Predictive Modeling of GH Blunting Patterns in Aging ‎and Exercise-Trained Individuals

  • Authors

    • Bevara Kondala Rao Department of Mathematics, GIET University, Gunupur, Rayagada 765022, Odisha, India and Department of Mathematics, SRI GCSR Degree College, Rajam 532127, Andhra Pradesh, India
    • Biplab Kumar Rath Department of Mathematics, SRI GCSR Degree College, Rajam 532127, Andhra Pradesh, India
    • A. Manickam School of Sciences, Division of Mathematics, SRM Institute of Science and Technology, Tiruchirappalli Campus, SRM Nagar, Trichy – Chennai Highway, Near Samayapuram, ‎Tiruchirappalli –621105. Tamilnadu, India
    https://doi.org/10.14419/51sv4776

    Received date: July 3, 2025

    Accepted date: August 2, 2025

    Published date: August 14, 2025

  • Reliability; GH; Failure Patterns; Normal Process; Quasiparametric Model

  • Abstract

    This paper proposes a novel semiparametric method using Gaussian process smoothing to estimate failure rates in engineered systems. Unlike traditional models, it provides accurate estimates based on historical data without assuming specific failure rate patterns. Experiments ‎using power system failure data demonstrate the method’s accuracy and effectiveness compared to other models. The approach applies ‎to various systems, including software reliability estimation. Additionally, mathematical results align well with the Gaussian process model, ‎successfully identifying the peak of growth hormone deficiency over time‎.

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  • How to Cite

    Rao , B. K. ., Rath , B. K. ., & Manickam , A. . (2025). Predictive Modeling of GH Blunting Patterns in Aging ‎and Exercise-Trained Individuals. International Journal of Basic and Applied Sciences, 14(4), 425-429. https://doi.org/10.14419/51sv4776