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Enhanced artificial bee colony-least squares support vector machines algorithm for time series prediction
Published 2014“…This study proposed a hybrid algorithm, based on Artificial Bee Colony (ABC) and LSSVM, that consists of three algorithms; ABC-LSSVM, lvABC-LSSVM and cmABC-LSSVM. …”
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Lévy mutation in artificial bee colony algorithm for gasoline price prediction
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Deriving Optimal Operation Rule for Reservoir System Using Enhanced Optimization Algorithms
Published 2025“…This study delves into the exploration of different algorithms, including Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Firefly Algorithm (FA), Invasive Weed Optimization (IWO), Teaching Learning-Based Optimization (TLBO), and Harmony Search (HS). …”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…The Traveling Salesman Problem (TSP) is a combinatorial optimization problem that is useful in a number of applications. Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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A novel swarm-based optimisation algorithm inspired by artificial neural glial network for autonomous robots
Published 2019“…Artificial neuro-glial networks is proposed to be combined in the swarm-based communication algorithm to provide a human-like model for the robot's communication and optimization.…”
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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter
Published 2015“…This paper proposes three steps of improvements for identification of the nonlinear dynamic system, which exploits the concept of a state-space based time domain Volterra model. The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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Application of intelligent optimization techniques and investigating the effect of reservoir size in calibrating the reservoir operating policy
Published 2023“…Particle swarm optimization, genetic algorithm and neural network-based stochastic dynamic programming are used to compare the model performances. …”
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RLMD-PA: A Reinforcement Learning-Based Myocarditis Diagnosis Combined with a Population-Based Algorithm for Pretraining Weights
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm
Published 2025“…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar
Published 2019“…In this study, the performance of these three algorithms in obtaining the optimal blade design based on the �436�45D are investigated and compared. …”
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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter
Published 2015“…This paper proposes three steps of improvements for identification of the nonlinear dynamic system, which exploits the concept of a state-space based time domain Volterra model. The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
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A study on solution of matrix riccati differential equations using ant colony programming and simulink / Mohd Zahurin Mohamed Kamali
Published 2015“…Illustrative examples are shown to prove the effectiveness of the proposed algorithm. Moreover, the proposed method have been well applied to biological and engineering problems such as linear and nonlinear singular systems, human immunodeficiency virus (HIV) models, microbial growth model and ethanol fermentation process. …”
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