique is required for identify the best parameter in minimizing the forecast errors. …”
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