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Data of simulation model for photovoltaic system's maximum power point tracking using sequential Monte Carlo algorithm
Published 2024“…The mathematical design and methodology of the complete PV system were detailed in our prior research, titled "Dynamic and Adaptive Maximum Power Point Tracking Using Sequential Monte Carlo Algorithm for Photovoltaic System" by Odat et al. (2023) [1]. …”
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Test case generation for path coverage. (c2000)
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Bird’s Eye View feature selection for high-dimensional data
Published 2023“…This approach is inspired by the natural world, where a bird searches for important features in a sparse dataset, similar to how a bird search for sustenance in a sprawling jungle. BEV incorporates elements of Evolutionary Algorithms with a Genetic Algorithm to maintain a population of top-performing agents, Dynamic Markov Chain to steer the movement of agents in the search space, and Reinforcement Learning to reward and penalize agents based on their progress. …”
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Estimating Construction Project Duration Using a Machine Learning Algorithm
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A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption
Published 2019“…To show the applicability of the proposed approach, Iran’s bitumen consumption data in the period of 1991-2006 are used as a case study. Findings Production, import, export, road construction and price are considered as the input data used in the present study. …”
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Salp swarm algorithm: survey, analysis, and new applications
Published 2024“…The benefits of the proposed algorithms in addressing real-world issues with challenging and unknown search areas are demonstrated by the outcomes of real-world case studies. …”
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Incremental Genetic Algorithm
Published 2006“…Classical Genetic Algorithms (CGA) are known to find good sub-optimal solutions for complex and intractable optimization problems. …”
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How can algorithms help in segmenting users and customers? A systematic review and research agenda for algorithmic customer segmentation
Published 2023“…Typically, studies generate four segments, although the maximum number rarely exceeds twenty, and in most cases, is less than ten. Based on these findings, we propose seven key goals and three practical implications to enhance customer segmentation research and application.…”
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Natural optimization algorithms for optimal regression testing
Published 1997“…The present two natural optimization algorithms, namely simulated annealing and genetic algorithms, for solving this problem. …”
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Incremental & classical genetic algorithm. (c2001)
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Intelligent Rapidly-Exploring Random Tree Star Algorithm
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A hybrid genetic algorithm for task allocation in multicomputers
Published 2018“…A hybrid genetic algorithm for the task allocation problem (HGATA) in multicomputers is presented. …”
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Simulated Annealing and Genetic Algorithms for Optimal Regression Testing
Published 1999“…The experimental results, which include a comparison with previous algorithms, show that the simulated annealing and genetic algorithms find the optimal or near-optimal number of retests within a reasonable time. …”
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A genetic algorithm for corrective retesting. (c1995)
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Fuzzy simulated evolution algorithm for topology design of campusnetworks
Published 2000“…Results show that on all test cases the simulated evolution algorithm exhibits more intelligent search of the solution subspace and was able to find better solutions than simulated annealing…”
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Time-varying volatility model equipped with regime switching factor: valuation of option price written on energy futures
Published 2025“…To determine the parameters of the regime switching model and identify when economic states change, we employ the EM algorithm, utilizing real gas futures price data. We validate our closed-form solution for the option pricing through simulations employing the generalized antithetic variates Monte-Carlo technique. …”
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Fixed-parameter algorithms for hitting set problems. (c2006)
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