Search Results - (( using (evolutionary OR evolution) based algorithm ) OR ( wolf optimization based algorithm ))
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1
Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…The proposed method is tested on 10 multi-objective benchmark problems of CEC 2009 and compared with four metaheuristics: Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D), Multi-Objective Differential Evolution (MODE) and MOPSO. …”
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Opposition Based Competitive Grey Wolf Optimizer For EMG Feature Selection
Published 2020“…Moreover, another new variant of CGWO, namely opposition based competitive grey wolf optimizer (OBCGWO), is proposed to enhance the performance of CGWO in feature selection. …”
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Investigation and validation of an eleven level symmetric modular multilevel inverter using grey wolf optimization and differential evolution control algorithm for solar PV applica...
Published 2021“…Purpose: This paper aims to examine the design and control of a symmetric multilevel inverter (MLI) using grey wolf optimization and differential evolution algorithms. …”
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A multi-objective particle swarm optimization algorithm based on dynamic boundary search for constrained optimization
Published 2018“…M-MOPSO is compared with four other algorithms namely, MOPSO, Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm based on Decompositions (MOEA/D) and Multi-Objective Differential Evolution (MODE). …”
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Time series forecasting of energy commodity using grey wolf optimizer
Published 2015“…The ability to model and perform decision making is an essential feature of many real-world applications including the forecasting of commodity prices.In this study, a forecasting model based on a relatively new Swarm Intelligence (SI) behaviour, namely Grey Wolf Optimizer (GWO), is developed for short term time series forecasting.The model is built upon data obtained from the West Texas Intermediate (WTI) crude oil and gasoline price.Performance of the GWO model is compared against two other models which are developed based on Evolutionary Computation (EC) algorithms, namely the Artificial Bee Colony (ABC) and Differential Evolution (DE).Results showed that the GWO model outperformed DE in both crude oil and gasoline price forecasting. …”
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Conference or Workshop Item -
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Time Series Forecasting of Energy Commodity using Grey Wolf Optimizer
Published 2015“…Performance of the GWO model is compared against two other models which are developed based on Evolutionary Computation (EC) algorithms, namely the Artificial Bee Colony (ABC) and Differential Evolution (DE). …”
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Conference or Workshop Item -
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An ensemble of neural network and modified grey wolf optimizer for stock prediction
Published 2019“…Widespread models like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Evolutionary Strategy (ES) and Population-Based Incremental Learning (PBIL) dealing with the specified problems are also explored and compared. …”
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Short term forecasting based on hybrid least squares support vector machines
Published 2018“…In this study, hybrid Least Squares Support Vector Machines (LSSVM) with four meta-heuristic algorithms viz. Grey Wolf Optimizer (GWO-LSSVM), Cuckoo Search (CS-LSSVM), Genetic Algorithm (GA-LSSVM) and Differential Evolution (DE-LSSVM) are presented for a week ahead water level forecasting. …”
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Hybrid harmony search algorithm for continuous optimization problems
Published 2020“…Addressing these aforementioned issues, this thesis proposes to augment HS with adaptive tuning using Grey Wolf Optimizer (GWO). Meanwhile, to enhance its exploitation, this thesis also proposes to adopt a new variant of the opposition-based learning technique (OBL). …”
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Solving economic load dispatch using immune evolutionary programming (IEP) optimization technique
Published 2024text::Final Year Project -
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Optimization ofhybrid flow shop scheduling in a machine shop: Achieving energy efficiency and minimizing machine idleness with multi-objective Tiki Taka optimization
Published 2025“…The EE-HFS was optimized using Multi-Objective Tiki Taka Optimization (MOTTA).The study considered machine idle time as a key factor influencing energy efficiency, incorporating it into the scheduling evaluation.The optimization result was compared to established algorithms, such as the Non-dominated Sorting Genetic Algorithm-II, the Multi-ObjectiveEvolutionary Algorithm Based on Decomposition, the Multi-ObjectiveParticle Swarm Optimization,and the recent algorithm,the Multi-ObjectiveGrey Wolf Optimizer. …”
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Optimization of hybrid flow shop scheduling in a machine shop: Achieving energy efficiency and minimizing machine idleness with multi-objective Tiki Taka optimization
Published 2025“…The study considered machine idle time as a key factor influencing energy efficiency, incorporating it into the scheduling evaluation. The optimization result was compared to established algorithms, such as the Non-dominated Sorting Genetic Algorithm-II, the Multi Objectives Evolutionary Algorithm Based on Decomposition, the Multi Objectives Particle Swarm Optimization, and the recent algorithm Multi Objectives Grey Wolf Optimizer. …”
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Energy management system for optimal operation of microgrid consisting of PV, fuel cell and battery / Shivashankar Sukumar
Published 2017“…The BESS sizing problem is solved using grey wolf optimizer (GWO), particle swarm optimization (PSO), artificial bee colony (ABC), gravitational search algorithm (GSA), and genetic algorithm (GA). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Stock market turning points rule-based prediction / Lersak Photong … [et al.]
Published 2021“…Finally, rule-based optimisation techniques such as Particle Swarm Optimization (PSO), Differential Evolution (DE) and Grey Wolf Optimizer (GWO) were used to minimise the amount of time employed in the stock market turning points prediction. …”
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Book Section -
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Robust multi-user detection based on hybrid grey wolf optimization
Published 2020“…The simulation results show that the iteration times of the multi-user detector based on the proposed algorithm is less than that of genetic algorithm, differential evolution algorithm and Grey wolf optimization algorithm, and has the lower BER.…”
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Book Chapter -
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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