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    Improved dung beetle optimization algorithm and finite element analysis for spindle optimization by Haohao, Ma, As’arry, Azizan, Xuping, Wu, Ismail, Mohd Idris Shah, Ramli, Hafiz Rashidi, Saad, Mohd Sazli, Delgoshaei, Aidin

    Published 2024
    “…This research introduces an integrated optimization methodology for spindle design, combining the improved dung beetle optimization (IDBO) algorithm with finite element analysis (FEA). …”
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    A genetic algorithm approach to VLSI macro cell non-slicing floorplans using binary tree by Rahim At Samsuddin, H. A., Ab. Rahman, A. A. H., Andaljayalakshmi, G., Ahmad, R. B.

    Published 2008
    “…Furthermore, the robustness of genetic algorithm also has been investigated in order to validate the performance stability in achieving the optimal solution for every runtime. …”
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    Hyper-Heuristic Evolutionary Approach for Constructing Decision Tree Classifiers by Kumar, Sunil, Ratnoo, Saroj, Vashishtha, Jyoti

    Published 2021
    “…Finding optimal values for the hyper parameters of a decision tree construction algorithm is a challenging issue. …”
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    Enhanced weight-optimized recurrent neural networks based on sine cosine algorithm for wave height prediction by Alqushaibi, A., Abdulkadir, S.J., Rais, H.M., Al-Tashi, Q., Ragab, M.G., Alhussian, H.

    Published 2021
    “…This paper proposes an enhanced weight-optimized neural network based on Sine Cosine Algorithm (SCA) to accurately predict the wave height. …”
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    Optimization of medical image steganography using n-decomposition genetic algorithm by Al-Sarayefi, Bushra Abdullah Shtayt

    Published 2023
    “…Despite attempts to optimize LSB, these issues persist due to (1) the formulation of the optimization suffering from non-valid implicit constraints, causing inflexibility in reaching optimal embedding, (2) lacking convergence in the searching process, where the message length significantly affects the size of the solution space, and (3) issues of application customizability where different data require more flexibility in controlling the embedding process. …”
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    Reinforcement learning in risk management for pharmaceutical construction projects: frontiers, challenges, and improvement strategies by Junjia, Yin, Jiawen, Liu, Alias, Aidi Hizami, Haron, Nuzul Azam, Abu Bakar, Nabilah

    Published 2025
    “…Therefore, this paper reviews the practical applications of six algorithms—Deep Q-Network (DQN), Deep Deterministic Policy Gradient (DDPG), and Proximity Policy Optimization (PPO)—in construction safety, temperature control, resource scheduling, and automated equipment optimization, validating the potential of reinforcement learning to effectively manage dynamic risks through adaptive learning. …”
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    Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat by Chia , Yu Huat

    Published 2024
    “…This is due to the data generated from the numerical model possess the pattern for the ML algorithm ease of prediction. In addition, Coati Optimization algorithm, Particle Swarm Opimisation (PSO) and Bayesian Optimsiation (BO) are integrated to identify optimal parameters and minimize settlement during twin tunnel excavation and GBT with the optimisation algorithm has shown consistent capability identifying the least SS induced by twin tunnels Keyword: …”
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    Hybrid weight deep belief network algorithm for anomaly-based intrusion detection system by Maseer, Ziadoon Kamil

    Published 2022
    “…In this study, the Deep Belief Network algorithm was optimized and constructed to design an effective NIDS anomaly model. …”
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    Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak by Emily Sing Kiang, Siew

    Published 2025
    “…The model employs a two-level structure, where the first level uses standard soft constraints as the objective function to evaluate solution quality, while the second level dynamically adapts to faculty-specific preferences. A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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    Accurate localization method combining optimized hybrid neural networks for geomagnetic localization with multi-feature dead reckoning by Yan, Suqing, Luo, Baihui, Sun, Xiyan, Xiao, Jianming, Ji, Yuanfa, Kamarul Hawari, Ghazali

    Published 2025
    “…To address these issues, we propose a fusion localization algorithm based on particle swarm optimization. First, we construct a five-dimensional hybrid LSTM (5DHLSTM) neural network model, and the 5DHLSTM network structure parameters are optimized via particle swarm optimization (PSO) to achieve geomagnetic localization. …”
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    Optimization of hydropower reservoir system using genetic algorithm for various climatic scenarios by Tayebiyan, Aida

    Published 2015
    “…In order to increase the system efficiency and maximize the power generation, constructed operation models were optimized. To determine the optimum solution in each policy, real coded genetic algorithm is used as an optimization technique. …”
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    Modeling and Optimization of Tapered Rectangular Thin-walled Columns Subjected to Oblique Loading for Impact Energy Absorption by Siti Aishah, Rusdan, Tarlochan, Faris, Mohamad Rusydi, Mohamad Yasin

    Published 2013
    “…The optimal design is obtained by using the constrained nonlinear multivariable optimization algorithm provided by MATLAB. …”
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    Application of system identification method coupled with evolutionary algorithms for the optimization of power consumption in a pem fuel cell propulsion system / Suhadiyana Hanapi by Hanapi, Suhadiyana

    Published 2018
    “…This thesis makes a number of key contributions to the advancement of fuel cell vehicle design within two main research areas; powertrain system design based on quality energy, and optimization system based on biology based algorithms. …”
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