Stochastic Processes for finding Prediction of Weight Status and their Predictive Lipid Makers using α - Brownian Motion

Dr. N. Umamaheswari, R. Guna Sundhari

Abstract: The study aims to forecast an individual's weight category e.g., underweight, normal, overweight, obese. A generalization of Brownian motion, allowing for more complex and realistic modelling of dynamic systems. Computational experiments on the presented methods are reported.

Keywords: Brownian Motion, It's Formula: The Essence, The Girsanov Theorem, Gartner - Ellis Theorem, ?-Brownian Motion, Large Deviation for Energy, Sharp Large Deviation for Energy (SLDE), High-Density Lipoprotein (HDL), Low-Density Lipoprotein (LDL)

How to Cite?: Dr. N. Umamaheswari, R. Guna Sundhari, "Stochastic Processes for finding Prediction of Weight Status and their Predictive Lipid Makers using α - Brownian Motion", Volume 14 Issue 2, February 2025, International Journal of Science and Research (IJSR), Pages: 1653-1659, https://www.ijsr.net/getabstract.php?paperid=SR25226104903, DOI: https://dx.doi.org/10.21275/SR25226104903

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R Anbalagan Rating: 10/10 😊

2025-03-01

This is a very valuable resource for people working within mathematics and that publish on stochastic processes.

K.b.abirami Rating: 10/10 😊

2025-03-01

This article very helpful to us to predict our weight.

Jaya Lakshmi Rating: 10/10 😊

2025-03-01

This article effectively explores the use of stochastic processes for weight prediction. It provides a solid mathematical foundation and discusses practical applications, making it useful for research

Anbalagan Rajan Rating: 10/10 😊

2025-03-01

The work offers a solid theoretical basis for employing stochastic models to forecast weight status. But it doesnt close the gap between theoretical forecasts and practical implementations.