Search Results - (( using factorizations _ algorithm ) OR ( using function method algorithm ))

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  1. 1

    A study on regional GDP forecasting analysis based on radial basis function neural network with genetic algorithm (RBFNN-GA) for Shandong economy by Qing, Zhang, Abdullah, Abdul Rashid, Choo, Wei Chong, Ali, Mass Hareeza

    Published 2022
    “…This stochastic learning method is a useful addition to the existing methods for determining the center and smoothing factors of radial basis function neural networks, and it can also help the network more efficiently train. …”
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    Article
  2. 2

    Firefly analytical hierarchy algorithm for optimal allocation and sizing of distributed generation in radial distribution network by Bujal, Noor Ropidah

    Published 2022
    “…As for multi-objective functions associated with the optimisation problem, a weight-sum method is typically used to determine each objective function's coefficient factors (CF). …”
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    Thesis
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    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
  5. 5

    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control by Srazhidinov, Radik

    Published 2016
    “…In recent works, it was shown that the SEF can be approximated using tangential hyperbolic function (THF) for Hammerstein and Wiener NLFXLMS algorithms, such that the degree of nonlinearity can be estimated using modelling approach. …”
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    Thesis
  6. 6

    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…In recent years soft computing methods like fuzzy logic and genetic algorithm are being used in modeling complex processes of hydrologic events. …”
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    Thesis
  7. 7

    Effect of fitness function on localization performance in range-free localization algorithm by Han, Fengrong, Izzeldin Ibrahim, Mohamed Abdelaziz, Kamarul Hawari, Ghazali, Zhao, Yue

    Published 2024
    “…How to choose the best localization fitness function for a specific target is a key factor in determining whether the localization algorithm is accurate or not. …”
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    Article
  8. 8

    Robotic indoor path planning using dijkstra's algorithm with multi-layer dictionaries by Fadzli, S.A., Abdulkadir, S.I., Makhtar, M., Jamal, A.A.

    Published 2016
    “…The adjacency matrix is the naive storage structure of the algorithm. This storage structure has limited the use of the algorithm as it expands large storage space. …”
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    Conference or Workshop Item
  9. 9

    Enhancement of Ant System Algorithm for Course Timetabling Problem by Djamarus, Djasli

    Published 2009
    “…Results of the experiments that were conducted using various data sets showed that the proposed algorithm produced better course schedule solution than the Greedy Algorithm, Genetic Algorithm, and other variants of Ant System Algorithm.…”
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    Thesis
  10. 10

    Design Methodology and Analysis of Hash Function based-on Field Programmable Gate Array for Hash-based Message Authentication Code Application by SHAMSIAH BINTI, SUHAILI

    Published 2025
    “…The main objective of this research is to formulate unfolding transformation factor 2 and factor 4 methods into hash function design. …”
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    Thesis
  11. 11

    High-Throughput of SHA-256 Hash Function with Unfolding Transformation by Shamsiah, Binti Suhaili, Watanabe, Takahiro

    Published 2019
    “…Hash Function in cryptography algorithms is used to encrypt the message by giving the appropriate output based on the structure of the hash function itself. …”
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    Proceeding
  12. 12

    High-Throughput of SHA-256 Hash Function with Unfolding Transformation by Shamsiah, Binti Suhaili, Watanabe, Takahiro

    Published 2019
    “…Hash Function in cryptography algorithms is used to encrypt the message by giving the appropriate output based on the structure of the hash function itself. …”
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    Proceeding
  13. 13

    Optimum grouping in a modified genetic algorithm for discrete-time, non-linear system identification by Abd Samad, Md Fahmi

    Published 2007
    “…The genetic algorithm approach is widely recognized as an effective and flexible optimization method for system identification. …”
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    Article
  14. 14

    Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat by Yuliant, Sibaroni, Sri Suryani, Prasetiyowati, Iqbal Bahari, Sudrajat

    Published 2020
    “…In this study, the problem of determination dengue disease factors was modeled using a neural network. The activation function in this neural network model then estimated using genetic algorithms. …”
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    Article
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    Modeling time series data using Genetic Algorithm based on Backpropagation Neural network by Haviluddin

    Published 2018
    “…This study showed the task of optimizing the topology structure and the parameter values (e.g., weights) used in the BPNN learning algorithm by using the GA. …”
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    Thesis
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    Graph-Based Algorithm With Self-Weighted And Adaptive Neighbours Learning For Multi-View Clustering by He, Yanfang

    Published 2024
    “…Particularly, swmcan addresses multi-view data noise using the l1-norm and optimizes the objective function through a novel iterative reweighted method. …”
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    Thesis
  19. 19

    Disparity map algorithm for stereo matching process using local based method by Gan, Melvin Yeou Wei

    Published 2022
    “…Global method performs a matching process using global energy or a probability function over the whole image. …”
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    Thesis
  20. 20

    Wood texture detection with conjugate gradient neural network algorithm by Widyarto, Setyawan, Suryasa, I. Nyoman, Khairul Annuar, Abdullah, Fajarianto, Otto, Mohd Shafry, Mohd Rahim, Priyandoko, Gigih, Budaya, Gilang Anggit

    Published 2017
    “…The experiments are based on artificial neural network (ANN) algorithm that used back propagation and conjugate gradient method of training function in the process of identification. …”
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    Conference or Workshop Item