Search Results - (( var optimization method algorithm ) OR ( data optimization based algorithm ))
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Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk
Published 2019“…In addition, compared with the VaR-FMOPSM model, our sensitivity-based improved model with the IPSO algorithm also performs better than Genetic Algorithm and Simulate Anneal Algorithm (SA), it provides the same performance on this point. …”
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An Empirical Study on the Construction of A Non-Convex Risk Parity Portfolio using a Genetic Algorithm
Published 2025“…While conventional numerical methods can be applied, they often struggle with inefficiency and fail to deliver optimal results. …”
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Determining optimal location of static VAR compensator by means of genetic algorithm
Published 2011“…The purpose of this paper is to study a practical and accurate heuristic method known as genetic algorithm (GA) which is used to find the optimal location of Static Var Compensator (SVC) and its appropriate size and setting. …”
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Optimal design of three-phase static var compensation system
Published 2023“…This manuscript is aimed to emphasize the application of synchronous detection method (SDM) to develop and design three-phase static var compensation (SVC) systems with minimal complexity. …”
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Genetic algorithm based method for optimal location placement of flexible ac transmission system devices for voltage profile improvement
Published 2011“…This thesis present a genetic algorithm based method for placement of FACTS devices for voltage profile improvement. …”
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Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method
Published 2023“…Copper deposits; Deposits; Geology; Learning algorithms; Mineralogy; Static Var compensators; Support vector machines; Three dimensional computer graphics; Alteration zones; Grid search; Grid-search method; Mineralization zone; Model Selection; Particle swarm optimization algorithm; Penalty parameters; Performance; Support vector classifiers; Support vectors machine; Particle swarm optimization (PSO); accuracy assessment; algorithm; classification; computer simulation; copper; geological survey; mineral alteration; mineralization; numerical model; ore deposit; parameterization; performance assessment; porphyry; resource assessment; support vector machine; three-dimensional modeling; Iran…”
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Loss minimization with SVC installation using the Firefly Algorithm method / Syazana Abdul Halim
Published 2012“…This algorithm method is idealized by some of the characteristics of fireflies. …”
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On the Application of heuristic Method and Saddle Node Bifurcation for Optimal Placement of FACTS Devices in Power System
Published 2011“…This study focuses on an optimal placement of five major types of FACTS devices, namely, Static Var Compensator (SVC), Thyristor Controlled Series Compensator (TCSC), Static Synchronous Compensator (STATCOM), Static Synchronous Series Compensator (SSSC) and Unified Power Flow Controller (UPFC) in power system network using a well-known and applicable heuristic method known as genetic algorithm to seek the optimum location and setting of these controllers in the system. …”
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Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network
Published 2020“…Based on the performance evaluation, GACS outperforms both Genetic Algorithm (GA)-based cluster optimization algorithm and Cuckoo Search (CS)-based multi-hop optimization algorithm.…”
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An online density-based clustering algorithm for data stream based on local optimal radius and cluster pruning
Published 2019“…BOCEDS clusters the data stream in a single stage. The algorithm summarizes the data from data stream in micro-clusters. …”
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Clustering chemical data set using particle swarm optimization based algorithm
Published 2008“…In this study, Particle Swarm Optimization (PSO) based clustering algorithm is exploited to optimize the results of other clustering algorithm such as K-means. …”
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Data-Driven control based on marine predators algorithm for optimal tuning of the wind plant
Published 2022“…Comparative results alongside other existing metaheuristic-based algorithms further confirmed excellence of the proposed method through its superior performance against the slime mould algorithm (SMA), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), grey wolf optimizer (GWO), and safe experimentation dynamics (SED) algorithm.…”
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Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm
Published 2024“…This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern
Published 2012“…GA is a widely used optimization algorithm based on the concept of survival of the fittest. …”
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A Conceptual Framework of Bacterial Foraging Optimization Algorithm for Data Classification
Published 2016“…Most previous works on Bacterial Foraging Optimization Algorithm (BFOA) for data classification were integrated BFOA as a feature selection algorithm and parameters optimizer for other classifiers. …”
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Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…In addition, ISSA was compared with four well-known optimization algorithms such as Genetic Algorithm, Particle Swarm Optimization, Grasshopper Optimization Algorithm, and Ant Lion Optimizer. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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LS-SVM Hyper-parameters Optimization Based on GWO Algorithm for Time Series Forecasting
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