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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.

Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei by Alireza , Pourdaryaei

“…The other foremost contribution of the work is proposing a hybrid electricity price forecasting technique to provide more accurate forecasts. …”
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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

“…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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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.

“…The results of the evaluation demonstrated varying performances among the three evolutionary algorithms. …”

Analysis of short term load forecasting techniques / Tan Vy Luoh by Tan, Vy Luoh

“…The algorithms for each respective techniques are modelled in MATLAB Toolbox for simulation purpose. …”
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Artificial neural network technique for modeling of groundwater level in Langat Basin, Malaysia by Mahmoud Khaki, Ismail Yusoff, Nur Islami, Nur Hayati Hussin

“…The results indicated that the ANN technique was well suited for forecasting groundwater levels. …”
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A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings by Raza, M.Q., Khosravi, A.

“…This paper provides the comprehensive and systematic literature review of Artificial Intelligence based short term load forecasting techniques. The major objective of this study is to review, identify, evaluate and analyze the performance of Artificial Intelligence (AI) based load forecast models and research gaps. …”
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Sediment load forecasting from a biomimetic optimization perspective: Firefly and Artificial Bee Colony algorithms empowered neural network modeling in �oruh River by Katipo?lu O.M., Kartal V., Pande C.B.

“…This study combined models such as the artificial neural network (ANN) algorithm with the Firefly algorithm (FA) and Artificial Bee Colony (ABC) optimization techniques for the estimation of monthly SL values in the �oruh River in Northeastern Turkey. …”

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

“…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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RSA Encryption & Decryption using JAVA by Ramli, Marliyana

“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Short-term PV power forecasting using hybrid GASVM technique by VanDeventer, William, Jamei, Elmira, Thirunavukkarasu, Gokul Sidarth, Seyedmahmoudian, Mehdi, Tey, Kok Soon, Horan, Ben, Mekhilef, Saad, Stojcevski, Alex

“…The forecasting accuracy of the proposed GASVM model is evaluated based on the root mean square error (RMSE) and mean absolute percentage error (MAPE). …”
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Air pollution forecasting in Kuala Terengganu using Artificial Neural Network (ANN) / Nur Raudzah Abdullah by Abdullah, Nur Raudzah

“…Existing researches on air pollution forecasting used a variety of machine learning algorithm. …”
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Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

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A New Optimization Technique Of Support Vector Machine For Electricity Market Price Forecasting by Wan Abdul Razak, Intan Azmira, Zainal Abidin, Izham, Yap, Keem Siah, Sulaima, Mohamad Fani, Hassan, Elia Erwani, Gan, Chin Kim

“…MATLAB will be used to simulate the performance of BFOA and evaluate the accuracy of LSSVM forecasting. BFOA has shown good performances in various field but it has yet to be attempted in electricity price forecasting. …”
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Provider independent cryptographic tools by Ibrahim, Subariah, Salleh, Mazleena, Abdul Aziz, Shah Rizan

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Application of augmented bat algorithm with artificial neural network in forecasting river inflow in Malaysia by Wee W.J., Chong K.L., Ahmed A.N., Malek M.B.A., Huang Y.F., Sherif M., Elshafie A.

“…Only a few simulation systems, where previous techniques failed to anticipate SF data quickly, let alone cost-effectively, and took a long time to execute. …”

Enhanced foreign exchange volatility forecasting using CEEMDAN with optuna-optimized ensemble deep learning model by Kausar, Rehan, Iqbal, Farhat, Raziq, Abdul, Sheikh, Naveed, Rehman, Abdul

“…In addition, we employed an attention mechanism to improve the effectiveness of the DL techniques. Furthermore, the hyperparameters for the DL models are optimized using the Optuna algorithm. …”
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Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem, Ang, Swee Peng

“…Therefore, this research proposes a hybrid method for electricity price forecasting via artificial neural network (ANN) and artificial cooperative search algorithm (ACS). …”
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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

“…In addition, the confidence level was built using the percentile-t-method (or bootstrap-t-method). The proposed technique was then tested on a dataset obtained from the same hydrological stations used when the forecasting modeling. …”
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Deep learning in public health: Comparative predictive models for COVID-19 case forecasting by Muhammad Usman Tariq, Muhammad Usman Tariq, Ismail, Shuhaida

“…To enhance the performance of these models, Bayesian optimization techniques were employed. Subsequently, the models were re-evaluated to compare their effectiveness. …”
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