Search Results - (( using computing based algorithm ) OR ( basic optimization based algorithm ))
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1
Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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2
Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…In this study, a pattern based using Particle Swarm Optimization (PSO) is proposed named as Hexagon PSO (HPSO). …”
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3
An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…Several variants of PSO have been proposed for solving discrete optimization problems like TSP. Among them, the basic algorithm is the Swap Sequence based PSO (SSPSO), however, it does not perform well in providing high quality solutions. …”
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Model of Improved a Kernel Fast Learning Network Based on Intrusion Detection System
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…Using a proper test-bed, after 10000 run times, we compared our newly proposed algorithm with the basic algorithm in terms of reliability and availability. …”
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6
Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…Basically, the proposed of FUHS16, UHDS16 and UHDS8 algorithm produces the best motion vector estimation finding based on the block-based matching criteria. …”
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7
Mobile First-Person Shooter (FPS) Game Using Basic Theta* Algorithm / Muhammad Syurahbil Abd Rohaman
Published 2020“…Basic Theta* is implemented in the game using grid-based map representation. …”
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8
Stochastic process and tutorial of the African bufalo optimization
Published 2022“…This paper presents the data description of the African buffalo optimization algorithm (ABO). ABO is a recently-designed optimization algorithm that is inspired by the migrant behaviour of African buffalos in the vast African landscape. …”
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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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10
A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…An intelligence strategy called quasi-oppositional based learning is incorporated into the proposed algorithm to enhance its convergence property, exploration capability, and solution optimality. …”
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Cyclic Path Planning Of Hyper-Redundant Manipulator Using Whale Optimization Algorithm
Published 2023Article -
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Web based applications for energy management system incorporated network reconfiguration using genetic algorithm / Wan Adnan Wan
Published 2006“…The development on Web Application system uses An ActiveX technology approach. The Genetic Algorithm Based Network Reconfiguration Technique for loss minimization in the UiTM Distribution System is also proposed based on general combinatorial optimization algorithm. …”
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13
Cyclic Path Planning Of Hyper-Redundant Manipulator Using Whale Optimization Algorithm
Published 2021“…To solve the redundancy resolution, meta-heuristic optimizations, namely Genetic Algorithm (GA) and Whale Optimization Algorithm (WOA), are applied to search optimal trajectories inside local orientation angle boundaries. …”
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Scheduling scientific workflow using multiobjective algorithm with fuzzy resource utilization in multi-cloud environment
Published 2020“…In this respect, this paper proposes a new multi-objective scheduling algorithm with Fuzzy resource utilization (FR-MOS) for scheduling scientific workflow based on particle swarm optimization (PSO) method. …”
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Development of cell formation algorithm and model for cellular manufacturing system
Published 2011“…Therefore, for this proposes good benchmarked algorithm, bacteria foraging algorithm is selected and developed to solve multiobjective cell formation model and traced constraints satisfaction handling to produce feasible optimal solution. …”
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16
Integration of enchanced jump point search (JPS) algorithm with modified bresenham technique for path planning in virtual grid-based environment
Published 2018“…We demonstrate our framework; the integration of enhanced Jump Point Search algorithm with modified Bresenham for heuristic computation in virtual grid-based environment. …”
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17
Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
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18
Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling
Published 2022“…This research first proposes an improved continuous MOPSO to address the rapid clustering problem that exists in the basic PSO algorithm using three improvement strategies: re-initialization of particles, systematic switch of best solutions and mutation on global best selection. …”
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Optimization and prediction of battery electric vehicle driving range using adaptive fuzzy technique
Published 2022“…The study also developed an algorithm for predictive EMS using fuzzy model predictive control technique based on regression algorithm. …”
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20
Metaheuristic-Based Neural Network Training And Feature Selector For Intrusion Detection
Published 2019“…Those problems lend themselves to the realm of optimization. Considering the wide success of swarm intelligence methods in optimization problems, the main objective of this thesis is to contribute to the improvement of intrusion detection technology through the application of swarm-based optimization techniques to the basic problems of selecting optimal packet features, and optimal training of neural networks on classifying those features into normal and attack instances. …”
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