Multi-Parameter Computational Modeling of Nuclear Stability, Binding Energy, and Radioactive Decay Dynamics with Quantitative Validation

This work presents a computational framework for modeling nuclear stability using the Semi-Empirical Mass Formula (SEMF), separation energies, and radioactive decay classification rules. A large synthetic nuclear dataset is generated and analyzed to identify stability regions, decay pathways, binding energy trends, and drip line boundaries. The framework reproduces major macroscopic nuclear phenomena including the valley of stability, binding energy peak near the iron region, and proton/neutron drip lines. Simulated results are compared against experimental nuclear datasets using quantitative validation metrics such as Mean Absolute Error (MAE) and Root Mean Square Error (RMSE), demonstrating strong agreement with established nuclear physics trends.