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  1. 1
    Design & Development of a Robotic System Using LEGO Mindstorm

    Design & Development of a Robotic System Using LEGO Mindstorm by Abd Manap, Nurulfajar, Md Salim, Sani Irwan, Haron, Nor Zaidi

    Published 2006
    “…Since the model is built using LEGO bricks, the model is fully customized, in term of its applications, to perform any relevant tasks. …”
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  2. 2
    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition

    Dynamic Bayesian networks and variable length genetic algorithm for designing cue-based model for dialogue act recognition by Yahya, Anwar Ali, Mahmod, Ramlan, Ramli, Abd Rahman

    Published 2010
    “…In the second stage, the developed variable length genetic algorithm is used to select different sets of lexical cues to constitute the dynamic Bayesian networks' random variables. …”
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  3. 3
    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.

    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

    Published 2020
    “…We develop an active-set based block coordinate descent algorithm (BCD) to optimize exactly the group LASSO. …”
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    UMK Etheses
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  4. 4
    SURE-Autometrics algorithm for model selection in multiple equations

    SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

    Published 2016
    “…Thus, this study aims to develop an algorithm for model selection in multiple equations focusing on seemingly unrelated regression equations (SURE) model. …”
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  5. 5
    Classification model for hotspot occurrences using spatial decision tree algorithm

    Classification model for hotspot occurrences using spatial decision tree algorithm by Sitanggang, Imas Sukaesih, Yaakob, Razali, Mustapha, Norwati, Nuruddin, Ahmad Ainuddin

    Published 2013
    “…The algorithm results a predictive model for hotspots occurrence from the real dataset on forest fires with high accuracy on the training set.…”
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  6. 6
    A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption

    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
    “…The research starts with developing the hybrid deep learning model consisting of DNN and a K-Means Clustering Algorithm. …”
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  7. 7
    New Learning Models for Generating Classification Rules Based on Rough Set Approach

    New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

    Published 2000
    “…Recently, different models were used to generate knowledge from vague and uncertain data sets such as induction decision tree, neural network, fuzzy logic, genetic algorithm, rough set theory, and others. …”
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  8. 8
    Modeling of static and dynamic components of bio-nanorobotic systems

    Modeling of static and dynamic components of bio-nanorobotic systems by Gavgani, Hamidreza Khataee

    Published 2012
    “…The first modeling technique applies graph algorithms to compute a new set of optimal weighted structural properties of C60 and C70 fullerenes. …”
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  9. 9
    Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting

    Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting by HASSAN, SAIMA

    Published 2013
    “…It can be concluded from the results that the aggregation algorithms of NNs ensemble can improve the accuracy of forecast than the individual NN models with a test data set. …”
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  10. 10
    Predicting streamflow in Peninsular Malaysia using support vector machine and deep learning algorithms

    Predicting streamflow in Peninsular Malaysia using support vector machine and deep learning algorithms by Essam Y., Huang Y.F., Ng J.L., Birima A.H., Ahmed A.N., El-Shafie A.

    Published 2023
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  11. 11
    Neural network based model predictive control for a steel pickling process

    Neural network based model predictive control for a steel pickling process by Kittisupakorn, P., Thitiyasook, P., Hussain, Mohd Azlan, Daosud, W.

    Published 2009
    “…The baths exhibit the normal features of an industrial system such as nonlinear dynamics and multi-effects among variables. In the modeling, multiple input, single-output recurrent neural network subsystem models are developed using input-output data sets obtaining from mathematical model simulation. …”
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  12. 12
    Development of genetic algorithm-based fuzzy rules design for metal cutting data selection

    Development of genetic algorithm-based fuzzy rules design for metal cutting data selection by Wong, S.V, Hamouda, A.M.S

    Published 2002
    “…The authors have developed fuzzy models for machinability data selection (Int. …”
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  13. 13
    Academic leadership bio-inspired classification model using negative selection algorithm

    Academic leadership bio-inspired classification model using negative selection algorithm by Jantan, Hamidah, Sa’dan, Siti ‘Aisyah, Che Azemi, Nur Hamizah Syafiqah

    Published 2015
    “…Managing employee’s competency is considered as the top challenge for human resource professional especially in the process to determine the right person for the right job that is based on their competency.As an alternative approach, this article attempts to propose academic leadership bio-inspired classification model using negative selection algorithm to handle this issue.This study consists of three phases; data preparation, model development and model analysis. …”
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  14. 14
    Experimenting the dendrite cell algorithm for disease outbreak detection model

    Experimenting the dendrite cell algorithm for disease outbreak detection model by Mohamad Mohsin, Mohamad Farhan, Hamdan, Abdul Razak, Abu Bakar, Azuraliza

    Published 2014
    “…The characteristics of early outbreak signal which are weak and behaved under uncertainties has brought to the development of outbreak detection model based on dendrite cell algorithm.Although the algorithm is proven can improve detection performance, it relies on several parameters which need to be defined before mining.In this study, the most appropriate parameter setting for outbreak detection using dendrite cell algorithm is examined.The experiment includes four parameters; the number of cell cycle update, the number of dendrite cell allowed to be in population, weight, and migration threshold value. …”
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  15. 15
    Predicting bankruptcy using ant colony optimization / Nur Syafiqah Abdul Ghani

    Predicting bankruptcy using ant colony optimization / Nur Syafiqah Abdul Ghani by Abdul Ghani, Nur Syafiqah

    Published 2021
    “…This study focussed on Industrial Risk, Financial Flexibility, Credibility, Management Risk, Operating Risk, and Competitiveness. To achieve the set objectives, this research is conducted through three-phase of research activities which are Data pre-processing, Model Development, and Model Validation. …”
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  16. 16
    Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.]

    Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.] by Mohd, Thuraiya, Jamil, Syafiqah, Masrom, Suraya, Ab Rahim, Norbaya

    Published 2021
    “…In addition, time and expertise are important factors needed to adapt the model to a specific problem such as green building housing development. …”
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  17. 17
    Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem

    Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem by Nurdiyana, Jamil

    Published 2022
    “…Firstly, the modified SCA (MSCA) model with cost-based local search strategy is developed. …”
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  18. 18
    Parametric system identification and active vibration control of vibrational structures using genetic algorithm

    Parametric system identification and active vibration control of vibrational structures using genetic algorithm by Mohammad Sofi @ Aziz, Azfi Zaihan

    Published 2007
    “…The sets of data obtained were utilised to develop ARX model using Least Squares (LS), Recursive Least Squares (RLS) and Genetic Algorithm (GA) methods. …”
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  19. 19
    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition

    A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

    Published 2002
    “…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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  20. 20
    Prediction of blood-brain barrier permeability of compounds by machine learning algorithms

    Prediction of blood-brain barrier permeability of compounds by machine learning algorithms by Feng, Tan wei, Raihana Zahirah, Edros, Ngahzaifa, Ab Ghani, Siti Umairah, Mokhtar, Dong, Ruihai

    Published 2024
    “…In this work, using the KNIME Analytics platform, 4 predictive models were developed with 4 ML algorithms followed by a ten-fold cross-validation approach to predict the external validation set. …”
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