Machine Learning Technologies on Energy Economics and Finance Energy and Sustainable Analytics, Volume 1 /
| Corporate Author: | |
|---|---|
| Other Authors: | , |
| Summary: | X, 332 p. 145 illus., 141 illus. in color. text |
| Language: | English |
| Published: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
|
| Edition: | 1st ed. 2025. |
| Series: | International Series in Operations Research & Management Science,
367 |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-3-031-94862-6 |
| Format: | Electronic Book |
Table of Contents:
- Analyzing Global Energy Patterns: Clustering Countries and Predicting Trends Towards Achieving Sustainable Development Goals
- Access to Energy Finance: Development of Renewable Energy in Bangladesh
- Explainable AI in Energy Forecasting: Understanding Natural Gas Consumption through Interpretable Machine Learning Models
- An Extensive Statistical Analysis of Time Series Modelling and Forecasting of Crude Oil Prices
- Comparative analysis of selected emerging economies energy transition scenario: A transition pathway for the continental neighbours
- Forecasting Energy Prices using Machine Learning Algorithms: A Comparative Analysis
- An Evidence-based Explainable AI Approach for Analyzing the Influence of CO2 Emissions on Sustainable Economic Growth
- BLDAR: A Blending Ensemble Learning Approach for Primary Energy Consumption Analysis
- Analyzing Biogas Production in Livestock Farms Using Explainable Machine Learning
- Application of Machine Learning Techniques in the Analysis of Sustainable Energy Finance
- Machine Learning and Deep Learning Strategies for Sustainable Renewable Energy: A Comprehensive Review
- Efficient Gasoline Spot Price Prediction using Hyperparameter Optimization and Ensemble Machine Learning Approach
- The Implications of Energy Transition and Development of Renewable Energy on Sustainable Development Goals of Two Asian Tigers.