Search Results - (( using optimization method algorithm ) OR ( variable integration _ algorithm ))
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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 PID Parameters Utilizing Variable Weight Grey-Taguchi Method and Particle Swarm Optimization
Published 2017“…Particle swarm optimization algorithm (PSO) is one of the artificial intelligence methods. …”
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Optimizing Decentralized Exam Timetabling with a Discrete Whale Optimization Algorithm
Published 2025“…In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…The paper conducts design optimization of CAMPRO 1.6L (S4PH) engine valve timing at various engine speeds using multi-objective genetic algorithm (MOGA) for the future variable valve timing (VVT) system research and development. …”
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Proceeding Paper -
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Optimizing decentralized exam timetabling with a discrete whale optimization algorithm
Published 2025“…—In recent years, there has been increasing interest in intelligent optimization algorithms, such as the Whale Optimization Algorithm (WOA). …”
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Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi
Published 2018“…A Modified Particle Swarm Optimization (MPSO) algorithm, a Genetic Algorithm (GA), a modified fruit fly optimization algorithm (MFOA) and a simulated annealing (SA) algorithm were used to find the optimal solution. …”
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Solving the optimal power flow problems using the superiority of feasible solutions-moth flame optimizer
Published 2024“…The main goal of this study is to use a cuttingedge version of recent metaheuristic algorithm, namely Moth-Flame Optimizer (MFO) algorithm for solving the mentioned OPF problems. …”
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Harmony search-based robust optimal controller with prior defined structure
Published 2013“…In this approach, a combination of interacting two levels HS optimization algorithm is presented. In the first level, a new method for analytical formulation of integral square error cost function based on controller variables is elaborated for performance evaluation purposes by the proposed optimization algorithm. …”
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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2025“…The proposed method is a version of the democratic political optimization algorithm in which the search capability of this method to cover the borders of the Pareto frontier is enhanced. …”
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A high-performance democratic political algorithm for solving multi-objective optimal power flow problem
Published 2024“…The proposed method is a version of the democratic political optimization algorithm in which the search capability of this method to cover the borders of the Pareto frontier is enhanced. …”
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Optimization of Digital Electronic Circuit Structure Design Using Genetic Algorithm
Published 2008“…Karnaugh map can provide the simple minimization process for Boolean expression, but it encounters difficulties when the variable is more than four In this research, Genetic Algorithm (GA) technique is used as a tool to search for the optimal solution for the digital circuit structure. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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Optimizing n-1 contingency rankings using a nature-inspired modified sine cosine algorithm
Published 2025“…The MSCA method is validated using the IEEE 30-bus test case, focusing on optimal parameter tuning for population size, iterations, and key variables. …”
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Neural network modeling and optimization for spray-drying coconut milk using genetic algorithm and particle swarm optimization
Published 2022“…The ANN model is further improved using GA and PSO. Each algorithm has its own parameters and is further optimized using RSM. …”
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Enhanced Taguchi�s T-method using angle modulated Bat algorithm for prediction
Published 2023“…In response to this issue, this paper proposed an angle modulated Bat algorithm to be integrated with the T-method in optimizing the prediction model. …”
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Modeling time series data using Genetic Algorithm based on Backpropagation Neural network
Published 2018“…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm
Published 2025“…The orthogonal learning mechanism improves the performance of the original GOOSE algorithm. This FC model uses the root mean squared error as the objective function for optimizing the unknown parameters. …”
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