يعرض 41 - 60 نتائج من 77 نتيجة بحث عن '(( genetic algorithm using processing ) OR ( genetic algorithm a processing ))', وقت الاستعلام: 0.11s تنقيح النتائج
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    On-site workshop investment problem: A novel mathematical approach and solution procedure حسب Nima Moradi (19418821)

    منشور في 2023
    "…<p>In real-world construction sites, On-Site Workshops (OSW) are installed to accelerate construction activities and facilitate the material handling process. These temporary OSWs are cost-effective, leading to decreasing the material handling cost and project makespan, which indicates their important role as a part of a construction project. …"
  3. 43

    GENETIC SCHEDULING OF TASK GRAPHS حسب Benten, M. S.

    منشور في 2020
    "…The problem of assigning tasks to processing elements as a combinatorital optimization is formulated, and a heuristic based on a genetic algorithm is presented. …"
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    article
  4. 44

    A genetic-based fuzzy logic power system stabilizer formultimachine power systems حسب Abido, M.A.

    منشور في 1997
    "…This paper presents a novel approach to combine genetic algorithms (GA) with fuzzy logic systems to design a genetic-based fuzzy logic power system stabilizer (GFLPSS) for multimachine power systems. …"
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    article
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    Tuning of a fuzzy logic power system stabilizer using geneticalgorithms حسب Abido, M.A.

    منشور في 1997
    "…The proposed approach uses genetic algorithms (GA) to search for optimal or near optimal settings of fuzzy logic power system stabilizer (FLPSS) parameters. …"
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    article
  9. 49

    Multi-Objective Optimization for Food Availability under Economic and Environmental Risk Constraints حسب Bashar Hassna (19170940)

    منشور في 2024
    "…Utilizing these assessments, a multi-objective optimization model is developed and solved using MATLAB (R2018a)’s Genetic Algorithm, aiming to identify optimal suppliers to meet Qatar’s food demand, with consideration of the economic, environmental, and risk factors. …"
  10. 50

    Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks حسب Najam Us Sahar Riyaz (22927843)

    منشور في 2025
    "…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R<sup>2</sup> = 0.05 to 0.99 in a representative thiophene set. …"
  11. 51

    Complexity Avoidance using Biological Resemblance of Modular Multivariable Structure حسب Kouatli, Issam

    منشور في 2014
    "…GFT (Genetic Fuzzimetric Technique) is of no exception which merges Fuzzy logic with genetic algorithm to achieve the optimization of the decision making process under uncertainty. …"
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    conferenceObject
  12. 52

    Scheduling and allocation in high-level synthesis using stochastic techniques حسب Sait, Sadiq M.

    منشور في 2020
    "…Scheduling and allocation can be formulated as an optimization problem. In this work, a unique approach to scheduling and allocation problem using the genetic algorithm (GA) is described. …"
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    article
  13. 53

    Localization of Damages in Plain And Riveted Aluminium Specimens using Lamb Waves حسب S. Andhale, Yogesh

    منشور في 2018
    "…The genetic optimization (GO) method is used to further refine the location of damage within the enclosed area obtained using astroid algorithm. …"
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  14. 54

    Pre-production movie rating prediction using machine learning. (c2017) حسب Gerges, Firas Abdallah

    منشور في 2017
    "…In this work, we present several machine learning techniques (Support Vectors Machine, K-Nearest Neighbors, C5, Neural Networks and Case-Based Reasoning) along with a genetic algorithm to predict the success of a movie before its production using the IMDB rating as an indicator of the success. …"
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    masterThesis
  15. 55

    Improving passenger satisfaction at Kuwait International Airport by using multi-objective optimisation حسب Alsaber, Ahmad

    منشور في 2024
    "…The proposed methods employ optimisation techniques such as mixed integer goal programming (MIGP) and genetic algorithm (GA) to offer a comparative multi-solution outcome towards optimising the passenger quality of services at airport departure check-in. …"
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  16. 56

    Using artificial bee colony to optimize software quality estimation models. (c2015) حسب Abou Assi, Tatiana Antoine

    منشور في 2016
    "…In order to measure such software quality characteristics, we must wait until the software is implemented, tested and put to use for a certain amount of time. Several software metrics have been proposed in the literature to avoid this long and costly process, and they proved to be a good means of estimating software quality. …"
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    masterThesis
  17. 57

    Intelligent route to design efficient CO<sub>2</sub> reduction electrocatalysts using ANFIS optimized by GA and PSO حسب Majedeh Gheytanzadeh (17541927)

    منشور في 2022
    "…The primary purpose of this study is to establish a new model through machine learning methods; namely, adaptive neuro-fuzzy inference system (ANFIS) combined with particle swarm optimization (PSO) and genetic algorithm (GA) for the prediction of *CO (the key intermediate) adsorption energy as the efficiency metric. …"
  18. 58

    A novel network-based SIS framework for improved GA performance حسب Tohme, Rawane

    منشور في 2025
    "…Genetic algorithms have long been used to solve complex optimization problems by mimicking natural selection processes. …"
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    masterThesis
  19. 59

    A Literature Review on System Dynamics Modeling for Sustainable Management of Water Supply and Demand حسب Khawar Naeem (17984062)

    منشور في 2023
    "…The solution approaches included the genetic algorithm (GA), particle swarm optimization (PSO), and the non-dominated sorting genetic algorithm (NSGA-II). …"
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    Dynamic performance evaluation and machine learning-assisted optimization of a solar-driven system integrated with PCM-based thermal energy storage: A case study approach حسب Haitham Osman (11737057)

    منشور في 2025
    "…Sensitivity and parametric analyses identify key performance parameters. A comprehensive techno-economic analysis is conducted, supported by a machine learning-assisted optimization framework that combines artificial neural networks with genetic algorithms. …"