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@article{194897,
        author = {M. ASAN NAINAR and Keerthana.R},
        title = {BEHAVIOURAL DIGITAL TWIN FOR PREDICTIVE DECISION MAKING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {6047-6057},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194897},
        abstract = {The Behavioural Digital Twin is an intelligent system designed to create a virtual representation of an individual's decision-making behaviour. The objective of this project is to develop a predictive system that analyses user interactions, preferences, and behavioural patterns to anticipate future decisions. By leveraging Artificial Intelligence, Machine Learning, and behavioural analytics, the system learns from historical user data such as choices, activities, and contextual factors to construct a personalized digital twin.
The proposed system collects behavioural data through user inputs and application interactions, processes the data using machine learning algorithms, and builds a behavioural profile for each user. This profile is used to predict potential future decisions, provide personalized recommendations, and simulate alternative decision outcomes.
The system utilizes classification and pattern recognition models to analyse behavioural trends and generate predictions. Visualization dashboards provide insights into behavioural tendencies and prediction results. This project demonstrates how digital twin technology can be applied beyond industrial systems to human behavioural modelling, enabling applications in personalized assistance, decision support systems, and intelligent recommendation platforms.},
        keywords = {},
        month = {March},
        }