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Squirrel Search Algorithm for Portfolio Optimization
Published 2019“…This problem has been studied extensively in the literature where different models have been proposed since the classical Mean-Variance model was introduced by Harry Markowitz in 1952 and the later modified version by William Sharpe. …”
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masterThesis -
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Cuckoo search for portfolio optimization. (c2014)
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masterThesis -
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DG-Means – A Superior Greedy Algorithm for Clustering Distributed Data
Published 2022“…Distributed clustering algorithms, however, can fulfil this gap. They extract a classification model from the distributed objects even when they are in different sites and locations. …”
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masterThesis -
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An Effective Hybrid NARX-LSTM Model for Point and Interval PV Power Forecasting
Published 2021“…Then, the stacked LSTM model, optimized by Tabu search algorithm, uses the residual error correction associated with the original data to produce a point and interval PVPF. …”
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A Novel Hybrid Genetic-Whale Optimization Model for Ontology Learning from Arabic Text
Published 2019“…For evaluating the performance of the ontology learning approach, extensive comparisons are conducted using different Arabic corpora and bio-inspired optimization algorithms. …”
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Portfolio Selection Problem Using CVaR Risk Measures Equipped with DEA, PSO, and ICA Algorithms
Published 2022“…It was found that when solving the Mean-CVaR model with evolutionary algorithms, the risk decreased. …”
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Development of Lévy flight-based reptile search algorithm with local search ability for power systems engineering design problems
Published 2022“…The Lévy flight concept is used for better exploration capability in the proposed algorithm, whereas the Nelder-Mead simplex search algorithm is integrated for further exploitation. …”
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The buffered work-pool approach for search-tree based optimization algorithms
Published 2017“…Different algorithms adopt different branching and pruning techniques in order to reduce the unavoidable exponential growth in run time. …”
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conferenceObject -
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Calibration of building model based on indoor temperature for overheating assessment using genetic algorithm: Methodology, evaluation criteria, and case study
Published 2022“…This methodology includes a variance-based sensitivity analysis to determine building parameters that significantly influence indoor air temperatures, the Multi-Objective Genetic Algorithm to calibrate different rooms simultaneously based on the significant param eters identified by the sensitivity analysis, and new evaluation criteria to achieve a high-accuracy calibrated model. …”
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Evaluation of Aerosol Optical Depth and Aerosol Models from VIIRS Retrieval Algorithms over North China Plain
Published 2017“…The aerosol model used in VIIRS_EDR algorithm shows that dust and clean urban models were the dominant model types during the evaluation period. …”
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Optimizing Document Classification: Unleashing the Power of Genetic Algorithms
Published 2023“…Additionally, our proposed model optimizes the features using a genetic algorithm. …”
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Meta-Heuristic Procedures for the Multi-Resource Leveling Problem with Activity Splitting
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doctoralThesis -
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Physical optimization algorithms for mapping data to distributed-memory multiprocessors
Published 1992“…The technique proposed for large problems is based on a pre-mapping graph contraction heuristic algorithm, which results in a smaller search space. …”
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masterThesis -
17
Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars
Published 2023“…Finally, a design equation that can predict the shear capacity of one-way BFRC-BFRP slabs was proposed based on genetic algorithm. The proposed model showed the best prediction accuracy compared to the available design codes and guidelines with a mean of predicted to experimental shear capacities (V<sub>pred</sub>/V<sub>exp</sub>) ratio of 0.97 and a coefficient of variation of 17.91%.…”
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Performance assessment and exhaustive listing of 500+ nature-inspired metaheuristic algorithms
Published 2023“…For fair comparisons, a parameter tuning tool named irace is used to automatically configure the parameters of all 15 algorithms. In addition, whether these algorithms have a search bias to the origin (i.e., the center of the search space) is investigated. …”
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A fast exact sequential algorithm for the partial digest problem
Published 2016“…The algorithm is able to find all possible solutions for the input and works by traversing the solution tree with a breadth-first search in two stages and deleting all repeated subproblems. …”
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UniBFS: A novel uniform-solution-driven binary feature selection algorithm for high-dimensional data
Published 2024“…UniBFS exploits the inherent characteristic of binary algorithms-binary coding-to search the entire problem space for identifying relevant features while avoiding irrelevant ones. …”
