“To Improve Model Precision via the Integration of AI and IoT in Mathematical Modeling”

Employing methods to improve model precision This research addresses nonlinear restricted optimization through the application ofAI-integrated mathematical modelling. The incorporation of AI through mathematical modelling signifies a merging of traditionalmathematical methods with sophisticated AI approaches, encompassing both machine learning and deep learning. This integrationaims to develop models that demonstrate increased precision, effectiveness, and flexibility in adapting to changing environments andnew data as it arises. Mathematical modelling involves the articulation of real-world challenges using mathematical expressions, whichfacilitates the analysis, simulation, alongside prediction of diverse outcomes. Mathematical models can be classified into variouscategories, including deterministic models, stochastic models, time-series analyses, regression models, and optimization models.Artificial intelligence plays a crucial role in data analysis processes, parameter estimation, model enhancement, surrogate modellingpurposes, and the implementation of Bayesian techniques.