Showing 141 - 160 results of 1,295 for search '"genetic algorithms"', query time: 0.06s Refine Results
  1. 141

    Fuel Costs Minimization on a Steel Billet Reheating Furnace Using Genetic Algorithms by Harley S. O. Santos, Paulo E. M. Almeida, Rodrigo T. N. Cardoso

    Published 2017-01-01
    “…For this purpose, a genetic algorithms approach is developed. Computational simulation results show that it is possible to minimize costs for different charge temperatures and production rates using the implemented method. …”
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  2. 142

    Module Partition Method of the Modular Design of Reducer based on Simulated Annealing and Genetic Algorithm by Zhao Han, Zhang Nan, Zong Wei

    Published 2015-01-01
    “…Finally,the products is classified by using the simulated annealing and genetic algorithm( SAGA),which is proved to be an efficient and rational way for module partition through the reducer instance.…”
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  5. 145

    Intelligent Ensemble Deep Learning System for Blood Glucose Prediction Using Genetic Algorithms by Dae-Yeon Kim, Dong-Sik Choi, Ah Reum Kang, Jiyoung Woo, Yechan Han, Sung Wan Chun, Jaeyun Kim

    Published 2022-01-01
    “…., long short-term memory (LSTM), stacked LSTM, bidirectional LSTM, and gated recurrent unit). Then, a genetic algorithm (GA) was applied to the five prediction models to optimize their weights through ensemble techniques and to yield (output) the final predicted BG values. …”
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    Genetic Algorithms in Antennas and Smart Antennas Design Overview: Two Novel Antenna Systems for Triband GNSS Applications and a Circular Switched Parasitic Array for WiMax Applications Developments with the Use of Genetic Algorithms by Stylianos C. Panagiotou, Stelios C. A. Thomopoulos, Christos N. Capsalis

    Published 2014-01-01
    “…Genetic algorithms belong to a stochastic class of evolutionary techniques, whose robustness and global search of the solutions space have made them extremely popular among researchers. …”
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    Optimization of Wind Turbine Airfoil Using Nondominated Sorting Genetic Algorithm and Pareto Optimal Front by Ziaul Huque, Ghizlane Zemmouri, Donald Harby, Raghava Kommalapati

    Published 2012-01-01
    “…Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) was used to determine the Pareto optimal set based on the response surfaces. …”
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  16. 156

    Inverse Analysis of the Partitioning Deformation Modulusof High-Arch Dams Based on Quantum Genetic Algorithm by Yantao Zhu, Xinqiang Niu, Jimin Wang, Chongshi Gu, Erfeng Zhao, Lixian Huang

    Published 2020-01-01
    “…A mechanical parameter inversion of high-arch dams is built from the intelligent optimization of an established algorithm by applying the quantum genetic algorithm. The proposed algorithm is tested to be feasible and valid for practical engineering projects and therefore shows scientific and practical application values.…”
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  17. 157

    Screw Performance Degradation Assessment Based on Quantum Genetic Algorithm and Dynamic Fuzzy Neural Network by Xiaochen Zhang, Hongli Gao, Haifeng Huang

    Published 2015-01-01
    “…To evaluate the performance of ball screw, screw performance degradation assessment technology based on quantum genetic algorithm (QGA) and dynamic fuzzy neural network (DFNN) is studied. …”
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  18. 158

    Concrete Mix Design for Service Life of RC Structures under Carbonation Using Genetic Algorithm by Seung-Jun Kwon, Byung Jae Lee, Yun Yong Kim

    Published 2014-01-01
    “…This paper is for a numerical technique for obtaining optimum concrete mix proportions through genetic algorithm (GA) for RC structures under carbonation which is considered as a serious deterioration in underground sites and big cities. …”
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  19. 159

    Research on Green Building Design Optimization Based on Building Information Modeling and Improved Genetic Algorithm by Fengtao Liu, Ting Ouyang, Bingzhang Huang, Jiehong Zhao

    Published 2024-01-01
    “…This article sets multiple objective functions based on the two dimensions of the carbon emissions of the entire life cycle of buildings and green building evaluation and uses the NSGA-II algorithm in genetic algorithms to optimize ten indicators selected from the two objectives. …”
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