Proceedings of the Recent Advances in Artificial Intelligence for Sustainable Development (RAISD 2025)

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Neural Networks for Predicting Market Trends in Sustainable Industries: A Review

Authors
Frédéric Mirindi1, *, Derrick Mirindi2
1Department of Economics, University of Manitoba, Winnipeg, Canada
2School of Architecture and Planning, Morgan State University, Baltimore, MD, USA
*Corresponding author. Email: mirindif@myumanitoba.ca
Corresponding Author
Frédéric Mirindi
Available Online 17 July 2025.
DOI
10.2991/978-94-6463-787-8_50How to use a DOI?
Keywords
Neural Networks; Sustainable Industries; Trend Forecasting
Abstract

Neural networks (NN) are increasingly acknowledged as effective tools for forecasting market trends in sustainable industries, providing the ability to improve decision-making in complex, dynamic environments. This paper provides a review of current research employing NN for forecasting trends in key sustainable fields, specifically energy, finance, and construction. It explores diverse NN architectures, their mathematical underpinnings, and practical applications such as energy demand forecasting, sustainable finance approaches, and construction workflow optimization. Consideration is given to the particular advantages NN offer in handling non-linear patterns and adapting to variable market dynamics. While significant obstacles related to data accessibility and model interpretability persists, the outlook for NNin sustainable industries is encouraging. Advancements in explainable AI (XAI), Green AI initiatives, and real-time adaptive systems bolster this positive outlook. In an era where sustainability is paramount, NN are poised to contribute substantially to innovation and the global transition toward a more sustainable future.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the Recent Advances in Artificial Intelligence for Sustainable Development (RAISD 2025)
Series
Advances in Intelligent Systems Research
Publication Date
17 July 2025
ISBN
978-94-6463-787-8
ISSN
1951-6851
DOI
10.2991/978-94-6463-787-8_50How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Frédéric Mirindi
AU  - Derrick Mirindi
PY  - 2025
DA  - 2025/07/17
TI  - Neural Networks for Predicting Market Trends in Sustainable Industries: A Review
BT  - Proceedings of the Recent Advances in Artificial Intelligence for Sustainable Development (RAISD 2025)
PB  - Atlantis Press
SP  - 655
EP  - 670
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-787-8_50
DO  - 10.2991/978-94-6463-787-8_50
ID  - Mirindi2025
ER  -