Search Results - (( storage optimization modified algorithm ) OR ( variable extractions method algorithm ))

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  1. 1

    New Quasi-Newton Equation And Method Via Higher Order Tensor Models by Gholilou, Fahimeh Biglari

    Published 2010
    “…The efficiency of the usual QN methods is improved by accelerating the performance of the algorithms without causing more storage demand. The presented equation allows the modification of several algorithms involving QN equations for practical optimization that possess superior convergence prop- erty. …”
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    Thesis
  2. 2

    Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct... by Wong Ling Ai

    Published 2023
    “…Besides, an optimization algorithm with high efficiency is important to ensure the attainment of optimal solutions, where the optimization algorithms like genetic algorithm and particle swarm optimization are known to have high possibility of being trapped in local optimal points. …”
    text::Thesis
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    Solving the integrated inventory supply chain problems using meta-heuristic methods / Seyed Mohsen Mousavi by Seyed Mohsen , Mousavi

    Published 2018
    “…A Modified Particle Swarm Optimization (MPSO) algorithm, a Genetic Algorithm (GA), a modified fruit fly optimization algorithm (MFOA) and a simulated annealing (SA) algorithm were used to find the optimal solution. …”
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    Thesis
  5. 5

    The Bacterial Foraging Optimisation Algorithm using Prototype Selection and Prototype Generation for Data Classification by Faizol, Bin Mohd Suria

    Published 2020
    “…Technically, BFOA has been applied as supplementary algorithm for optimizing weight, parameters for other classifier algorithms and selecting optimised features for other classifiers. …”
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    Thesis
  6. 6

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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    Thesis
  7. 7

    A modified weighted support vector machine (WSVM) to reduce noise data in classification problem by Mohd Dzulkifli, Syarizul Amri

    Published 2021
    “…When noise exists in training data, the decision boundary of SVM would deviate from the optimal hyperplane severely. To overcome SVM drawback for noise data problem, WSVM using KPCM algorithm was used but WSVM using kernel-based learning algorithm such as KPCM algorithm suffer from training complexity, expensive computation time and storage memory when noise data contaminate training data. …”
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    A Hybrid Sparrow Search Optimized Fractional Virtual Inertia Control for Frequency Regulation of Multi-Microgrid System by Fadheel B.A., Wahab N.I.A., Manoharan P., Mahdi A.J., Radzi M.A.B.M., Soh A.B.C., Ridha H.M., Alsoud A.R., Veerasamy V., Irudayaraj A.X.R., Alemu B.D.

    Published 2025
    “…The hybrid sparrow search and mountain gazelle optimizer algorithm (SSAMGO) optimizes the parameters for the three-loop controller. …”
    Article
  10. 10

    Coronary artery stenosis detection and visualization / Tang Sze Ling by Tang, Sze Ling

    Published 2015
    “…The proposed method benchmarked with the state-of-the-art methods and achieved comparable results. …”
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    Thesis
  11. 11

    Optimizing timber transportation planning for timber harvesting using bees algorithm in Malaysia by Jamaluddin, Jamhuri, Kamarudin, Norizah, Ismail, Mohd Hasmadi, Ahmad, Siti Azfanizam

    Published 2023
    “…A Bees Algorithm (BA) was proposed to find an optimum TTP for timber extraction, forest road, and landing locations with grid cell-sized 10 m × 10 m and attributed with fixed and variable costs. …”
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    Article
  12. 12

    Multi road marking detection system for autonomous car using hybrid- based method by Shah, Khan Bahadur

    Published 2018
    “…Wu dataset that consist of 1208 road images, which were extracted from videos recorded around California, the proposed algorithm performed satisfactorily. …”
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    Thesis
  13. 13

    Quasi-Newton type method via weak secant equations for unconstrained optimization by Lim, Keat Hee

    Published 2021
    “…Motivated by the idea of memoryless scheme, the proposed formulas are further modified such that only vector computations and storage are required at every iteration. …”
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    Thesis
  14. 14

    Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

    Published 2010
    “…The gain and the Jacobian matrices associated with the basic algorithm require large storage and have to be evaluated at every iteration, resulting in more computation time. …”
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    HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

    Published 2014
    “…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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    Final Year Project
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    Augmentation of basic-line-search and quick-simplex-method algorithms to enhance linear programming computational performance by Nor Azlan, Nor Asmaa Alyaa

    Published 2021
    “…The methodology starts with literature comprehension studies on the computation pitfalls and existed augmentation studies of Simplex algorithm. Then, followed by concept development which consists of concept extraction, computation stages classification and algorithms integration. …”
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    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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    Thesis