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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
    “…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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    Thesis
  2. 2

    Characterization of oil palm fruitlets using artificial neural network by Olukayode, Ojo Adedayo

    Published 2014
    “…To further validate the generalization accuracy of the LSB_ANN, its performance was compared with that of a Multi-ANFIS network as well as those of three different ANN training algorithms: Levenberg Marquardt (LM) algorithm, Resilient Backpropagation (RP) algorithm and Gradient Descent with Adaptive learning rate (GDA). …”
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    Thesis
  3. 3

    An initial state of design and development of intelligent knowledge discovery system for stock exchange database by Che Mat @ Mohd Shukor, Zamzarina, Khokhar, Rashid Hafeez, Md Sap, Mohd Noor

    Published 2004
    “…Generally our clustering algorithm consists of two steps including training and running steps.The training step is conducted for generating the neural network knowledge based on clustering.In running step, neural network knowledge based is used for supporting the Module in order to generate learned complete data, transformed data and interesting clusters that will help to generate interesting rules.…”
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    Conference or Workshop Item
  4. 4

    Visual analysis to investigate the capability of ANFIS in modelling hydrological relationship using synthetic dataset by Ngahzaifa, Ab. Ghani, Zuriani, Mustaffa, Zafril Rizal, M Azmi

    Published 2018
    “…In using most of the machine learning algorithms including ANFIS, to obtain the best model, the common and normal approach is always by comparing models of different parameter settings based on the goodness-offit statistical measures. …”
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    Article
  5. 5

    Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation by Chen, Qipeng, Xiong, Qiaoqiao, Huang, Haisong, Tang, Saihong, Liu, Zhenghong

    Published 2024
    “…Finally, the concept of model compression is integrated, utilizing scaling factors in the batch normalization (BN) layer, and introducing sparse factors to perform sparse training on the network. …”
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    Article
  6. 6

    An Improved Diabetes Risk Prediction Framework : An Indonesian Case Study by Sutanto, Daniel Hartono

    Published 2018
    “…Pre-processing resolves the issue of missing data and hence normalizes the data.Outlier treatment employs k-mean clustering to validate the class.Suitable components were selected through comparison of classifier algorithms and feature selection.Attribute weighting based feature selection was selected for assigning weightage.Weighted risk factor was used on training dataset in order to improve accuracy and computation time of the prediction. …”
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    Thesis
  7. 7

    Cognitive knowledge-based model for adaptive feedback: A case in physics / Andrew Thomas Bimba by Andrew Thomas, Bimba

    Published 2019
    “…In a computer-based learning environment, feedback is considered as one of the most effective factors which influence learning. …”
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    Thesis
  8. 8

    A proposed approach for diabetes diagnosis using neuro-fuzzy technique by Alasaady, Maher Talal, Mohd Aris, Teh Noranis, Mohd Sharef, Nurfadhlina, Hamdan, Hazlina

    Published 2022
    “…In the classification stage, ANFIS classifiers were trained using the hybrid learning algorithm of the neural network. …”
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    Article
  9. 9

    Prediction of breast cancer diagnosis using machine learning in Malaysian women by Mokhtar, Tengku Muhammad Hanis Tengku

    Published 2024
    “…This project found that there was a strong interest in the application of ML to breast cancer in the last three decades. The three frequently used ML algorithms were deep learning, support vector machine (SVM), and cluster analysis. …”
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    Thesis
  10. 10

    The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

    Published 2015
    “…It’s data-driven, self-adaptive, and non-linear capabilities channel it for use in processing at high speed and ability to learn the solution to a problem from a set of examples. …”
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    Thesis
  11. 11

    Predicting Market Trends : A Stock Prices Forecasting with Artificial Neural Network for Apple Inc. and Microsoft Corp. by Nur Fazliana, Rahim, Farah Liyana, Azizan, Nur’azra Alia Nisa, Zulpakar

    Published 2025
    “…The unpredictability of stock price behaviour, influenced by numerous factors, adds complexity to this process. Consequently, numerous studies have explored the use of machine learning for stock price forecasting. …”
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    Article
  12. 12

    Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining by Termedi @ Termiji, Mohammad Izzuan

    Published 2023
    “…Four different data mining classification algorithms which are Random Forest, PART, J48 and Naive Bayes will be used on the dataset. …”
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    Thesis
  13. 13

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    Published 2004
    “…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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    Thesis
  14. 14

    An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma by Sani , Danjuma

    Published 2017
    “…In addition, the algorithm was relatively easy to understand compare to the state of the art of normal parameter reduction algorithm. …”
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    Thesis
  15. 15

    JPEG Image Encryption Using Combined Reversed And Normal Direction-Distorted Dc Permutation With Key Scheduling Algorithm-Based Permutation by Abu, Ahmad Zaidee

    Published 2008
    “…The proposed approach uses a frequency domain combinational framework of coefficients scrambling with Key Scheduling Algorithm based (KSA-based) permutation. …”
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    Thesis
  16. 16

    Taguchi?s T-method with Normalization-Based Binary Bat Algorithm by Marlan Z.M., Jamaludin K.R., Harudin N.

    Published 2025
    “…Specifically, a normalization-based Binary Bat algorithm is used, where discretization of continuous solution into binary form is performed using a normalization equation. …”
    Conference paper
  17. 17

    The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer by Ahmad, Noor Ashikin

    Published 2015
    “…Four treatment plans are created and DVHs are evaluated based on criteria of acceptance level. NTCP values for thorax plan one and two are evaluated by using different algorithm. …”
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    Monograph
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    Enhancement processing time and accuracy training via significant parameters in the batch BP algorithm by Fatma Susilawati, Mohamad, Mumtazimah, Mohamad, Sarhan, AlDuais

    Published 2020
    “…We created the dynamic learning rate and dynamic momentum factor for increasing the efficiency of the algorithm. …”
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    Article
  20. 20

    Towards the utilization of normalized LMS algorithm in adaptive filter by Misbah Emhammed, Misbah Abdelsalam, Ho, Yih Hwa

    Published 2014
    “…The analysis was mainly concentrated on the adapted algorithms’ performance. This study provides the insights necessary for considering other filtering mechanisms based on the normalized least mean square.…”
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    Article