Search Results - (( developing indicator swarm algorithm ) OR ( java implication based algorithm ))
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Extended bat algorithm for PID controller tuning of wheeled mobile robot and swarm robotics target searching strategy
Published 2020“…Hence, EBA which is the proposed method is able to develop target searching algorithm for swarm robotic system and tuning PD controller gains for wheeled mobile robot.…”
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Pumped-storage scheduling using particle swarm optimization / Amirul Asraf Razali
Published 2012“…This is because particle swarm optimization (PSO) algorithm is developed to give the economical cost for the hydrothermal generation with pumped-storage unit to fulfill the constraint of thermal and hydro unit. …”
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Review of Multi-Objective Swarm Intelligence Optimization Algorithms
Published 2021“…These reviewed algorithms were mainly developed to solve continuous MOPs. …”
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Intergrated multi-objective optimisation of assembly sequence planning and assembly line balancing using particle swarm optimisation
Published 2013“…In order to supply sufficient test problems that cover a range of problem difficulties, a tuneable test problem generator is developed. Statistical tests on the algorithms' performance indicates that the proposed MODPSO algorithm presents significant improvement in terms of larger nondominated solution numbers in Pare't o optimal, compared to comparable algorithms including GA based algorithms in both single-model and mixedmodel ASP and ALB problems. …”
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Estimation of small-scale kinetic parameters of escherichia coli (E. coli) model by enhanced segment particle swarm optimization algorithm ese-pso
Published 2023“…In this regard, the result of the ESe-PSO algorithm achieved superior accuracy compared with the Segment Particle Swarm Optimization (Se-PSO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Differential Evolution (DE) algorithms. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Predictive modeling of condominium prices using a Particle Swarm Optimization-Random Forest approach / Che Wan Sufia Che Wan Samsudin
Published 2025“…The development of a predictive model for condominium prices using the Particle Swarm Optimization-Random Forest approach is the key focus of this research project. …”
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State of charge estimation of a lithium-ion battery for electric vehicle based on particle swarm optimization
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Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing
Published 2011“…Many AI-based strategies have been developed, such as Ant Colony, Simulated Annealing, Genetic Algorithm, and Tabu Search. …”
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Modelling and Optimization of Asymmetric Vehicle Routing Problem Using Particle Swarm Optimization Algorithm
Published 2021“…The optimization results indicated that this algorithm able to offer good solutions with the best answer for the practical problem. …”
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Rock brittleness prediction through two optimization algorithms namely particle swarm optimization and imperialism competitive algorithm
Published 2018“…The main goal of this research work is to propose the novel practical models to predict the BI through particle swarm optimization (PSO) and imperialism competitive algorithm (ICA). …”
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Optimal Power Flow of power systems using Harris Hawks Optimization and Salp Swarm Algorithm
Published 2021“…This thesis has proposed recently developed Harris Hawks Optimization (HHO) and Salp Swarm Algorithm (SSA) to solve single- and multi-objective OPF problems considering fuel cost, power loss and environment emission. …”
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Adaptive mechanism for enhanced performance of shark smell optimization / Nur Atharah Kamarzaman, Shahril Irwan Sulaiman and Intan Rahayu Ibrahim
Published 2021“…Numerical results indicate that the ASSO algorithm strategy outperforms the basic SSO algorithm, Genertic Algorithm (GA), Particle Swarm Intelligence (PSO), Firefly Algorithm (FA), Artificial Bee Colony (ABC) and Teaching Learning Based Optimization (TBLO) in term of reaching for global solution.…”
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Multi-Agent Reinforcement Learning For Swarm Robots Formation
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Irrigation management based on reservoir operation with an improved weed algorithm
Published 2023Article -
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Optimum Power Production of Small Hydropower Plant (SHP) Using Firefly Algorithm (FA) in Himreen Lake Dam (HLD), Eastern Iraq
Published 2017“…The results obtained from these two methods, namely Firefly Algorithm (FA) and Particle Swarm Optimization, (PSO) are compared. …”
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A sequential handwriting recognition model based on a dynamically configurable convolution recurrent neural network and hybrid salp swarm algorithm
Published 2024“…The built DCCRNN is based on the Salp Swarm optimization Algorithm (SSA), a processor that given a particular dataset will find the best CRNN’s structure and hyperparameters. …”
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