Search Results - (( practices evaluation method algorithm ) OR ( based optimization method algorithm ))

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  1. 1

    Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost by Chen, Suihai, Bong, Chih How, Chiu, Po Chan

    Published 2024
    “…Under the background of big data, it is of practical significance to prevent loan risk by the machine learning algorithm. …”
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    Article
  2. 2

    Harmony search-based robust optimal controller with prior defined structure by Rafieishahemabadi, Ali

    Published 2013
    “…In this approach, a combination of interacting two levels HS optimization algorithm is presented. In the first level, a new method for analytical formulation of integral square error cost function based on controller variables is elaborated for performance evaluation purposes by the proposed optimization algorithm. …”
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    Thesis
  3. 3

    Data-driven continuous-time Hammerstein modeling with missing data using improved Archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad

    Published 2024
    “…Across all experiments, the IAOA-based method demonstrated superior performance compared to AOA and other methods, including a hybrid approach combining the average multi-verse optimizer and sine cosine algorithm, particle swarm optimizer, the sine cosine algorithm, multi-verse optimizer and grey wolf optimizer. …”
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    Article
  4. 4

    Hybrid performance measures and mixed evaluation method for data classification problems by Hossin, Mohammad

    Published 2012
    “…First, this study examines the use of accuracy measure as a discriminator for building an optimized Prototype Selection (PS) algorithm. Second, this study evaluates the current evaluation practices for evaluating and comparing the two performance measures. …”
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    Thesis
  5. 5

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…So far, the tuning methods used for data-driven PID for the underactuated systems are mostly based on the multi-agent-based optimization, which means that the design requires substantial computation time and make it not practical for on-line tuning applications. …”
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    Thesis
  6. 6

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…So far, the tuning methods used for data-driven PID for the underactuated systems are mostly based on the multi-agent-based optimization, which means that the design requires substantial computation time and make it not practical for on-line tuning applications. …”
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    Thesis
  7. 7

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…Applications and improvements to the HKA algorithm suggest that optimization algorithm based on estimation principle has a huge potential in solving a wide variety of optimization problems. …”
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    Thesis
  8. 8

    Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment Problem by Ngo, T.S., Jaafar, J., Aziz, I.A., Aftab, M.U., Nguyen, H.G., Bui, N.A.

    Published 2022
    “…We evaluated the effectiveness of the proposed algorithm with the Tabu Search algorithm and the original genetic algorithm on the tested dataset. …”
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    Article
  9. 9

    PID TUNING OF DC MOTOR USING SWARM ITELLIGENCE ALGORITHM by Hasdi Aimon, Arhimny

    Published 2012
    “…In this project, Particle Swarm Optimization (PSO) as one of Swarm Intelligence Algorithm based has proposed to be integrated with PID (Proportional, Integral, Derivative) Controller in order to achieve optimal tuning method. …”
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    Final Year Project
  10. 10

    Optimizing tree planting areas through integer programming and improved genetic algorithm by Md Badarudin, Ismadi

    Published 2012
    “…The result of line representation promoting less iteration numbers indicates that time usage is more efficient. More number of optimal solutions in combined best-fit methods and the rejection of infeasible chromosomes in Genetic Algorithm are significant factors to be better efficiency. …”
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    Thesis
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