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  1. 1
    Development Of Machine Learning User Interface For Pump Diagnostics

    Development Of Machine Learning User Interface For Pump Diagnostics by Lee, Zhao Yang

    Published 2022
    “…Build up a user interface by using Visual Studio Code (VSC) to run the coding of Cascading Style Sheet (CSS), Hyper Text Markup Language (HTML) and JavaScript (JS) as a webpage and connect to Azure Machine Learning Model and this will allow the user from using the model from a webpage when they have active internet with any devices.…”
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  2. 2
    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform

    Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform by Alias, Norma, Satam, Noriza, Abd. Ghaffar, Zarith Safiza, Darwis, Roziha, Hamzah, Norhafiza, Islam, Md. Rajibul

    Published 2009
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  3. 3
    Automated time series forecasting

    Automated time series forecasting by Ismail, Suzilah, Zakaria, Rohaiza, Tuan Muda, Tuan Zalizam

    Published 2011
    “…Moving Average, Decomposition, Exponential Smoothing, Time Series Regressions and ARIMA) were used.The algorithm was developed in JAVA using up to date forecasting process such as data partition, several error measures and rolling process.Successfully, the results of the algorithm tally with the results of SPSS and Excel.This automatic forecasting will not just benefit forecaster but also end users who do not have in depth knowledge about forecasting techniques.…”
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  4. 4
    Neural Networks Ensemble: Evaluation of Aggregation Algorithms for Forecasting

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

    Published 2013
    “…The aggregation algorithms were employed on the forecasts obtained from all individual NN models as well as on a number of the best forecasts obtained from the best NN models. …”
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  5. 5
    Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach

    Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem

    Published 2019
    “…Through the combination of backtracking search algorithm (BSA) in learning process of ANFIS approach, a hybrid machine learning algorithm has been developed to forecast the electricity price more accurately. …”
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  6. 6
    Input attributes optimization using the feasibility of genetic nature inspired algorithm: Application of river flow forecasting

    Input attributes optimization using the feasibility of genetic nature inspired algorithm: Application of river flow forecasting by Afan H.A., Allawi M.F., El-Shafie A., Yaseen Z.M., Ahmed A.N., Malek M.A., Koting S.B., Salih S.Q., Mohtar W.H.M.W., Lai S.H., Sefelnasr A., Sherif M., El-Shafie A.

    Published 2023
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  7. 7
    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO)

    Water level forecasting using feed forward neural networks optimized by African Buffalo Algorithm (ABO) by Ahmed, Ehab Ali

    Published 2019
    “…The results demonstrated the superiority of the IABO-trained algorithm in avoiding local minima, convergence speed, and accuracy compared to the benchmarking (BP and PSO) algorithms in water level forecasting tasks.…”
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  8. 8
    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589)

    M-Factors Fuzzy Time Series for Forecasting Moving Holiday Electricity Load Demand in Malaysia (S/O 14589) by Mansor, Rosnalini, Mat Kasim, Maznah, Othman, Mahmod, Zaini, Bahtiar Jamili

    “…Hence, the WeSuSFTS algorithm succeeds to improve the MH-ELD forecasting accuracy.…”
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  9. 9
    Box-jenkins and genetic algorithm hybrid model for electricity forecasting system

    Box-jenkins and genetic algorithm hybrid model for electricity forecasting system by Mahpol, Khairil Asmani

    Published 2005
    “…The investigation is simulated using Intelligent Electricity Forecasting System (IEFS) developed in this research which written in Borland Delphi 7.0 programming.…”
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  10. 10
    Adaptive Fast Orthogonal Search (FOS) algorithm for forecasting streamflow

    Adaptive Fast Orthogonal Search (FOS) algorithm for forecasting streamflow by Osman A., Afan H.A., Allawi M.F., Jaafar O., Noureldin A., Hamzah F.M., Ahmed A.N., El-shafie A.

