Machine Learning Technologies on Energy Economics and Finance – Energy and Sustainable Analytics, Volume I & II
- By Springer
Publication in Studies in International Series in Operations Research & Management Science
Indexed by Web of Science (WoS)
Submission Deadline: 15 July 2024
Publication Deadline: 15 December 2024
Submission Link: Click Here to Submit
Scope
The proposed book will present the significance and application of machine learning algorithms for the development of the energy sector. This book will also highlight the introduction of energy economics and finance; consider all necessary innovative factors that contribute to the development of energy and sustainable analytics. Energy economics basically focuses on the production and consumption of energy under socioeconomic perspective and Energy finance is a sub-field of energy economic. This proposed book will cover all factors that have an impact on fossil fuels such as market structures, regulatory frame works, environmental impacts, and global energy market.
This book will be beneficial to academics, practitioners, financial managers, stakeholders, government, and policy makers who are looking for ways the advancement of energy systems, reducing energy costs, increasing revenue for economic growth. Renewable Energy Technologies (RETs) place a significant role on the development of energy economics and finance which is an alternative to fossil fuel. Thus, the purpose of this proposed book is to provide the prediction of energy prices, crude oil prices, electricity prices, fuel wood prices, solar prices, natural gas prices, and show the role of RETs on energy economic sector.
Keywords
Machine learning; Data Analytics; Deep learning; Energy Analytics; Energy consumption and production; Energy price; Climate finance; Global energy market; Sustainable finance; CO2 emission
Topics
Management Policy for Energy Demand and Supply
Global Energy Market and Energy Finance
The Role of Renewable Energy Technologies on Energy Economic Sector
Forecasting of Energy Prices with Big Data and Artificial Intelligence
Analysis of Sustainable Energy Finance with Machine Learning
The Role of Women in Energy Economics and Finance
Analysis of Global Energy Market Security with Business Intelligence
ML/DL Algorithms in Economic and Financial Analysis of Energy Market
Analysis of Innovative Factors for the Development of Energy Economics and Energy Supply
CO2 Omission and Global Energy Market
Sustainable Development Goals (SDGs) and CO2 Omission