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

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

“…Furthermore, the hyperparameters for the DL models are optimized using the Optuna algorithm. Finally, a hybrid ensemble model for forecasting exchange rate volatility is developed by combining the predictions of three distinct DL models. …”
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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

“…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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A novel hybrid method of LSSVM-GA with multiple stage optimization for electricity price forecasting by Razak I.A.W.A., Abidin I.Z., Yap K.S., Abidin A.A.Z., Rahman T.K.A., Nasir M.N.M.

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

“…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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Empirical analysis of parallel-NARX recurrent network for long-term chaotic financial forecasting by Abdulkadir, S.J., Yong, S.-P.

“…The main aim of forecasters is to develop an approach that focuses on increasing profit by being able to forecast future stock prices based on current stock data. …”
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Investigating photovoltaic solar power output forecasting using machine learning algorithms by Essam Y., Ahmed A.N., Ramli R., Chau K.-W., Idris Ibrahim M.S., Sherif M., Sefelnasr A., El-Shafie A.

“…Solar power integration in electrical grids is complicated due to dependence on volatile weather conditions. To address this issue, continuous research and development is required to determine the best machine learning (ML) algorithm for PV solar power output forecasting. …”

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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An optimization method of genetic algorithm for lssvm in medium term electricity price forecasting by Abdul Razak I.A.W., Abidin I.Z., Siah Y.K., Abidin A.A.Z., Rahman T.K.A., Baharin N., Jali H.B.

“…Therefore, an optimisation technique of Genetic Algorithm (GA) for Least Square Support Vector Machine (LSSVM) was developed in this study to provide an accurate electricity price forecast with optimised LSSVM parameters and input features. …”

A hybrid method of least square support vector machine and bacterial foraging optimization algorithm for medium term electricity price forecasting by Razak I.A.W.A., Ibrahim N.N.A.N., Abidin I.Z., Siah Y.K., Abidin A.A.Z., Rahman T.K.A.

“…Therefore, an optimization technique of Bacterial Foraging Optimization Algorithm (BFOA) for Least Square Support Vector Machine (LSSVM) was developed in this study to provide an accurate electricity price forecast with optimized LSSVM parameters and input features. …”

Forecasting Malaysian gold price using random forest / Muhammad Nur Firmanrulah Samsudin by Samsudin, Muhammad Nur Firmanrulah

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Short term electricity price forecasting with multistage optimization technique of LSSVM-GA by Razak I.A.W.A., Abidin I.Z., Siah Y.K., Abidin A.A.Z., Rahman T.K.A.

“…The developed LSSVM-GA shows higher forecast accuracy with lower complexity than the existing models.…”

Short Term Electricity Price Forecasting With Multistage Optimization Technique Of LSSVM-GA by Wan Abdul Razak, Intan Azmira, Zainal Abidin, Izham, Keem Siah, Yap, Zainul Abidin, Aidil Azwin, Abdul Rahman, Titik Khawa

“…Price prediction has now become an important task in the operation of electrical power system.In short term forecast,electricity price can be predicted for an hour-ahead or day-ahead.An hour-ahead prediction offers the market members with the pre-dispatch prices for the next hour.It is useful for an effective bidding strategy where the quantity of bids can be revised or changed prior to the dispatch hour.However,only a few studies have been conducted in the field of hour-ahead forecasting.This is due to most of the power markets apply two-settlement market structure (day-ahead and real time) or standard market design rather than singlesettlement system (real time).Therefore,a multistage optimization for hybrid Least Square Support Vector Machine (LSSVM) and Genetic Algorithm (GA) model is developed in this study to provide an accurate price forecast with optimized parameters and input features.So far,no literature has been found on multistage feature and parameter selections using the methods of LSSVM-GA for hour-ahead price prediction.All the models are examined on the Ontario power market;which is reported as among the most volatile market worldwide.A huge number of features are selected by three stages of optimization to avoid from missing any important features.The developed LSSVM-GA shows higher forecast accuracy with lower complexity than the existing models.…”
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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

“…Lower accuracy is produced due to the nature of electricity price that is highly volatile. Hence, some researchers have developed complex procedures and techniques to produce more accurate forecast while considering significant feature selection as well as parameter optimization. …”
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Modeling financial environments using geometric fractional Brownian motion model with long memory stochastic volatility by Al Haqyan, Mohammed Kamel Mohammed

“…All parameters involved in the developed model are estimated by using innovation algorithm. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Corrosion Inhibition Study Of Carboxymethyl Celluloseionic Liquid Via Electrochemical And Machine Learning Technique by Adi Hafizamri Ariffin, Wan Mohd Norsani Wan Nik, Samsuri Abdullah, Mohd Ikmar Nizam Mohamad Isa, Vincent Izionworu, Mohammad Fakhratul Ridwan Zulkifli

Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush