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  1. 1

    Perbandingan penggunaan algoritma Krzyzak dengan algoritma rambatan balik piawai dalam domain peramalan by Alwee, Razana, Sallehuddin, Roselina, Shamsuddin, Siti Mariyam

    Published 2004
    “…The performance is measured based on the accuracies, which is, quantified by root mean square error and learning speed for convergence. The results show that by using a small value of learning rate, Krzyzak algorithm is better than standard back propagation algorithm for medium and long term forecasting.…”
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    Article
  2. 2

    A machine learning approach to tourism recommendations system by Chia, An

    Published 2025
    “…To overcome this problem, this project implements machine learning algorithms with collaborative filtering, content-based filtering and hybrid filtering approaches. …”
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    Final Year Project / Dissertation / Thesis
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    Perbandingan penggunaan algoritma Krzyzak dengan algoritma rambatan balik piawai dalam domain peramalan by Alwee, Razana, Sallehuddin, Roselina, Shamsuddin, Siti Mariyam

    Published 2004
    “…The performance is measured based on the accuracies, which is, quantified by root mean square error and learning speed for convergence. The results show that by using a small value of learning rate, Krzyzak algorithm is better than standard back propagation algorithm for medium and long term forecasting.…”
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    Article
  5. 5
  6. 6

    Watermarking in safe region of frequency domain using complex-valued neural network by Olanrewaju, Rashidah Funke, Khalifa, Othman Omran, Hassan Abdalla Hashim, Aisha, Aburas, A. A., Zeki, Akram M.

    Published 2010
    “…It has been discovered by computational experiments that Complex Back-Propagation (CBP) algorithm is well suited for learning complex pattern, and it has been reported that this ability can successfully be applied in image processing with complex values. …”
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    Proceeding Paper
  7. 7

    Attribute related methods for improvement of ID3 Algorithm in classification of data: A review by Nur Farahaina, Idris, Mohd Arfian, Ismail

    Published 2020
    “…Decision tree is an important method in data mining to solve the classification problems. There are several learning algorithms to implement the decision tree but the most commonly-used is ID3 algorithm. …”
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    Article
  8. 8

    Music Recommender System Using Machine Learning Content-Based Filtering Technique by Foong, Kin Hong

    Published 2022
    “…In this study, methods of K-Mean Clustering, Euclidean Distance and Cosine Similarity are implemented. These are the popular algorithm for unsupervised learning, a machine learning method to analyse and cluster datasets. …”
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    Undergraduates Project Papers
  9. 9

    Enhancing Classification Algorithms with Metaheuristic Technique by Cokro, Nurwinto, Tri Basuki, Kurniawan, Misinem, ., Tata, Sutabri, Yesi Novaria, Kunang

    Published 2024
    “…In its operation, the metaheuristic algorithm optimizes the feature selection process,which will later be processed using the classification algorithm.Three (3) meta-heuristics were implemented, namely Genetic Algorithm, Particle Swarm Optimization, and Cuckoo Search Algorithm; the experiment was conducted, and the results were collected and analyzed. …”
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    Article
  10. 10

    Development of lung cancer prediction system using meta-heuristic optimized deep learning model by Mohamed Shakeel, Pethuraj

    Published 2023
    “…Finally, the classification is implemented using an ensemble classifier, deep learning instantaneously trained a neural network and an Autoencoder-based Recurrent Neural Network (ARNN) classification algorithm. …”
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    Thesis
  11. 11

    Kernel and multi-class classifiers for multi-floor wlan localisation by Abd Rahman, Mohd Amiruddin

    Published 2016
    “…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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    Thesis
  12. 12

    Case Slicing Technique for Feature Selection by A. Shiba, Omar A.

    Published 2004
    “…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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    Thesis
  13. 13

    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption by Nurnajmin Qasrina Ann, Ayop Azmi

    Published 2023
    “…Then, the developed algorithm is implemented to estimate the parameters of the Lorenz system. …”
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    Thesis
  14. 14

    Car dealership web application by Yap, Jheng Khin

    Published 2022
    “…Hence, two transfer learning algorithms were proposed and implemented to provide initial performance boost to the River adaptive random forest regressor and classifier, respectively. …”
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    Final Year Project / Dissertation / Thesis
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    Damageless Digital Watermarking Using Complex-valued Artificial Neural Network by Olanweraju, Rashidah Funke

    Published 2010
    “…Implementation results have shown that this watermarking algorithm has a high level of robustness and accuracy in recovery of the watermark.…”
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    Article
  17. 17

    Prediction models of heritage building based on machine learning / Nur Shahirah Ja'afar by Ja'afar, Nur Shahirah

    Published 2021
    “…Thus, through the implementation of machine learning, the researcher can analyse the proper and acceptable algorithms that can be used in heritage property price prediction which also are recommended for other researchers. …”
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    Thesis
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    Deep Learning Based Face Attributes Recognition by Saidi, Mohamad Hazim

    Published 2018
    “…Combined-algorithm based optimizers plays an important role in optimizing the training algorithm. …”
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    Monograph
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    Extreme learning machine for user location prediction in mobile environment by Mantoro, Teddy, Olowolayemo, Akeem, Olatunji, Sunday O., Ayu, Media Anugerah, Md. Tap, Abu Osman

    Published 2011
    “…Purpose – Prediction accuracies are usually affected by the techniques and devices used as well as the algorithms applied. This work aims to attempt to further devise a better positioning accuracy based on location fingerprinting taking advantage of two important mobile fingerprints, namely signal strength (SS) and signal quality (SQ) and subsequently building a model based on extreme learning machine (ELM), a new learning algorithm for single-hidden-layer neural networks. …”
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    Article