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  1. 1

    Weighted subsethood segmented fuzzy time series for moving holiday electricity load demand forecasting by Mansor, R., Kasim, M.M., Othman, M.

    Published 2020
    “…The modified algorithm, Weighted Subsethood Segmented Fuzzy Time Series (WeSuSFTS) consists of three main phases; data pre-processing, forecasting based on WeSuSFTS model and model evaluation. …”
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    Article
  2. 2

    The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction by Marlan Z.M., Ramlie F., Jamaludin K.R., Harudin N.

    Published 2023
    “…Taguchi�s T-method is a predictive modeling technique under the Mahalanobis-Taguchi system that is based on the regression principle and robust quality engineering elements to predict future state or unknown outcomes. …”
    Article
  3. 3

    Taguchi's T-method with nearest integer-based binary bat algorithm for prediction by Marlan Z.M., Jamaludin K.R., Ramlie F., Harudin N.

    Published 2023
    “…In this paper, a swarm-based binary bat optimization algorithm with a nearest integer discretization approach is integrated with the Taguchi�s T-method. …”
    Article
  4. 4

    Machine learning application to industrial control systems by Bingi, K., Prusty, B.R., Ibrahim, R.

    Published 2022
    “…The performance evaluation of the proposed modeling will be done on R2 and mean square errors. …”
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    Book
  5. 5

    Semantic-Based, Scalable, Decentralized and Dynamic Resource Discovery for Internet-Based Distributed System by Hassan, Mahamat. I, Azween, Abdullah

    Published 2010
    “…In short, our main contributions are outlined new key taxonomy for the semantic-based grid RD studies; an interoperable semantic description RD component model for intergrid services metadata representation; a semantic distributed registry architecture for indexing service metadata; and an agent-based service search and selection algorithm. …”
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    Thesis
  6. 6

    Semantic-Based, Scalable, Decentralized and Dynamic Resource Discovery for Internet-Based Distributed System by HASSAN, MAHAMAT ISSA

    Published 2010
    “…In particular, we classify such systems based on their qualitative use of the semantic information. …”
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    Thesis
  7. 7

    Modeling and Analysis of New Hybrid Clustering Technique for Vehicular Ad Hoc Network by Abdulrazzak H.N., Hock G.C., Mohamed Radzi N.A., Tan N.M.L., Kwong C.F.

    Published 2023
    “…The evaluation process was implemented on RK-Means, K-Means++, and OK-Means models. …”
    Article
  8. 8

    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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    Thesis
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    Optimizing energy and reserve minimization in a sustainable microgrid with electric vehicle integration: dynamic and adjustable manta ray foraging algorithm by Abed, Adnan Ajam, Suwaed, Mahmood Sh., Al-Rubaye, Ameer H., Awad, Omar I., Mohammed, M.N, Hai, Tao, Kadirgama, Kumaran, Karah Bash, Ali A. H.

    Published 2023
    “…The results showcase significant improvements in energy and reserve minimization, highlighting the potential advantages of integrating EVs into sustainable microgrid systems. …”
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    Article
  11. 11

    Evaluation of MLP-ANN Training Algorithms for Modeling Soil Pore-Water Pressure Responses to Rainfall by Mustafa, M.R., Rezaur, R.B., Saiedi, Saied, Rahardjo, H., Isa, M.H.

    Published 2013
    “…The performance of the training algorithms was evaluated using standard performance evaluation measures—root mean square error, coefficient of efficiency, and the time and number of epochs required to reach a predefined accuracy. …”
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    Citation Index Journal
  12. 12

    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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    Thesis
  13. 13

    Algorithmic approaches in model selection of the air passengers flows data by Ismail, Suzilah, Yusof, Norhayati, Tuan Muda, Tuan Zalizam

    Published 2015
    “…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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    Conference or Workshop Item
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    A static jobs scheduling for independent jobs in Grid Environment by using Fuzzy C-Mean and Genetic algorithms by Lorpunmanee, Siriluck, Md. Sap, Mohd. Noor, Abdullah, Abdul Hanan, Srinoy, Surat

    Published 2006
    “…We present a static job scheduling algorithm by using Fuzzy C-Mean and Genetic algorithms. …”
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    Conference or Workshop Item
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    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…The system will automatically check for the nearest vacant bay and reserve it for the current user allowing a different bay reservation for the next user. …”
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    Thesis
  18. 18

    Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector by Wang G., Mukhtar A., Moayedi H., Khalilpoor N., Tt Q.

    Published 2025
    “…The results of the evaluation demonstrated varying performances among the three evolutionary algorithms. …”
    Article
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    Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

    Published 2013
    “…These algorithms include equal-weights combination of Best NN models, combination of trimmed forecasts, and Bayesian Model Averaging (BMA). …”
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    Conference or Workshop Item