Search Results - (( probability function search algorithm ) OR ( based optimization based algorithm ))
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1
Tree-based contrast subspace mining method
Published 2020“…This thesis also presents the optimization of contrast subspace search of the tree-based method by genetic algorithm. …”
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2
Improved flower pollination optimization algorithm based on swap operator and dynamic switch probability selection
Published 2023“…Furthermore, it is hybridized with the Pattern Search algorithm to ensure the optimality of the solution. …”
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3
Dynamic probability selection for flower pollination algorithm based on metropolis-hastings criteria
Published 2021“…However, FPA still suffers from variability of its performance as there is no one size that fits all values for pa, depending on the characteristics of the optimization function. This paper proposed flower pollination algorithm metropolis-hastings (FPA-MH) based on the adoption of Metropolis-Hastings criteria adopted from the Simulated Annealing (SA) algorithm to enable dynamic selection of the pa probability. …”
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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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An empirical study of density and distribution functions for ant swarm optimized rough reducts
Published 2011“…Ant Swarm Optimization refers to the hybridization of Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) algorithms to enhance optimization performance. …”
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6
Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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7
Performance Enhancement Of Artificial Bee Colony Optimization Algorithm
Published 2013“…To overcome the problems, this research work has proposed few modified and new ABC variants; Gbest Influenced-Random ABC (GRABC) algorithm systematically exploits two different mutation equations for appropriate exploration and exploitation of search-space, Multiple Gbest-guided ABC (MBABC) algorithm enhances the capability of locating global optimum by exploiting so-far-found multiple best regions of a search-space, Enhanced ABC (EABC) algorithm speeds up exploration for optimal-solutions based on the best so-far-found region of a search-space and Enhanced Probability-Selection ABC (EPS-ABC) algorithm, a modified version of the Probability-Selection ABC algorithm, simultaneously capitalizes on three different mutation equations for determining the global-optimum. …”
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8
Optimizing S-box generation based on the Adaptive Agent Heroes and Cowards Algorithm
Published 2021“…The main feature of AAHC is the fact that the algorithm allows adaptive assignment of its population agents into cowards and heroes based on the exponential controlling functions. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
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10
A hybrid Q-learning sine-cosine-based strategy for addressing the combinatorial test suite minimization problem
Published 2018“…The sine-cosine algorithm (SCA) is a new population-based meta-heuristic algorithm. …”
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A Comparative Performance Analysis of Gaussian Distribution Functions in Ant Swarm Optimized Rough Reducts
Published 2011“…Solution vector of ACO is presented by implementing density and distribution function to search for a better solution and to specify a probability functions for every particle (ant). …”
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12
The effect of job satisfaction on the relationship between organizational culture and organizational performance
Published 2023“…Furthermore, it is hybridized with the Pattern Search algorithm to ensure the optimality of the solution. …”
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13
Hybridization of Strength Pareto Multiobjective Optimization with Modified Cuckoo Search Algorithm for Rectangular Array
Published 2017“…In addition, the MCS algorithm is hybridized with the particle swarm optimization (PSO) and hill climbing (HC) stochastic techniques along with the standard strength Pareto evolutionary algorithm (SPEA) forming the MCSPSOSPEA and MCSHCSPEA, respectively.All the proposed MCS-based algorithms are examined to perform MO optimization on Zitzler–Deb–Thiele’s (ZDT’s) test functions. …”
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14
Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification
Published 2011“…Since EC, like genetic algorithm, relies on randomness and probabilities, it is cumbersome when constraints are present in the search. …”
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The efficiency of conjugate gradient methods with global convergence / Siti Nur Hafiza Shamsudin
Published 2019“…A simple three-term conjugate gradient algorithm for unconstrained optimization. Journal of Computational and Applied Mathematics, 241, 19-29.). …”
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16
Sine-cosine optimization-based bijective substitution-boxes construction using enhanced dynamics of chaotic map
Published 2018“…This paper proposes a novel method of constructing strong substitution-boxes (S-boxes) of order n (4 ≤ n ≤ 8) based on a recent optimization algorithm known as sine-cosine algorithm (SCA). …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…One of these low-level heuristics is selected by EMCQ in each iteration based on the best performance. Apart from the best low-level heuristic, EMCQ also gives a chance to low-performing heuristics to search for the optimal threshold values using their probability density function. …”
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A hyper-heuristic based strategy for image segmentation using multilevel thresholding
Published 2025“…One of these low-level heuristics is selected by EMCQ in each iteration based on the best performance. Apart from the best low-level heuristic, EMCQ also gives a chance to low-performing heuristics to search for the optimal threshold values using their probability density function. …”
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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…The suggested algorithm outperforms the competition in terms of improving path cost, smoothness, and search time. …”
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