Electricity load forecasting: a systematic review

IK Nti, M Teimeh, O Nyarko-Boateng… - Journal of Electrical …, 2020 - Springer
The economic growth of every nation is highly related to its electricity infrastructure, network,
and availability since electricity has become the central part of everyday life in this modern …

A systematic review of statistical and machine learning methods for electrical power forecasting with reported mape score

E Vivas, H Allende-Cid, R Salas - Entropy, 2020 - mdpi.com
Electric power forecasting plays a substantial role in the administration and balance of
current power systems. For this reason, accurate predictions of service demands are needed …

Artificial intelligence for load forecasting: A stacking learning approach based on ensemble diversity regularization

J Shi, C Li, X Yan - Energy, 2023 - Elsevier
State-of-art artificial intelligence (AI) has made great breakthroughs in various industries.
Ensemble learning mixed with various predictors provides a considerable solution for …

Mid-term electricity demand forecasting using improved variational mode decomposition and extreme learning machine optimized by sparrow search algorithm

T Gao, D Niu, Z Ji, L Sun - Energy, 2022 - Elsevier
Mid-term electricity demand forecasting plays an important role in ensuring the operational
safety of the power system and the economic efficiency of grid companies. Most studies …

[HTML][HTML] Incorporating air temperature into mid-term electricity load forecasting models using time-series regressions and neural networks

NB Behmiri, C Fezzi, F Ravazzolo - Energy, 2023 - Elsevier
One of the most controversial issues in the mid-term load forecasting literature is the
treatment of weather. Because of the difficulty in obtaining precise weather forecasts for a …

[HTML][HTML] A review of electricity demand forecasting in low and middle income countries: The demand determinants and horizons

AA Mir, M Alghassab, K Ullah, ZA Khan, Y Lu, M Imran - Sustainability, 2020 - mdpi.com
With the globally increasing electricity demand, its related uncertainties are on the rise as
well. Therefore, a deeper insight of load forecasting techniques for projecting future …

[HTML][HTML] Neural networks for financial time series forecasting

K Sako, BN Mpinda, PC Rodrigues - Entropy, 2022 - mdpi.com
Financial and economic time series forecasting has never been an easy task due to its
sensibility to political, economic and social factors. For this reason, people who invest in …

Short-term load forecasting with an improved dynamic decomposition-reconstruction-ensemble approach

D Yang, J Guo, Y Li, S Sun, S Wang - Energy, 2023 - Elsevier
Short-term load forecasting has evolved into an important aspect of power system in safe
operation and rational dispatching. However, given the load series' instability and volatility …

Forecasting electricity consumption using a novel hybrid model

GF Fan, X Wei, YT Li, WC Hong - Sustainable Cities and Society, 2020 - Elsevier
In recent years, the electricity industry has become increasingly important to social and
economic development. For sustainability of the power industrial business, an accurate …

Forecasting the macrolevel determinants of entrepreneurial opportunities using artificial intelligence models

SB Jabeur, H Ballouk, S Mefteh-Wali, A Omri - … Forecasting and Social …, 2022 - Elsevier
To date, entrepreneurship researchers have tended to avoid state-of-the-art artificial
intelligence techniques; in this paper, we fill that gap. Based on eclectic entrepreneurship …