IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Advanced Machine Learning Models for Dynamic Pricing in Energy Markets

Advanced Machine Learning Models for Dynamic Pricing in Energy Markets
View Sample PDF
Author(s): Usharani Bhimavarapu (Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, India)
Copyright: 2026
Pages: 30
Source title: Harnessing Data Science for Sustainable Insurance
Source Author(s)/Editor(s): Gagan Kukreja (College of Business Administration, University of Bahrain, Bahrain), Ayben Koy (Fenerbahçe University, Turkey), Pooja Kansra (Mittal School of Business, Lovely Professional University, India), Diksha Verma (Chandigarh Business School of Administration, Landran Mohali, India)and S.L. Gupta (Birla Institute of Technology, India)
DOI: 10.4018/979-8-3373-1882-0.ch001

Purchase

View Advanced Machine Learning Models for Dynamic Pricing in Energy Markets on the publisher's website for pricing and purchasing information.

Abstract

Dynamic pricing schemes have an important function in firms aiming to optimize revenue while being fair to consumers. In this study, dynamic pricing methods application in markets like electric vehicle (EV) charging is examined, where fluctuating demand, shifting consumer tastes, and weather conditions raise the intricacy of the decision-making process regarding prices. The research will strike a balance between profitability and customer equity using advanced machine learning techniques, specifically a Bidirectional Stacked Gated Recurrent Unit (BiStacked GRU) model. The model identifies the intricate, sequential relationships among time-series data, which allows for demand fluctuation and customer behavior forecasting in response to price adjustments. Particle Swarm Optimization (PSO) is also applied in feature selection, the identification of the most influential variables that impact pricing strategies.

Related Content

Usharani Bhimavarapu. © 2026. 30 pages.
Jasvir Kaur. © 2026. 24 pages.
Nida Fatimah, K. Jayashree. © 2026. 30 pages.
Kirti Rani, Simranjit Kaur. © 2026. 24 pages.
Usharani Bhimavarapu. © 2026. 26 pages.
Piali Haldar, Dev Kumar Mandal, Utkarsh Gupta. © 2026. 32 pages.
Rachit Agarwal, Tanya Kumar, Shraddha Rawat, Harpreet Kaur. © 2026. 28 pages.
Body Bottom