Description

Book Synopsis

Green Driving: Harnessing Machine Learning to Predict Vehicle Carbon Footprints and Interpreting Results with Explainable AI.- A Comparative Evaluation of Deep Neural Networks for Electricity Price Forecasting.- Energy Forecasting Utilizing CNN-LSTM Attention Mechanism: Empirical Evidence from the Spanish Electricity Market.- Feature Selection and Explainable AI For Transparent Windmill Power Forecasting.- Improving the Analysis of CO2 Emissions with a Filter and Imputation-Based Processing Method.- A Study on the Efficacy of Machine Learning and Ensemble Learning in Wind Power Generation Analysis.- Predicting Solar Radiation: A Fusion Approach with CatBoost and Random Forest Ensemble Enhanced by Explainable AI.- Modeling Nuclear Fusion Reaction Occurrence with Advanced Deep Learning Techniques: Insights from LIME and SMOTE.- A Critical Study on LSTM AND TRANSFORMER Models for Financial Analysis and Forecasting.- Exploring Feature Selection Techniques in Predicting Indian Household Electricity Consumption.- Constructing Women Empowerment Indices-based on Kernel PCA and Evaluating Its Determinants: Evidence from BDHS.- An Ensemble Machine Learning Approach to Predicting CO2 Emission Rates: Evidence from Denmark's Energy Data Service.- Smart Grid Stability Analysis with Interpretable Machine Learning and Deep Learning Models.- Weather as a Critical Component in Investment Strategies: Insights for Stakeholders.

Machine Learning Technologies on Energy Economics and Finance

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    A Hardback by Mohammad Zoynul Abedin

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      Publisher: Springer
      Publication Date: 25/08/2025
      ISBN13: 9783031950988, 978-3031950988
      ISBN10:
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      Management of specific areas

      Description

      Book Synopsis

      Green Driving: Harnessing Machine Learning to Predict Vehicle Carbon Footprints and Interpreting Results with Explainable AI.- A Comparative Evaluation of Deep Neural Networks for Electricity Price Forecasting.- Energy Forecasting Utilizing CNN-LSTM Attention Mechanism: Empirical Evidence from the Spanish Electricity Market.- Feature Selection and Explainable AI For Transparent Windmill Power Forecasting.- Improving the Analysis of CO2 Emissions with a Filter and Imputation-Based Processing Method.- A Study on the Efficacy of Machine Learning and Ensemble Learning in Wind Power Generation Analysis.- Predicting Solar Radiation: A Fusion Approach with CatBoost and Random Forest Ensemble Enhanced by Explainable AI.- Modeling Nuclear Fusion Reaction Occurrence with Advanced Deep Learning Techniques: Insights from LIME and SMOTE.- A Critical Study on LSTM AND TRANSFORMER Models for Financial Analysis and Forecasting.- Exploring Feature Selection Techniques in Predicting Indian Household Electricity Consumption.- Constructing Women Empowerment Indices-based on Kernel PCA and Evaluating Its Determinants: Evidence from BDHS.- An Ensemble Machine Learning Approach to Predicting CO2 Emission Rates: Evidence from Denmark's Energy Data Service.- Smart Grid Stability Analysis with Interpretable Machine Learning and Deep Learning Models.- Weather as a Critical Component in Investment Strategies: Insights for Stakeholders.

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