Results 51 to 60 of about 55,623 (279)
Uluslararası Türk Eğitim Bilimleri DergisiThis paper explores the integration of metaheuristic artificial intelligence (AI) optimization algorithms into the process of curriculum evaluation, proposing a novel approach that could enhance educational outcomes.
Volkan Duran, Gülay Ekici
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Random adjustment - based Chaotic Metaheuristic algorithms for image contrast enhancement
Jurnal Ilmu Komputer dan Informasi, 2017 Metaheuristic algorithm is a powerful optimization method, in which it can solve problems by exploring the ordinarily large solution search space of these instances, that are believed to be hard in general.
Vina Ayumi +3 more
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Slime Mould Algorithm-Based Tuning of Cost-Effective Fuzzy Controllers for Servo Systems
International Journal of Computational Intelligence Systems, 2021 This paper suggests five new contributions with respect to the state-of-the-art. First, the optimal tuning of cost-effective fuzzy controllers represented by Takagi–Sugeno–Kang proportional-integral fuzzy controllers (TSK PI-FCs) is carried out using a ...
Radu-Emil Precup +4 more
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Bat Algorithm for Multi-objective Optimisation [PDF]
, 2011 Engineering optimization is typically multiobjective and multidisciplinary with complex constraints, and the solution of such complex problems requires efficient optimization algorithms.
Yang, Xin-She
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Ensemble‐based soil liquefaction assessment: Leveraging CPT data for enhanced predictions
Civil Engineering Design, Volume 7, Issue 1, Page 23-35, March 2025.Abstract This study focuses on predicting soil liquefaction, a critical phenomenon that can significantly impact the stability and safety of structures during seismic events. Accurate liquefaction assessment is vital for geotechnical engineering, as it informs the design and mitigation strategies needed to safeguard infrastructure and reduce the risk ...
Arsham Moayedi Far, Masoud Zare
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Automatic Data Clustering Using Hybrid Firefly Particle Swarm Optimization Algorithm
IEEE Access, 2019 The firefly algorithm is a nature-inspired metaheuristic optimization algorithm that has become an important tool for solving most of the toughest optimization problems in almost all areas of global optimization and engineering practices.
Moyinoluwa B. Agbaje +2 more
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Sensors, 2023 Algorithms for machine learning have found extensive use in numerous fields and applications. One important aspect of effectively utilizing these algorithms is tuning the hyperparameters to match the specific task at hand. The selection and configuration
Farkhanda Abbas +6 more
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The Canadian Journal of Chemical Engineering, EarlyView.Abstract Carbon dioxide‐reduced hydrogen can be synthesized through various methods such as dry‐reforming (DRM), steam reforming (SMR), and partial oxidation (POX). Tri‐reforming of methane (TRM) is a promising technology which combines all the above‐mentioned processes for the simultaneous production of hydrogen and syngas with high energy efficiency.
Paulo A. L. de Souza +3 more
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Metaheuristics for pharmacometrics
CPT: Pharmacometrics & Systems Pharmacology, 2021 Metaheuristics is a powerful optimization tool that is increasingly used across disciplines to tackle general purpose optimization problems. Nature‐inspired metaheuristic algorithms is a subclass of metaheuristic algorithms and have been shown to be ...
Seongho Kim +4 more
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Sand cat swarm optimization-based feedback controller design for nonlinear systems
Heliyon, 2023 The control of the open loop unstable systems with nonlinear structure is challenging work. In this paper, for the first time, we present a sand cat swarm optimization (SCSO) algorithm-based state feedback controller design for open-loop unstable systems.
Vahid Tavakol Aghaei +3 more
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