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1
The design and applications of the african buffalo algorithm for general optimization problems
Published 2017“…Some of the successfully designed stochastic algorithms include Simulated Annealing, Genetic Algorithm, Ant Colony Optimization, Particle Swarm Optimization, Bee Colony Optimization, Artificial Bee Colony Optimization, Firefly Optimization etc. …”
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Improved cuckoo search based neural network learning algorithms for data classification
Published 2014“…This research proposed an improved CS called hybrid Accelerated Cuckoo Particle Swarm Optimization algorithm (HACPSO) with Accelerated particle Swarm Optimization (APSO) algorithm. …”
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BAT-BP: A new BAT based back-propagation algorithm for efficient data classification
Published 2016“…The performance of the proposed Bat-BP algorithm is then compared with Artificial Bee Colony using BPNN (ABC-BP), Artificial Bee Colony using Levenberg-Marquardt (ABC-LM) and BPNN algorithm. …”
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Optimal distributed generation and load shedding scheme using artificial bee colony- hill climbing algorithm considering voltage stability and losses indices
Published 2021“…Another part of this work focuses on enhancing the stability of the power system using distributed generator (DG). The proposed solution is based on the optimization method developed from a combination of the Artificial Bee Colony and Hill Climbing algorithms (ABC-HC) to give the optimal placement and sizing of DG units to be deployed in the system. …”
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5
Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification
Published 2015“…As a solution, nature inspired metaheuristic algorithms provide derivative-free solution to optimize complex problems. …”
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Selective harmonic elimination in cascaded H-bridge multilevel inverter using hybrid APSO algorithm / Mudasir Ahmed
Published 2019“…The simulation results show that the proposed algorithm calculates highly precise firing angles in less number of iterations with the very high capability of tackling the local optima then Bee Algorithm (BA), differential evolution (DE), GA and PSO. …”
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Optimization of fed-batch fermentation processes using the Backtracking Search Algorithm
Published 2018“…However, the complexity of these processes requires an expert system that involves swarm intelligence-based metaheuristics such as Artificial Algae Algorithm (AAA), Artificial Bee Colony (ABC), Covariance Matrix Adaptation Evolution Strategy (CMAES) and Differential Evolution (DE) for simulation and optimization of the feeding trajectories. …”
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Solving large-scale problems using multi-swarm particle swarm approach
Published 2018“…The results showed that the proposed PSO algorithm outperformed the other algorithms in terms of the optimal solutions and the convergence.…”
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A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites
Published 2019“…Many test data generation strategies based on meta-heuristic algorithms such as Simulated Annealing (SA), Tabu Search (TS), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search (HS), Cuckoo Search (CS), Bat Algorithm (BA) and Bees Algorithm have been developed in recent years. …”
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An efficient multi join query optimization for relational database management system using swarm intelligence approaches
Published 2016“…The TP ABC algorithm can be utilized to solve MJQO problems via simulation and increasing exploration and exploitation whilst balancing them for optimal results from giving queries. …”
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An efficient multi join query optimization for relational database management system using swarm intelligence approaches
Published 2016“…The TP ABC algorithm can be utilized to solve MJQO problems via simulation and increasing exploration and exploitation whilst balancing them for optimal results from giving queries. …”
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Optimization of neural network using cuckoo search for the classification of diabetes
Published 2015“…The propose diabetes classifier performance was compared to the classifiers built based on artificial bee colony and genetic algorithm. Simulation results show that the proposed approach converges faster to the optimum solution than the comparative classifiers. …”
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Restoration planning strategy of transmission system based on optimal energizing time of sectionalizing islands / Dian Najihah Abu Talib
Published 2019“…There are two discrete optimization techniques used in this work, which are the Artificial Bee Colony algorithm and Evolutionary Programming. …”
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A stable energy balancing based clustering routing protocol for IoUT using meta-heuristic technique
Published 2024“…The proposed method enable to optimization the IoUT energy efficiency by balancing strategy that uses the Q-learning algorithm to ensure more balanced distribution of tasks across UNs and CHs. …”
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Proceeding Paper -
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Application of the bees algorithm for constrained mechanical design optimisation problem
Published 2019“…To find the optimal solution for the multiple disc clutch design, the Bees Algorithm will be used and expected to give better result compared to other optimisation algorithms that already have been used.…”
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Artificial bee colony algorithm with proposed discrete nearest neighborhood algorithm for discrete optimization problems
Published 2021“…In addition, 2 types of scout bee were used for to intensify the probability property of the algorithm. …”
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Solving the travelling salesman problem by using artificial bee colony algorithm / Noor Ainul Hayati Mohd Naziri
Published 2021“…ABC algorithm has three types of bees that are used by bees, onlooker bees, and scout bees. …”
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Student Project -
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Solving the travelling salesman problem by using artificial bee colony algorithm / Siti Hafawati Jamaluddin ... [et al.]
Published 2022“…ABC algorithm has three types of bees that are used by bees, onlooker bees, and scout bees. …”
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Optimal design of step – cone pulley problem using the bees algorithm
Published 2021“…The Bees Algorithm is used in this study to find the optimum solution for stepped-cone pulley design and found better results compared to other optimization algorithms.…”
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