    Published 2023
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  11. 11
    Hybrid optimization approach to estimate random demand

    Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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  12. 12
    A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm

    A new approach for forecasting OPEC petroleum consumption based on neural network train by using flower pollination algorithm by Haruna, Chiroma, Khan, Abdullah, Abubakar, Adamu, Saudi, Younes, Hamza, Mukhtar Fatihu, Shuiba, Liyana, Gital, Abdulsalam, Herawan, Tutut

    Published 2016
    “…Many meta-heuristic algorithms have been proposed in literature for the optimization of Neural Network (NN) to build a forecasting model. …”
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  13. 13
    Multi-horizon ternary time series forecasting

    Multi-horizon ternary time series forecasting by Htike@Muhammad Yusof, Zaw Zaw

    Published 2013
    “…This is mainly because state-of-the-art forecasting algorithms essentially perform single-horizon forecasts and produce continuous numbers as outputs. …”
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  14. 14
    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…Given the multitude of components to manage, streamflow forecasting is preferable to employ an algorithm with low sensitivity to parameter variations. …”
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  15. 15
    Development of hybrid algorithm of residual bootstrap artificial neural network based on sukuk volatility forecast model.

    Development of hybrid algorithm of residual bootstrap artificial neural network based on sukuk volatility forecast model. by Nurul Hila Zainuddin

    Published 2018
    “…Development of hybrid algorithm of residual bootstrap artificial neural network based on sukuk volatility forecast model. by Nurul Hila Zainuddin…”
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  16. 16
    Improving artificial intelligence models accuracy for monthly streamflow forecasting using grey Wolf optimization (GWO) algorithm

    Improving artificial intelligence models accuracy for monthly streamflow forecasting using grey Wolf optimization (GWO) algorithm by Tikhamarine Y., Souag-Gamane D., Najah Ahmed A., Kisi O., El-Shafie A.

    Published 2023
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  17. 17
    Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting

    Weighted subsethood and reasoning based fuzzy time series for moving holiday electricity load demand forecasting by Rosnalini, Mansor

    Published 2021
    “…Besides, different characteristics of each moving holiday and existence of a great number of irregularities in the load data also contribute to the forecasting inaccuracy and uncertainty. Fuzzy time series (FTS) algorithm is able to overcome moving holiday electricity load demand (MH-ELD) forecasting problem, but the FTS algorithm lacks final model interpretation, less interpretability of fuzzy logical relationship strength, and does not provide a complete FTS forecasting process. …”
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  18. 18
    Long term energy demand forecasting based on hybrid, optimization: Comparative study

    Long term energy demand forecasting based on hybrid, optimization: Comparative study by Musa, Wahab, Ku-Mahamud, Ku Ruhana, Yasin, Azman

    Published 2012
    “…The objective of this research is to develop a long term energy demand forecasting model that used hybrid optimization.To accomplish this goal, a hybrid algorithm that combined a genetic algorithm and a local search algorithm method has been developed to overcome premature convergence.Model performances of hybrid algorithm were compared with former single algorithm model in estimating parameter values of an objective function to measure the goodness-of-fit between the observed data and simulated results.Averages error between two models was adopt to select the proper model for future projection of energy demand.…”
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  19. 19
    A systematic literature review of deep learning neural network for time series air quality forecasting

    A systematic literature review of deep learning neural network for time series air quality forecasting by Zaini N., Ean L.W., Ahmed A.N., Malek M.A.

    Published 2023
    “…air quality; algorithm; artificial neural network; industrial development; literature review; machine learning; public health; time series; urbanization; air pollution; forecasting; human; time factor; Air Pollution; Deep Learning; Forecasting; Humans; Neural Networks, Computer; Time Factors…”
    Review
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  20. 20
    Balanced Stochastic Realization Algorithm For Development Of Rainfall Model

    Balanced Stochastic Realization Algorithm For Development Of Rainfall Model by Azhari, Fahimy

    Published 2014
    “…In this research, Balanced Stochastic Realization (BSR) subspace algorithm is used to develop a rainfall model for Malaysia. …”
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