Search Results - (( initial selection method algorithm ) OR ( using modification learning algorithm ))

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  1. 1

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

    Published 2017
    “…To overcome these ANN problems, the Genetic Algorithm (GA) has been most frequently used for this purpose, however, some drawbacks of GA include, slow search speed and dependence on initial parameters. …”
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    Thesis
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    Automated cone cut error detection of bitewing images using convolutional neural network by Mohamed Misbahou Mkouboi, Mohamed Moubarak, Olowolayemo, Akeem, Ghazali, Ahmad Badruddin

    Published 2023
    “…Methods: This study received ethical approval from the IIUM Research Ethics committee: Approval no: IREC 2022-151. 2712 bitewing images were collected and classified into normal and error groups from the Imaging Unit, Kulliyyah of Dentistry, IIUM. The deep learning method selected was Convolutional Neural Network (CNN), and the algorithm was used and trained to classify the cone cut error. …”
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    Proceeding Paper
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    Predicting noise-induced hearing loss (NIHL) in TNB workers using GDAM algorithm by Rehman Gillani, Syed Muhammad Zubair

    Published 2012
    “…Previously, several modifications were suggested to improve the convergence rate of Gradient Descent Back-propagation algorithm such as careful selection of initial weights and biases, learning rate, momentum, network topology, activation function and ‘gain’ value in the activation function. …”
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    Thesis
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    Modified Kohonen network algorithm for selection of the initial centres of Gustafson-Kessel algorithm in credit scoring by Sameer, Fadhaa Othman, Abu Bakar, Mohd Rizam

    Published 2017
    “…A good clustering analysis implemented by good Initial Centres of clusters should be selected. To overcome this problem of Gustafson-Kessel (GK) algorithm, we proposed a modified version of Kohonen Network (KN) algorithm to select the initial centres. …”
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    Article
  6. 6

    A hybrid residue based sequential encoding mechanism with XGBoost improved ensemble model for identifying 5-hydroxymethylcytosine modifications by Uddin I., Awan H.H., Khalid M., Khan S., Akbar S., Sarker M.R., Abdolrasol M.G.M., Alghamdi T.A.H.

    Published 2025
    “…Among the applied machine learning algorithms, the XGBoost ensemble model using the tenfold cross-validation test achieved improved results than existing state-of-the-art models. …”
    Article
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    Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925) by Kamarudin, Nur Azulia

    Published 2021
    “…Hence, this study concentrates on an automated model selection procedure for the SURE model by integrating the expectation-maximization (EM) algorithm estimation method, named SURE(EM)-Autometrics. …”
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    Monograph
  9. 9

    Multiple equations model selection algorithm with iterative estimation method by Kamarudin, Nur Azulia, Ismail, Suzilah

    Published 2016
    “…In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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    Article
  10. 10

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…Automated machine learning is a promising approach widely used to solve classification and prediction problems, which currently receives much attention for modification and improvement. …”
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    Article
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    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…Automated machine learning is a promising approach widely used to solve classification and prediction problems, which currently receives much attention for modification and improvement. …”
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    Article
  12. 12

    Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms by Koh, Johnny Siaw Paw

    Published 2008
    “…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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    Thesis
  13. 13

    Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

    Published 2018
    “…For the third problem a modified of Kohonen Network (MKN) algorithm was proposed to select the initial centres of clusters. …”
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  14. 14

    New selection algorithm for Mengubah Destini Anak Bangsa (MDAB) students / Zamali Tarmudi ... [et al.] by Tarmudi, Zamali, Saibin, Tammie Christy, Naharu, Nasrah, Ung, Ling Ling

    Published 2014
    “…This research introduces a new algorithm to select students from low income family the so-called Mengubah Destini Anak Bangsa (MDAB) using fuzzy approach. …”
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    Research Reports
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    Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

    Published 2019
    “…The first set showed the efficiency and performance of the proposed composing techniques including: kmean++ algorithm for initialization, fitness scaling for fitness selection, the proposed split and merge mutation operator, and choosing the medoid instead of the mean as a centroid-selection schema. …”
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    Thesis
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    Learning to filter text in forum message by Sainin, Mohd Shamrie

    Published 2005
    “…In this paper, the modification of the algorithm including pre-processing and classification will be discussed in the attempt to apply learning to filter forum messages.…”
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    Conference or Workshop Item
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    Three-term backpropagation algorithm for classification problem by Saman, Fadhlina Izzah

    Published 2006
    “…Standard Backpropagation Algorithm (BP) is a widely used algorithm in training Neural Network that is proven to be very successful in many diverse application. …”
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    Thesis
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    Effects of user selected conditions on modeling of dynamic systems using adaptive fuzzy model by Yaacob, Mohd. Shafiek, Jamaluddin, Hishamuddin

    Published 2001
    “…Three methods for choosing the initial parameter of the fuzzy model are considered, namely the on-line, the off-line, and the random initial parameters. …”
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    Article
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