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  1. 1
    Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting

    Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

    Published 2013
    “…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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  2. 2
    Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting

    Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

    Published 2013
    “…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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  3. 3
    Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting

    Neural network ensemble: Evaluation of aggregation algorithms in electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

    Published 2013
    “…The predictive performance of these algorithms are evaluated using Australian electricity demand data. …”
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  4. 4
    Multistep forecasting for highly volatile data using new algorithm of Box-Jenkins and GARCH

    Multistep forecasting for highly volatile data using new algorithm of Box-Jenkins and GARCH by Siti Roslindar, Yaziz, Roslinazairimah, Zakaria

    Published 2018
    “…In order to achieve the objective, the algorithm of multistep ahead forecast for BJ-G model is proposed using R language. …”
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  5. 5
    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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  6. 6
    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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  7. 7
    A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting

    A Systematic Literature Review of Machine Learning Methods for Short-term Electricity Forecasting by Md Salleh N.S., Suliman A., Jorgensen B.N.

    Published 2023
    Conference Paper
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  8. 8
    A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting

    A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting by Mohammed, Athraa Jasim, Ghathwan, Khalil Ibrahim, Yusof, Yuhanis

    Published 2020
    “…Following the success, this study has integrated the two algorithms to better optimize the LSSVM. The newly proposed forecasting algorithm, termed as CUCKOO-BAT-LSSVM, produces better forecasting in terms of MAPE, accuracy and RMSPE. …”
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  9. 9
    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, Yazid, Souag-Gamane, Doudja, Najah Ahmed, Ali, Kisi, Ozgur, El-Shafie, Ahmed

    Published 2020
    “…Therefore, the chief aim of this study is to propose efficient hybrid system by integrating Grey Wolf Optimization (GWO) algorithm with Artificial Intelligence (AI) models. 130 years of monthly historical natural streamflow data will be used to evaluate the performance of the proposed modelling technique. …”
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  10. 10
    Electricity demand forecasting in Turkey and Indonesia using linear and nonlinear models based on real-value genetic algorithm and extended Nelder-Mead local search

    Electricity demand forecasting in Turkey and Indonesia using linear and nonlinear models based on real-value genetic algorithm and extended Nelder-Mead local search by Wahab, Musa

    Published 2014
    “…The second problem is the use of a single algorithm that failed to solve local optima. …”
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  11. 11
    Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market

    Analytical Study Of Machine Learning Models For Stock Trading In Malaysian Market by Hazirah Halul

    Published 2024
    “…Comparative analysis of evaluation indicators for all trading algorithms has been assessed and discussed. …”
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  12. 12
    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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  13. 13
    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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  14. 14
    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
    “…The WeSuSFTS algorithm uses the min-max operator for fuzzy reasoning and average rule defuzzification which make the process simpler. …”
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  15. 15
    Algorithmic approaches in model selection of the air passengers flows data

    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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  16. 16
    An enhanced support vector regression -African Buffalo optimisation algorithm for electricity time series forecasting

    An enhanced support vector regression -African Buffalo optimisation algorithm for electricity time series forecasting by Maijama'a, Inusa Sani

    Published 2023
    “…Combining the enhanced algorithms results in SVR-eABO, whose forecasting ability has been assessed using MAE, MAPE, RMSE, PA and R2. …”
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  17. 17
    Group method of data handling with artificial bee colony in combining forecasts

    Group method of data handling with artificial bee colony in combining forecasts by Yahya, Nurhaziyatul Adawiyah, Samsudin, Ruhaidah, Darmawan, Irfan, Kasim, Shahreen

    Published 2018
    “…In this study, the use of Artificial Bee Colony (ABC) algorithm to combine several time series forecasts is presented. …”
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  18. 18
    Weather prediction system using ANN algorithm / Nur Afiqah Ahmad Sukri

    Weather prediction system using ANN algorithm / Nur Afiqah Ahmad Sukri by Ahmad Sukri, Nur Afiqah

    Published 2024
    “…The objective of the project is to develop a weather prediction system using artificial neural network (ANN) algorithms and to evaluate its performance and accuracy. …”
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  19. 19
    Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector

    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. …”
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  20. 20
    Air pollution forecasting in Kuala Terengganu using Artificial Neural Network (ANN) / Nur Raudzah Abdullah

    Air pollution forecasting in Kuala Terengganu using Artificial Neural Network (ANN) / Nur Raudzah Abdullah by Abdullah, Nur Raudzah

    Published 2020
    “…Existing researches on air pollution forecasting used a variety of machine learning algorithm. …”
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