Search Results - (( using factorization search algorithm ) OR ( using optimization method algorithm ))

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  1. 1

    Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman by Che Osman, Siti Eshah

    Published 2019
    “…In future, this work could be enhanced for better performances in both aspects using another variant of the PSO or other potential metaheuristic searching techniques such as Firefly Optimization, Bat Algorithm and etc.…”
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    Thesis
  2. 2

    Real-Time State of Charge Estimation of Lithium-Ion Batteries Using Optimized Random Forest Regression Algorithm by Hossain Lipu M.S., Hannan M.A., Hussain A., Ansari S., Rahman S.A., Saad M.H.M., Muttaqi K.M.

    Published 2024
    “…Hence, a differential search algorithm (DSA) is employed to search for the optimal values of trees and leaves in the RFR algorithm. …”
    Article
  3. 3

    Refinement of Tuned Mass Damper parameters on machine support structure using dynamic Cuckoo Search algorithm by Ahmad Muinuddin, Mahmood, Zamri, Mohamed, Rosmazi, Rosli

    Published 2025
    “…This study proposes the use of a dynamic Cuckoo Search (CS) algorithm, a nature-inspired optimization method, to enhance the accuracy of TMD parameters when external factors, such as excitation frequency or structural properties, change. …”
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    Conference or Workshop Item
  4. 4

    Hybrid binary grey Wolf with Harris hawks optimizer for feature selection by Al-Wajih, R., Abdulkadir, S.J., Aziz, N., Al-Tashi, Q., Talpur, N.

    Published 2021
    “…Several significant GWO factors can be explored to enhance the performance of selection in classification, with two conflicting concepts to be considered in using or modeling a metaheuristic method, exploring a search field, and exploiting optimal solutions. …”
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    Article
  5. 5

    Hybrid Binary Grey Wolf with Harris Hawks Optimizer for Feature Selection by Al-Wajih, R., Abdulkadir, S.J., Aziz, N., Al-Tashi, Q., Talpur, N.

    Published 2021
    “…Several significant GWO factors can be explored to enhance the performance of selection in classification, with two conflicting concepts to be considered in using or modeling a metaheuristic method, exploring a search field, and exploiting optimal solutions. …”
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    Article
  6. 6

    Hybrid binary grey Wolf with Harris hawks optimizer for feature selection by Al-Wajih, R., Abdulkadir, S.J., Aziz, N., Al-Tashi, Q., Talpur, N.

    Published 2021
    “…Several significant GWO factors can be explored to enhance the performance of selection in classification, with two conflicting concepts to be considered in using or modeling a metaheuristic method, exploring a search field, and exploiting optimal solutions. …”
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    Article
  7. 7

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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    Thesis
  8. 8

    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…In the hybrid scheme, the initial parameters of the modified BP neural network are optimized by using the global search ability of genetic algorithm, improved by cat chaotic mapping to enrich its optimization capability. …”
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    Thesis
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  10. 10

    Stochastic fractal search algorithm for reconfiguration of distribution networks with distributed generations by Tran, T.T., Truong, K.H., Vo, D.N.

    Published 2020
    “…The SFS is a meta-heuristic algorithm inspired by the fractal theory for solving optimization problems. …”
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    Article
  11. 11

    PID-Ant Colony Optimization (ACO) control for electric power assist steering system for electric vehicle by Abu Hanifah, Rabiatuladawiyah, Toha, Siti Fauziah, Ahmad, Salmiah

    Published 2013
    “…The fast tuning feature of ACO algorithm is the factor that distinguish this hybrid method as compared to conventional trial and error method PID controller tuning. …”
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    Proceeding Paper
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  14. 14

    Low Complexity Error Correction in Low Density Parity Check (LDPC) Code Decoder and Encoder for Decode and Forward Cooperative Wireless Communication by JAM'AAH, SUUD

    Published 2021
    “…The Particle Swarm Optimization (PSO) search method is adopted to search the optimized scaling factor to obtain optimal error rate performance. …”
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    Thesis
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  16. 16

    Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

    Published 2018
    “…In the OGC framework, the exhibited explorative search behavior of the Gravitational Clustering (GC) algorithm has been addressed by (i) eliminating the agent velocity accumulation, and (ii) integrating an initialization method of agents using variance and median to subrogate the exploration process. …”
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    Thesis
  17. 17

    Optimization Of Pid Controller Using Grey Wolf Optimzer And Dragonfly Algorithm by Nik Mohamed Hazli, Nik Muhammad Aiman

    Published 2018
    “…In this research, swarming intelligence is used to solve optimisation problem. Grey Wolf Optimizer and Dragonfly Algorithm were chosen. …”
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    Monograph
  18. 18

    Successor selection for Ant Colony Optimization technique algorithm / Muhammad Iskandar Isman by Isman, Muhammad Iskandar

    Published 2017
    “…Therefore, in this research, will be use Ant Colony Optimization (ACO) algorithm as an optimize technique that provide a shortest path of defining a successor that is their highest value of criteria. …”
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    Thesis
  19. 19

    Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

    Published 2025
    “…The effectiveness of the proposed LSA + LSTM model is assessed using battery aging data from the NASA dataset. In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”
    Article
  20. 20

    Feature Selection Based on Grey Wolf Optimizer for Oil Gas Reservoir Classification by Al-Tashi, Q., Rais, H.M., Abdulkadir, S.J., Mirjalili, S.

    Published 2020
    “…The wrapper K-Nearest Neighbors (KNN) classifier is used to evaluate the selected features. In addition, to examine the efficiency of the proposed method, two recent algorithms namely: Whale Optimization algorithm (WAO) and Dragonfly Algorithm (DA) are implemented for comparison. …”
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    Conference or Workshop Item