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High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm
Published 2025“…The trigonometric function-based sine cosine algorithm (SCA) may solve such problems, but it traps in local optima, making it inappropriate for larger optimization tasks. …”
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42
Optimizing Document Classification: Unleashing the Power of Genetic Algorithms
Published 2023“…Additionally, our proposed model optimizes the features using a genetic algorithm. Optimal feature selection performances a crucial role in this domain, enhancing the overall accuracy of the document classification system while reducing the time complexity associated with selecting the most relevant features from this large-dimensional space. …”
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Simulated Annealing and Genetic Algorithms for Optimal Regression Testing
Published 1999“…We present two natural optimization algorithms, namely, a simulated annealing and a genetic algorithm, for solving this problem. …”
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Optimization of Interval Type-2 Fuzzy Logic System Using Grasshopper Optimization Algorithm
Published 2022“…The forecasting performance of the proposed model is compared with other population-based optimized IT2-FLS including genetic algorithm and artificial bee colony optimization algorithm. …”
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46
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A genetic algorithm for corrective retesting. (c1995)
Published 1995Get full text
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48
Trial-based dominance for comparing both the speed and accuracy of stochastic optimizers with standard non-parametric tests
Published 2023“…<p>Non-parametric tests can determine the better of two stochastic optimization algorithms when benchmarking results are ordinal—like the final fitness values of multiple trials—but for many benchmarks, a trial can also terminate once it reaches a prespecified target value. …”
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Optimized FPGA Implementation of PWAM-Based Control of Three—Phase Nine—Level Quasi Impedance Source Inverter
Published 2019“…Since, PWAM control algorithm is more complex than PSCPWM, FPGA based implementation for PWAM control is discussed. …”
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EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach
Published 2019“…A series of vocabularies consisting of 10 cluster centers of each class is calculated using the k-means cluster algorithm. …”
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Improved Jaya Synergistic Swarm Optimization Algorithm to Optimize Task Scheduling Problems in Cloud Computing
Published 2024“…Overall, our proposed Improved Jaya Synergistic Swarm Optimization Algorithm offers a promising solution for optimizing TSCC (TSCC), contributing to enhanced resource utilization and system performance in cloud-based applications. …”
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52
Multiclass feature selection with metaheuristic optimization algorithms: a review
Published 2022“…Nevertheless, metaheuristic algorithms attract substantial attention to solving different problems in optimization. …”
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53
Cooperative Co-evolution using The Brain Storm Optimization Algorithm
Published 2016“…The Brain Storm Optimization (BSO) algorithm is a powerful optimization approach that has been proposed in the past few years. …”
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Parallel physical optimization algorithms for allocating data to multicomputer nodes
Published 1994“…Three parallel physical optimization algorithms for allocating irregular data to multicomputer nodes are presented. …”
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A Survey of cuckoo search algorithm: optimizer and new applications
Published 2024“…Cuckoo search (CS) is an efficient swarm intelligence-based algorithm that has come a long way since its start in 2009. …”
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Recent Advances in Butterfly Optimization Algorithm, Its Versions and Applications
Published 2023“…The butterfly optimization algorithm (BOA) is a recent successful metaheuristic swarm-based optimization algorithm. …”
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57
Using genetic algorithms to optimize software quality estimation models
Published 2004“…This thesis explores the use of genetic algorithms for the problem of optimizing existing rule-based software quality estimation models. …”
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masterThesis -
58
Physical optimization algorithms for mapping data to distributed-memory multiprocessors
Published 1992“…We present three parallel physical optimization algorithms for mapping data to distributed-memory multiprocessors, concentrating on irregular loosely synchronous problems. …”
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