Search Results - (( colony optimization bees algorithm ) OR ( parameter optimization method algorithm ))

Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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Comparative analysis of spiral dynamic algorithm and artificial bee colony optimization for position control of flexible link manipulators by Nor Maniha, Abdul Ghani, Nizaruddin, M. Nasir, Azrul Azim, Abdullah Hashim

“…This study aims to evaluate the effectiveness of two optimization algorithms, artificial bee colony (ABC) and spiral dynamic algorithm (SDA), in controlling the position of a flexible-link manipulator. …”
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A novel explanatory hybrid artificial bee colony algorithm for numerical function optimization by Jarrah, Muath Ibrahim, Mohamad Jaya, Abdul Syukor, Mohd Abid, Mohd Asyadi Azam, Alqattan, Zakaria N., Azam, Mohd Asyadi, Abdullah, Rosni, Jarrah, Hazim, Abu‑Khadrah, Ahmed Ismail

“…However, it is impossible to fnd an optimization algorithm that can obtain the global optimum for every optimization problem. …”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

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LSSVM parameters tuning with enhanced artificial bee colony by Mustaffa, Zuriani, Yusof, Yuhanis

“…To guarantee its convincing performance, it is crucial to select an appropriate technique in order to obtain the optimized hyper-parameters of LSSVM algorithm.In this paper, an Enhanced Artificial Bee Colony (eABC) is used to obtain the ideal value of LSSVM’s hyper parameters, which are regularization parameter, γ and kernel parameter, σ2.Later, LSSVM is used as the prediction model. …”
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Artificial Bee Colony-based satellite image contrast and brightness enhancement technique using DWT-SVD by Bhandari, A.K., Soni, V., Kumar, A., Singh, G.K.

“…The proposed technique is based on the Artificial Bee Colony (ABC) algorithm using Discrete Wavelet Transform and Singular Value Decomposition (DWT-SVD). …”
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A review of training methods of ANFIS for applications in business and economic by Mohd Salleh, Mohd Najib, Hussain, Kashif

“…Other than that, Genetic Algorithm (GA), Firefly Algorithm (FA), Ant Bee Colony (ABC) optimization methods have been employed for effective training of ANFIS networks when solving various problems in the field of business and finance.…”
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A review of training methods of ANFIS for applications in business and economics by Mohd Salleh, Mohd Najib, Hussain, Kashif

“…Other than that, Genetic Algorithm (GA), Firefly Algorithm (FA), Ant Bee Colony (ABC) optimization methods have been employed for effective training of ANFIS networks when solving various problems in the field of business and finance.…”
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Optimization of economic lot scheduling problem with backordering and shelf-life considerations using calibrated metaheuristic algorithms by Mohammadi, M., Musa, S.N., Bahreininejad, A.

“…Efficient search procedures are presented to obtain the optimum solutions by employing four well-known metaheuristic algorithms, namely genetic algorithm (GA), particle swarm optimization (PSO), simulated annealing (SA), and artificial bee colony (ABC). …”
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HABCSm: A Hamming Based t -way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A., Capretz, L.F., Imam, A.A., Balogun, A.O.

“…Consequently, a new meta-heuristic based t -way strategy called Hybrid Artificial Bee Colony (HABCSm) strategy, based on merging the advantages of the Artificial Bee Colony (ABC) algorithm with the advantages of a Particle Swarm Optimization (PSO) algorithm is proposed in this paper. …”
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HABCSm: A Hamming Based t -way Strategy based on Hybrid Artificial Bee Colony for Variable Strength Test Sets Generation by Alazzawi, A.K., Rais, H.M., Basri, S., Alsariera, Y.A., Capretz, L.F., Imam, A.A., Balogun, A.O.

“…Consequently, a new meta-heuristic based t -way strategy called Hybrid Artificial Bee Colony (HABCSm) strategy, based on merging the advantages of the Artificial Bee Colony (ABC) algorithm with the advantages of a Particle Swarm Optimization (PSO) algorithm is proposed in this paper. …”
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Hydroclimatic data prediction using a new ensemble group method of data handling coupled with artificial bee colony algorithm by Basri Badyalina, Nurkhairany Amyra Mokhtar, Nur Amalina Mat Jan, Muhammad Fadhil Marsani, Mohamad Faizal Ramli, Muhammad Majid, Fatin Farazh Ya'acob

“…It is rare to find a hydrological application using the group method of data handling (GMDH) model, artificial bee colony (ABC) algorithm, and ensemble technique, precisely predicting ungauged sites. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…In this paper, heuristic optimization approaches such as genetic algorithm and artificial bee colony are used to optimize the parameters of the antecedent part of interval type-2 fuzzy logic systems. …”
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Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

“…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
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Power system network splitting and load frequency control optimization using ABC based algorithms / Kanendra Naidu a/l Vijyakumar by Vijyakumar, Kanendra Naidu

“…This research presents a modified optimization program for the system splitting problem in large scale power system based on Artificial Bee Colony algorithm and graph theory. …”
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A new teaching learning artificial bee colony based maximum power point tracking approach for assessing various parameters of photovoltaic system under different atmospheric condit... by Dokala Janandra, Krishna Kishore

“…In addition, to enhance the performance teaching learning-based artificial bee colony (TLABC) method has been used at distinct weather conditions. …”
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Artificial Bee Colony for Minimizing the Energy Consumption in Mobile Ad Hoc Network by Tareq, M., Abed, S.A., Sundararajan, E.A.

“…The aim of this paper is to find the best possible route from the source to the destination based on a method inspired by the searching behaviour of bee colonies, i.e. artificial bee colony (ABC) algorithm. …”
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Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter by ., Edwar Yazid, Mohd Shahir Liew, Setyamartana Parman, Velluruzhati

“…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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Exploration and Exploitation Mechanism in Pairwise Test Case Generation: A Systematic Literature Review by Yahaya, Muhammad Sabo, Hashim, Ahmad Sobri B., Oluwagbemiga Balogun, Abdullateef, Aminu Muazu, Aminu, Sabo Usman, Fatima, Adamu Aliyu, Dahiru, Uwaisu Muhammad, Abdullahi

“…Covering research from 2014 to 2024, the review evaluates hybrid and metaheuristic strategies, including Pairwise Migrating Birds Optimization-Based Strategies (PMBOS), Pairwise Gravitational Search Algorithm Strategy (PGSAS), Pairwise hybrid Artificial Bee Colony (PhABC), Genetic and Particle Swarm Optimization (GAPSO) algorithm, Hybrid Optimization Algorithm (HOA), and Parameter Free Choice Function based Hyper-Heuristic (PCFHH), among others. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…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. …”