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Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

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Exploring Bayesian model averaging with multiple ANNs for meteorological drought forecasts by Achite M., Banadkooki F.B., Ehteram M., Bouharira A., Ahmed A.N., Elshafie A.

Improved bacterial foraging optimization algorithm with machine learning-driven short-term electricity load forecasting: a case study in peninsular Malaysia by Zaini, Farah Anishah, Sulaima, Mohamad Fani, Wan Abdul Razak, Intan Azmira, Othman, Mohammad Lutfi, Mokhlis, Hazlie

“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short-term daily electricity load in Peninsular Malaysia. …”
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Improved bacterial foraging optimization algorithm with machine learning driven short term electricity load forecasting: A case study in Peninsular Malaysia by Sulaima, Mohamad Fani, Zaini, Farah Anishah, Wan Abdul Razak, Intan Azmira, Othman, Mohammad Lutfi, Mokhlis, Hazlie

“…Thus, these parameters of LSSVM need to be chosen appropriately using intelligent optimization algorithms. This study proposes a new hybrid model based on the LSSVM optimized by the improved bacterial foraging optimization algorithm (IBFOA) for forecasting the short‑term daily electricity load in Peninsular Malaysia. …”
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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

“…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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Hybridization of Ensemble Kalman Filter and Non-linear Auto-regressive Neural Network for Financial Forecasting by Lai, Fong Woon

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

“…Weakness such as trapped in local minima, slow convergence and finding a good rate between exploitation and exploration of the search space. This research proposed a swarm intelligence training algorithm, Improved African Buffalo Optimization algorithm (IABO) based on the Metaheuristic method called the African Buffalo Optimization algorithm (ABO). …”
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Exploration of machine learning forecasting methods in M4 competition / Muhammad Halim Hamdan and Shuzlina Abdul-Rahman by Hamdan, Muhammad Halim, Abdul-Rahman, Shuzlina

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Hybridization of Ensemble Kalman Filter and Non-linear Auto-regressive Neural Network for Financial Forecasting by Said , Jadid Abdulkadir, Suet Peng, Yong, Maran , Marimuthu, Lai, Fong Woon

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Hybridization of Ensemble Kalman Filter and Non-linear Auto-regressive Neural Network for Financial Forecasting by Said, Jadid Abdulkadir, Yong, S.P., Maran, Marimuthu, Lai, Fong Woon

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Mapreduce algorithm for weather dataset by Khalid Adam, Ismail Hammad

“…Results from the proposed algorithm have been compared with the existing model known as AWK (Alfred Aho, Peter Weinberger, and Brian Kernighan) model. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…Furthermore, EEC in ASEAN-5 countries is forecasted by autoregressive integrated moving average (ARIMA) model and first-order single-variable grey model (GM (1, 1)) and their forecasts are compared with those obtained by the proposed method.…”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

“…The main challenge in this area is providing highly accurate and efficient day-ahead price forecasting. A suitable feature selection technique, which is able to model the interacting features and nonlinearities of the forecast processes, is still required although researches have been performed for day-ahead forecasting. …”
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Application of artificial intelligence algorithms for hourly river level forecast: a case study of Muda River, Malaysia by Zakaria, Muhamad Nur Adli, Abdul Malek, Marlinda, Zolkepli, Maslina, Ahmed, Ali Najah

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MapReduce algorithm for weather dataset by Majid, Mazlina A., Romli, Awanis, Ahmad, Noraziah, Hammad, Khalid Adam Ismail

“…Results from the proposed algorithm have been compared with the existing model known as AWK (Alfred Aho, Peter Weinberger, and Brian Kernighan) model. …”
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Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq by Yaseen, Z.M., Jaafar, O., Deo, R.C., Kisi, O., Adamowski, J., Quilty, J., El-Shafie, A.

“…Based on the findings of this study, several recommendations were suggested for further exploration of the ELM model in hydrological forecasting problems.…”
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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.

“…These findings underscore the importance of algorithm selection in optimizing predictive models for energy consumption forecasting. …”

A review of the hybrid artificial intelligence and optimization modelling of hydrological streamflow forecasting by Ibrahim K.S.M.H., Huang Y.F., Ahmed A.N., Koo C.H., El-Shafie A.

A review on high frequency trading forecasting methods: opportunity and challenges for quantum based method by Palaniappan, Visalakshi, Ishak, Iskandar, Ibrahim, Hamidah, Sidi, Fatimah, Ahmad Zukarnain, Zuriati

“…The exploration and use of quantum computing for HFT forecasting marks a significant stride toward overcoming current limitations.…”
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Application of augmented bat algorithm with artificial neural network in forecasting river inflow of hydroelectric reservoir stations in Malaysia by Joe Wee Wei, Mr.

“…Both standalone and hybrid models were developed to identify the most optimum parameter to be used for river SF forecasting. …”