Search Results - (( parallel optimization bat algorithm ) OR ( global contributing function algorithm ))
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A hybrid bat–swarm algorithm for optimizing dam and reservoir operation
Published 2019“…This study proposes a new hybrid optimization algorithm based on a bat algorithm (BA) and particle swarm optimization algorithm (PSOA) called the hybrid bat–swarm algorithm (HB-SA). …”
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…After that, SKF is tested to find the most accurate image template matching and compared with Particle Swarm Optimization (PSO) and Bat Algorithm with Mutation (BAM). …”
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Thesis -
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PSO-LFDE Algorithm on Constrained Real-Parameter Optimisation Test Functions
Published 2023“…The proposed algorithm will hold a better exploration–exploitation equilibrium if the contributions of convergence and diversity and global and individual bests in attracting particles are maintained in balance. …”
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Chaos search in fourire amplitude sensitivity test
Published 2012“…Work in Artificial Intelligence (AI) often involves search algorithms. In many complicated problems, however, local search algorithms may fail to converge into global optimization and global search procedures are needed. …”
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Chaos Search in Fourier Amplitude Sensitivity Test
Published 2012“…Work in Artificial Intelligence (AI) often involves search algorithms. In many complicated problems, however, local search algorithms may fail to converge into global optimization and global search procedures are needed. …”
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An empirical study of density and distribution functions for ant swarm optimized rough reducts
Published 2011“…Ant colony approach in Ant Swarm algorithm generates local solutions which satisfy the Gaussian distribution for global optimization using PSO algorithm. …”
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Book Chapter -
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Enhancing Harmony Search Parameters Based On Step And Linear Function For Bus Driver Scheduling And Rostering Problems
Published 2018“…Therefore,it is of great interest that we find adjustments for these parameters in this research.There are two contributions to this research.The first one is having HMCR parameter using step function and the linear increase function while the second is applying the fret spacing concept on guitars that is associated with mathematical formulae is also applied in the BW parameter.There are three proposed models on the alteration of HMCR parameters based on the use of the fundamental step function;namely,the constant interval of step function, and its dynamic increase and decrease interval functions.The experimental results revealed that our proposed approach is superior to other state of the art harmony searches either in specific or generic cases. …”
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Thesis -
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Modified Parameters of Harmony Search Algorithm for Better Searching
Published 2017“…The contributions to this research are the HMCR parameter using step function while the fret spacing concept on guitars that is associated with mathematical formulae is also applied in the BW parameter. …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…DE has effectively solved various global optimization problems, including benchmark functions. …”
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Thesis -
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New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…Thirdly, the thesis validates the algorithm's performance on standard constrained single objective and multi objective benchmark test functions. …”
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A comparative analysis of machine learning algorithms for diabetes prediction
Published 2024“…The study contributes insights into the importance of pre-processing and feature selection in improving algorithm performance. …”
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Enhanced multi-objective evolutionary mating algorithm with improved crowding distance and levy flight for optimizing comfort index and energy consumption in smart buildings
Published 2025“…The proposed MOEMA enhances the original EMA framework through two key innovations: an improved crowding distance function inspired by the Non-dominated Sorting Genetic Algorithm (NSGA) to enhance solution diversity and selection pressure, and the integration of Levy flight mechanics to improve exploration efficiency by balancing local and global searches. …”
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Extension of RMIL conjugate gradient method for unconstrained optimization / Nur Idalisa Norddin
Published 2023“…Sufficient Descent Condition (SDC) and global convergence qualities for both the exact and the strong Wolfe line search were demonstrated to exist in NEWRMIL algorithm. …”
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Thesis -
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Heart-design nexus: the emotion algorithm
Published 2025“…How might these approaches help create a world that is not just functionally efficient but emotionally enriching? How might they contribute to more meaningful connections between people and the designed environments that surround them? …”
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A real-time traffic sign recognition system for autonomous vehicle using Yolo / Nurul Paudziah Aida Mohd Paudzi
Published 2020“…The finding from this study is believed to be helpful as it may contribute to the automotive industry. In future, this system can be improved by integrating with the navigation system such as Global Positioning System (GPS) to make the system more functional and achieve more advance monitoring.…”
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Discrete-time system identification using genetic algorithm with single parent-based mating technique
Published 2024“…Rigorous validation tests, including autocorrelation and cross-correlation functions, confirmed the reliability and robustness of these models. …”
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Optimization of supply chain management by simulation based RFID with XBEE Network
Published 2015“…This algorithm computes the optimal results of objective functions in a scientific manner. …”
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Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End
Published 2012“…In order to obtain a global optimum solution of the problem, an outer-approximation algorithm is proposed, whereby lower and upper bounds on the global optimum are generated, which are converged to a specified tolerance. …”
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