Search Results - (( using self method algorithm ) OR ( based optimization based algorithm ))

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  1. 1

    Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

    Published 2024
    “…To address the noise problem in multi-view data, this study enhances the gbs method and develops a new self-weighted graph multi-view clustering algorithm (swmcan). …”
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    Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

    Published 2023
    “…The evolutionary algorithm has been extensively used to solve a range of combinatorial optimization problems. …”
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    Article
  5. 5

    Self-adaptive conjugate method for a robust and efficient performance measure approach for reliability-based design optimization by Keshtegar, Behrooz, Baharom, Shahrizan, El-Shafie, Ahmed

    Published 2018
    “…The advanced mean value and hybrid mean value methods are commonly used to evaluate the probabilistic constraint of reliability-based design optimization (RBDO) problems. …”
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  6. 6

    Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm by Ehteram, Mohammad, Othman, Faridah, Yaseen, Zaher Mundher, Afan, Haitham Abdulmohsin, Allawi, Mohammed Falah, Malek, Marlinda Abdul, Ahmed, Ali Najah, Shahid, Shamsuddin, Singh, Vijay P., El-Shafie, Ahmed

    Published 2018
    “…In this study, a hybrid of the bat algorithm (BA) and the particle swarm optimization (PSO) algorithm, i.e., the hybrid bat-swarm algorithm (HBSA), was developed for the optimal determination of these four parameters. …”
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    Article
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    Utilizing self-organization systems for modeling and managing risk based on maintenance and repair in petrochemical industries by Jaderi, Fereshteh, Ibrahim, Zelina Zaiton, Nikoo, Mehdi, Nikoo, Mohammad

    Published 2018
    “…For this purpose, operation impact, operation flexibility, maintenance cost, impact of safety and environment and frequency parameters had been considered as input; and using this model, the risk level is calculated. Utilizing genetic algorithms, the structures of all self-organizing systems are optimized. …”
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    Article
  9. 9

    Prediction and multi-criteria-based schemes for seamless handover mechanism in mobile WiMAX networks by Mubarak, Mohammed Awadh Ahmed Ben

    Published 2013
    “…In the proposed HATSC scheme, the AHP method is uese for criteria weighting, while the TOPSIS method uses for the selection technique based on a multi-criteria decision-making algorithm is proposed. …”
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    Optimal tuning of sigmoid PID controller using nonlinear sine cosine algorithm for the automatic voltage regulator system --- KIV (status in press) by Mohd Helmi, Suid, Mohd Ashraf, Ahmad

    Published 2021
    “…In addition, the parameters of the proposed SPID controller are obtained using an enhanced self-tuning heuristic optimization method called Nonlinear Sine Cosine Algorithm (NSCA), for achieving a better dynamic response, particularly with regards to the steady-state errors and overshoot of the system. …”
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    Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks by Hussein, Yassein Soubhi

    Published 2014
    “…The third scheme works on the self optimization of handover parameters using fuzzy logic control (FLC) and multiple preparation (MP) called FuzAMP. …”
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    Nature-Inspired Drone Swarming for Wildfires Suppression Considering Distributed Fire Spots and Energy Consumption by Alsammak I.L.H., Mahmoud M.A., Gunasekaran S.S., Ahmed A.N., Alkilabi M.

    Published 2024
    “…Our quantitative tests show that the improved model has the best coverage (95.3%, 84.3% and 65.8%, respectively) compared to two other methods Levy Flight (LF) algorithm and Particle Swarm Optimization (PSO), which use the same initial parameter values. …”
    Article
  13. 13

    Feature selection optimization using hybrid relief-f with self-adaptive differential evolution by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran, Ahmad Nazri, Azree Shahrel, Mohamed, Raihani, Abd Manaf, Syaifulnizam

    Published 2017
    “…Hence, feature selection is embedded to select the most meaningful features based on their rank. Differential evolution (DE) is one of the evolutionary algorithms that are widely used in various classification domains. …”
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    Dual-head marking performance optimisation via evolutionary solutions by Koh J., Tiong S.K., Aris I.B., Mahmoud S.

    Published 2023
    “…This paper presents a new approach to optimise the performance of a multi-head marking system in terms of its marking speed This processing method named as MMA (Molecular Marking Optimisation algorithm) will adopt the use of Genetic Algorithm. …”
    Conference paper
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    Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

    Published 2015
    “…ARDE algorithm makes use of JADE strategy and the MDE_pBX parameters adaptive schemes as frameworks. …”
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    An Improved Network Intrusion Detection Method Based On CNN-LSTM-SA by Bian, Hui

    Published 2025
    “…To overcome these limitations, this research proposes the CNN-LSTM-SA method, an enhanced deep learning approach that integrates Convolutional Neural Networks, Long Short-Term Memory networks, and Self-Attention mechanisms. …”
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    Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

    Published 2016
    “…The rationale behind developing algorithms using real encoding of chromosome representations is the limitations of binary encoding. …”
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    Self-Adaptive Autoreclosing Scheme usingI Artificial Neural Network and Taguchi's Methodology in Extra High Voltage Transmission Systems by Desta, Zahlay Fitiwi

    Published 2009
    “…The fault identification prior to reclosing is based on optimized artificial neural network associated with three training algorithms, namely, Standard Error Back-Propagation, Levenberg Marquardt and Resilient Back-Propagation algorithms. …”
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