Artificial intelligence driven demand forecasting: an application to the electricity market
作者：
Marco Repetto;Cinzia Colapinto*;Muhammad Usman Tariq
通讯作者：
Cinzia Colapinto
作者机构：
CertX, Fribourg, Switzerland
IPAG Business school, Nice, France and Ca’ Foscari University of Venice, Venice, Italy
Abu Dhabi University, Abu Dhabi, United Arab Emirates
通讯机构：
IPAG Business school, Nice, France and Ca’ Foscari University of Venice, Venice, Italy
语种：
英文
关键词：
Demand forecasting,Federated learning,Deep learning,Multiple criteria decision making,Goal programming,Electricity forecasting
期刊：
Annals of Operations Research
ISSN：
0254-5330
年：
2024
基金类别：
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sector
摘要：
Demand forecasting with maximum accuracy is critical to business management in various fields, from finance to marketing. In today’s world, many firms have access to a lot of data that they can use to implement sophisticated models. This was not possible in the past, but it has become a reality with the advent of large-scale data analysis. However, this also requires a distributed thinking approach due to the resource-intensive nature of Deep Learning models. Forecasting power demand is of utmost importance in the energy industry, and various methods and approaches have been employed by electrical companies for predicting electricity demand. This paper proposes a novel m...
