Md. Akhtaruzzaman, Mohammad Kamrul Hasan, S. Rayhan Kabir, Siti Norul Huda Sheikh Abdullah et al.
Load forecasting is a vital part of smart grids for predicting the required electrical power using artificial intelligence (AI). Deep learning is broadly used for load forecasting in the smart grid using the artificial neural network (ANN). Generally, computing the deep learning in the smart grid re...
Ahmed Yousuf Saber, Afrin Alam
This paper presents short term load forecasting using multi-variable linear regression (MLR) for big data. Load forecasting is very important for planning, operation, resource scheduling and so on in power system. Total electric demand dynamically changes in a power system and mainly depends on temp...
Abdus Samad Azad, Rajalingam Sokkalingam, Hanita Daud, Sajal Kumar Adhikary et al.
Reservoir water level (RWL) prediction has become a challenging task due to spatio-temporal changes in climatic conditions and complicated physical process. The Red Hills Reservoir (RHR) is an important source of drinking and irrigation water supply in Thiruvallur district, Tamil Nadu, India, also e...
Razin Ahmed, Victor Sreeram, Roberto Togneri, Amitava Datta et al.
A.K. Azad, M.G. Rasul, Rubayat Islam, Imrul R. Shishir
Wind energy is one of the fastest growing sectors in renewable energy. These energy resources are freely available throughout the world. It is one of the zero emission energy sources. The wind energy is used mainly for two purposes namely irrigation (water pumping) and electricity generation. The pr...
Jannatul Ferdous Ruma, Mohammed Sarfaraz Gani Adnan, Ashraf Dewan, Rashedur M. Rahman
Floods are one of the most catastrophic natural disasters. Water level forecasting is an essential method of avoiding floods and disaster preparedness. In recent years, models for predicting water levels have been developed using artificial intelligence techniques like the artificial neural network ...
Tashreef Muhammad, Anika Bintee Aftab, Muhammad Ibrahim, M. M. Ahsan et al.
In the modern capital market, the price of a stock is often considered to be highly volatile and unpredictable because of various social, financial, political and other dynamic factors. With calculated and thoughtful investment, stock market can ensure a handsome profit with minimal capital investme...
Trang Thi Kieu Tran, Taesam Lee, Ju‐Young Shin, Jong‐Suk Kim et al.
Time series forecasting of meteorological variables such as daily temperature has recently drawn considerable attention from researchers to address the limitations of traditional forecasting models. However, a middle-range (e.g., 5–20 days) forecasting is an extremely challenging task to get reliabl...
Iqbal Hossain, H. M. Rasel, Monzur Alam Imteaz, Fatemeh Mekanik
Md Morshed Alam, Md. Habibur Rahman, Md. Faisal Ahmed, Mostafa Zaman Chowdhury et al.
The development of the advanced metering infrastructure (AMI) and the application of artificial intelligence (AI) enable electrical systems to actively engage in smart grid systems. Smart homes with energy storage systems (ESS) and renewable energy sources (RES)-known as home microgrids-have become ...
Parag Biswas, Abdur Rashid, Angona Biswas, MD Abdullah Al Nasim et al.
Reduced environmental impacts, lower operating costs, and a stable, sustainable energy supply for current and future generations are the main reasons why power optimization is important. Power optimization ensures that energy is used more efficiently, reducing waste and optimizing the utilization of...
Dilip Kumar Roy, Tapash Kumar Sarkar, Sheikh Shamshul Alam Kamar, Torsha Goswami et al.
Precise forecasting of reference evapotranspiration (ET0) is one of the critical initial steps in determining crop water requirements, which contributes to the reliable management and long-term planning of the world’s scarce water sources. This study provides daily prediction and multi-step forward ...
Mohammad Islam Miah, Sohrab Zendehboudi, Salim Ahmed
Log-based reservoir characterization is one of the widely used techniques to estimate the reservoir properties and make decisions for hydrocarbon production. Use of the machine learning tools is becoming a more accessible approach for data-driven model development. The objective of this research is ...
M. Abdullah Al Amin, Md. Ashraful Hoque
To ensure a stable and reliable operation of a power system network, load forecasting on a short-term basis is very crucial. The two most important requirements of short-term load forecasting are accurate forecasting and speed. It is really necessary to study as well as analyze the load characterist...
Mustain Billah, Sajjad Waheed, Abu Hanifa
Predicting closing stock price accurately is an challenging task. Computer aided systems have been proved to be helpful tool for stock prediction such as Artificial Neural Net-work(ANN), Adaptive Neuro Fuzzy Inference System (ANFIS) etc. Latest research works prove that Adaptive Neuro Fuzzy Inferenc...