Innovative Research Award
Mrs. Sajedeh Hedayatallahpour
Iran University of Science and Technology (IUST), Iran
| Mrs. Sajedeh Hedayatallahpour |
| Affiliation |
Iran University of Science and Technology (IUST) |
| Country |
Iran |
| Scopus ID |
59511409900 |
| Documents |
1 |
| Citations |
10 |
| h-index |
1 |
| Subject Area |
Artificial Intelligence |
| Event |
Global CSE Awards |
Mrs. Sajedeh Hedayatallahpour is a researcher affiliated with Iran University of Science and Technology whose documented scholarly profile is associated with Artificial Intelligence and forecasting-oriented research. Her indexed record includes work involving grey prediction and electricity-related forecasting, providing a basis for consideration within the Innovative Research Award category of the Global CSE Awards. [1] [3]
Abstract
Mrs. Sajedeh Hedayatallahpour, affiliated with Iran University of Science and Technology, has a documented research profile in Artificial Intelligence and forecasting-related computational methods. Her scholarly record includes research applying grey prediction approaches to energy forecasting and electricity-market analysis, including work involving the Von Bertalanffy equation and improved grey Verhulst modelling. These studies demonstrate an interest in predictive modelling, computational intelligence, and data-driven forecasting problems with practical energy applications. Her Scopus record reports one document, ten citations, and an h-index of one. Based on these documented research activities, her profile may be considered relevant to an Innovative Research Award focused on computational and artificial-intelligence-oriented research. [1] [2] [3]
Keywords
Artificial Intelligence; Grey Prediction; Energy Forecasting; Electricity Market Forecasting; Grey Verhulst Model; Predictive Modelling; Computational Intelligence; Reinforcement Learning; Energy Systems; Research Innovation. [1] [2]
Introduction
Research in Artificial Intelligence increasingly incorporates predictive and computational methods for complex energy-system problems. Grey-system modelling provides approaches for forecasting when available information may be limited or uncertain. Hedayatallahpour’s documented research connects these methods with energy and electricity-market forecasting, positioning her work within an applied computational research context relevant to intelligent prediction. [1] [2]
Research Profile
The available Scopus information identifies Mrs. Sajedeh Hedayatallahpour with Scopus Author ID 59511409900 and records one document, ten citations, and an h-index of one. Her listed subject area is Artificial Intelligence, while the available publications indicate an applied interest in grey prediction, forecasting, and energy-related computational analysis. [3]
Research Contributions
Her documented contributions include applying a grey prediction model based on the Von Bertalanffy equation to energy prediction and investigating an improved time-delay grey Verhulst model for electricity-market forecasting. The latter work incorporates multi-agent reinforcement learning optimization, illustrating a combination of grey modelling and contemporary intelligent computational techniques. [1] [2]
Publications
The documented publication record includes research on grey prediction and energy forecasting. One identified article is titled “A grey prediction model based on Von Bertalanffy equation and its application in energy prediction.” Another documented research contribution concerns an improved time-delay grey Verhulst model optimized through multi-agent reinforcement learning for electricity-market forecasting. [1] [2]
Research Impact
The available bibliometric record reports ten citations for one indexed document, indicating that the documented research has received scholarly attention. Its application-oriented focus on energy prediction and electricity-market forecasting gives the work relevance to computational decision-support problems, while the integration of forecasting models with intelligent optimization reflects interdisciplinary research connecting artificial intelligence with energy systems. [1] [3]
Award Suitability
The documented research is relevant to an Innovative Research Award because it addresses forecasting challenges through computational modelling and combines established grey-system techniques with intelligent optimization. The research also demonstrates application-oriented innovation in energy prediction and electricity-market forecasting. Award assessment should additionally consider the complete publication record, originality, methodology, and verified research achievements. [1] [2]
Conclusion
Mrs. Sajedeh Hedayatallahpour’s documented research profile combines Artificial Intelligence with forecasting methods applied to energy-related problems. Her identified studies address grey prediction, energy prediction, and electricity-market forecasting, including reinforcement-learning-based optimization. These themes provide a credible scholarly basis for consideration under an Innovative Research Award, subject to independent verification and award criteria. [1] [2] [3]
External Links
References
- Elsevier. (2025). A grey prediction model based on Von Bertalanffy equation and its application in energy prediction. Journal of Computational Science.
https://www.sciencedirect.com/science/article/abs/pii/S0952197625000120
- Hedayatallahpour, S. (n.d.). An Improved Time-Delay Grey Verhulst Model Optimized by Multi-Agent Reinforcement Learning for Electricity Market Forecasting. Civilica.
https://en.civilica.com/doc/2478582/
- Elsevier. (n.d.). Scopus author details: Sajedeh Hedayatallahpour, Author ID 59511409900. Scopus.
https://www.scopus.com/authid/detail.uri?authorId=59511409900