Search Results - intelligence based ((three algorithm) OR (((bee algorithm) OR (bat algorithm))))
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HEURISTIC OPTIMIZATION OF BAT ALGORITHM FOR HETEROGENEOUS SWARMS USING PERCEPTION
Published 2023“…The Bat Algorithm is a population-based meta-heuristic algorithm for solving continuous optimization problems. …”
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Review of Multi-Objective Swarm Intelligence Optimization Algorithms
Published 2021“…The MOO approaches include scalarization, Pareto dominance, decomposition and indicator-based. In this paper, the status of MOO research and state-of-the-art MOSI algorithms namely, multi-objective particle swarm, artificial bee colony, firefly algorithm, bat algorithm, gravitational search algorithm, grey wolf optimizer, bacterial foraging and moth-flame optimization algorithms have been reviewed. …”
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Performance Analyses of Nature-inspired Algorithms on the Traveling Salesman’s Problems for Strategic Management
Published 2017“…After critical assessments of the performances of eleven algorithms consisting of two heuristics (Randomized Insertion Algorithm and the Honey Bee Mating Optimization for the Travelling Salesman’s Problem), two trajectory algorithms (Simulated Annealing and Evolutionary Simulated Annealing) and seven population-based optimization algorithms (Genetic Algorithm, Artificial Bee Colony, African Buffalo Optimization, Bat Algorithm, Particle Swarm Optimization, Ant Colony Optimization and Firefly Algorithm) in solving the 60 popular and complex benchmark symmetric Travelling Salesman’s optimization problems out of the total 118 as well as all the 18 asymmetric Travelling Salesman’s Problems test cases available in TSPLIB91. …”
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Solving the minimum dominating set problem of partitioned graphs using a hybrid bat algorithm
Published 2020“…This paper investigates the swarm intelligence behaviour represented by a population-based approach called the bat algorithm (BA) to find the smallest set of nodes that dominate the graph. …”
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Local search manoeuvres recruitment in the bees algorithm
Published 2011“…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. …”
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Performance Enhancement Of Artificial Bee Colony Optimization Algorithm
Published 2013“…Artificial Bee Colony (ABC) algorithm is a recently proposed bio-inspired optimization algorithm, simulating foraging phenomenon of honeybees. …”
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A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing
Published 2024“…Empirical studies of metaheuristic algorithms performance demonstrated that the hybrid metaheuristic algorithms-artificial neural network outperformed the gradient-based artificial neural network (RMSE=113.92 m3/s) for streamflow forecasting, notably with the firefly approach, with an average RMSE=96.06 m3/s. …”
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A Novel Hybrid Evolutionary Data-Intelligence Algorithm for Irrigation and Power Production Management: Application to Multi-Purpose Reservoir Systems
Published 2019“…The average monthly demand for irrigation is 142.14 (106 m3), and the amount of released water based on the new hybrid algorithm (NHA) is 141.25 (106 m3). …”
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Bats echolocation-inspired algorithms for global optimisation problems
Published 2016“…The aim of the research is to introduce novel form of swarm intelligence algorithms based on real echolocation behaviour of bats. …”
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Extended bat algorithm for PID controller tuning of wheeled mobile robot and swarm robotics target searching strategy
Published 2020“…Extended Bat Algorithm (EBA) has been chosen as swarm intelligent based method for this research study. …”
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Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network
Published 2020“…A total of 6 datasets were deployed to evaluate the effectiveness of the proposed algorithm. Results showed that EACS(TS) outperformed in terms of success rate, packet loss, latency, and energy efficiency when compared with single swarm intelligence routing algorithms which are Energy-Efficient Ant-Based Routing (EEABR), BeeSensor and Termite-hill. …”
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Artificial bee colony for inventory routing problem with backordering
Published 2014“…The bees are classified into three agents: the employed bee which carries the information about the food source, the onlooker bee watching the dance of the employed bees within the hive and making the decision to choose a food source based on the dances, and the scout bee, performing random search for the food sources. …”
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Quantum Inspired Computational Intelligence Techniques for Combined Economic Emission Dispatch Problem
Published 2017“…Quantum computing phenomenon is integrated with swarm intelligence-based PSO and bat algorithm (BA) to make these algorithms computationally more powerful and robust.…”
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Application of Bee Colony Optimization (BCO) in NP-Hard Problems
Published 2011“…Bee-Inspired algorithms were presumed to bring the new direction in the field of Swann Intelligence. …”
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A comprehensive overview of classical and modern route planning algorithms for self-driving mobile robots
Published 2022“…Classical or traditional methods, such as Roadmaps (Visibility Graph and Voronoi Diagram), Potential Fields, and Cell Decomposition, and modern methodologies such as heuristic-based (Dijkstra Method, A* Algorithms, and D* Algorithms), metaheuristics algorithms (such as PSO, Bat Algorithm, ACO, and Genetic Algorithm), and neural systems such as fuzzy neural networks or fuzzy logic (FL) and Artificial Neural Networks (ANN) are described in this report. …”
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Selective harmonic elimination in cascaded H-bridge multilevel inverter using hybrid APSO algorithm / Mudasir Ahmed
Published 2019“…The preliminary review of existing control techniques revealed that the Bio-inspired intelligent algorithms (BIAs) based selective harmonic elimination pulse width modulation (SHEPWM) are more proficient to eliminate the loworder harmonics. …”
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Thesis
