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  1. 1
    The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach

    The Determination of Pile Capacity Using Artificial Neural-net: An Optimization Approach by Ab. Malik, Rosely, Jamil S., Mohamed

    Published 2001
    “…Using the developed algorithm, the safety measures involved are such as reliability index and the probability of failure; instead of only factor of safety if conventional deterministic approach is used. …”
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  2. 2
    Modified artificial neural network (ANN) models for Malaysian construction costs indices (MCCI) data / Saadi Ahmad Kamaruddin

    Modified artificial neural network (ANN) models for Malaysian construction costs indices (MCCI) data / Saadi Ahmad Kamaruddin by Ahmad Kamaruddin, Saadi

    Published 2018
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  3. 3
    Ant system-based feature set partitioning algorithm for classifier ensemble construction

    Ant system-based feature set partitioning algorithm for classifier ensemble construction by Abdullah, , Ku-Mahamud, Ku Ruhana

    Published 2016
    “…In this study, Ant system-based feature set partitioning algorithm for classifier ensemble construction is proposed.The Ant System Algorithm is used to form an optimal feature set partition of the original training set which represents the number of classifiers.Experiments were carried out to construct several homogeneous classifier ensembles using nearest mean classifier, naive Bayes classifier, k-nearest neighbor and linear discriminant analysis as base classifier and majority voting technique as combiner. …”
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  4. 4
    Clustering of rainfall data using k-means algorithm

    Clustering of rainfall data using k-means algorithm by Mohd Sham, Mohamad, Yuhani, Yusof, Ku Muhammad Na’im, Ku Khalif, Mohd Khairul Bazli, Mohd Aziz

    Published 2019
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  5. 5
    Clustering Approach In Wireless Sensor Networks Based On K-Means: Limitations And Recommendations

    Clustering Approach In Wireless Sensor Networks Based On K-Means: Limitations And Recommendations by Hassan, Ali Abdul-hussian, Md Shah, Wahidah, Husien, Ali Mohamed, Talib, Mohammed Saad, Mohammed, Ali Abdul Jabbar, Othman, Mohd Fairuz Iskandar

    Published 2019
    “…One of most popular cluster algorithms that utilizing into organize sensor nodes is K-means algorithm. …”
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  6. 6
    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly

    Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

    Published 2019
    “…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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  7. 7
    An optimal approximation algorithm for optimization of un-weighted minimum vertex cover problem

    An optimal approximation algorithm for optimization of un-weighted minimum vertex cover problem by Fayaz, Muhammad, Arshad, S, Shah, Abdul Salam, Shah, Asadullah

    Published 2016
    “…Mean of Neighbors of Minimum Degree Algorithm (MNMA) is proposed in this paper. …”
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  8. 8
    Modified artificial neural network (ANN) models for Malaysian construction costs indices (MCCI) data / Saadi Ahmad Kamaruddin

    Modified artificial neural network (ANN) models for Malaysian construction costs indices (MCCI) data / Saadi Ahmad Kamaruddin by Ahmad Kamaruddin, Saadi

    Published 2018
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  9. 9
    Adaptive filtering of EEG/ERP through bounded range artificial Bee Colony (BR-ABC) algorithm

    Adaptive filtering of EEG/ERP through bounded range artificial Bee Colony (BR-ABC) algorithm by Ahirwal, M.K., Kumar, A., Singh, G.K.

    Published 2014
    “…ANCs are also implemented with Least Mean Square (LMS) and Recursive Least Square (RLS) algorithm. …”
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  10. 10
    Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management

    Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

    Published 2024
    “…Evaluation metrics such as Mean Squared Error, Root Mean Squared Error, Mean Absolute Error, and R-squared are commonly employed in the assessment of Machine Learning models' performance. …”
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  11. 11
    An evolutionary based features construction methods for data summarization approach

    An evolutionary based features construction methods for data summarization approach by Rayner Alfred, Suraya Alias, Chin, Kim On

    Published 2015
    “…Here, feature construction methods are applied in order to improve the descriptive accuracy of the DARA algorithm.This research proposes novel feature construction methods, called Variable Length Feature Construction without Substitution (VLFCWOS) and Variable Length Feature Construction with Substitution(VLFCWS), in order to construct a set of relevant features in learning relational data. …”
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  12. 12
    Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm

    Characterization of water quality conditions in the Klang River Basin, Malaysia using self organizing map and K-means algorithm by Mohd Sharif, Sharifah, Mohd Kusin, Faradiella, Asha’ari, Zulfa Hanan, Aris, Ahmad Zaharin

    Published 2015
    “…The self organizing map (SOM) combined with the K-means algorithm arranged the data based on the relationships of 25 variables. …”
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  13. 13
    Development Of Construction Noise Prediction Method Using Deep Learning Model

    Development Of Construction Noise Prediction Method Using Deep Learning Model by Siew, Jun Teng

    Published 2021
    “…It will eventually become mainstream of the construction noise prediction method and will also be used in industries other than construction.…”
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  14. 14
    A rectification strategy in genetic algorithms for academic timetabling problem

    A rectification strategy in genetic algorithms for academic timetabling problem by Teoh, Chong Keat, Wibowo, Antoni, Ngadiman, Salihin

    Published 2015
    “…The feasible timetable is constructed by means of Genetic Algorithm, embedded with a rectification strategy which transforms infeasible timetables into feasible timetables.…”
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  15. 15
    A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction

    A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction by Hammid, Ali Thaeer, M. H., Sulaiman, Awad, Omar I.

    Published 2018
    “…The results display that the regression coefficient, root-mean-square error, mean absolute error, and mean bias error values of the suggested model are 99.86%, 1.87%, 0.91%, and 0.31%, respectively. …”
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  16. 16
    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach

    Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach by Nurnajmin Qasrina Ann, ., Pebrianti, Dwi, Mohamad Fadhil, Abas, Bayuaji, Luhur

    Published 2022
    “…After that, it has been suggested to improve the efficiencies in the Deep Neural Network (DNN) model by combining the DNN with an unsupervised machine learning algorithm, the K-Means clustering algorithm. This study constructs the flow of DNN based method with the K-Means algorithm. …”
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  17. 17
    Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting

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

    Published 2013
    “…The performances ofthese aggregation algorithms ofNNs ensemble were evaluated with the mean absolutepercentage error and symmetric mean absolute percentage error. …”
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  18. 18
    Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan

    Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan by Aznan, Muhammad Nur Syazwanie Aznan

    Published 2019
    “…Which is why this project objective is to develop a web based clustering tool using K-MEAN++ algorithm. This project will use the rapid application development (RAD) methodology since this are the most suitable method for developing the system. …”
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  19. 19
    A Modified Hybrid Fuzzy Controller for Real-Time Mobile Robot Navigation

    A Modified Hybrid Fuzzy Controller for Real-Time Mobile Robot Navigation by Hossen J., Sayeed S., Iqbal A.K.M.P.

    Published 2023
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  20. 20
    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems

    Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

    Published 2024
    “…(iii) It is a constructive-based meta-heuristic algorithm which means, the solution is incrementally constructed (step by step) until the complete solution is obtained (Noferesti and Shah-Hosseini, 2012). …”
    thesis::doctoral thesis
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