“To Improve Model Precision via the Integration of AI and IoT in Mathematical Modeling”
DOI:
https://doi.org/10.48047/yr3m3j15Keywords:
Model Accuracy, Evolving Optimizations , Illustrating Techniques, Fuzzy Logic, Linear Algorithm Design, Innovative Optimizations linear geometry Algorithms .Abstract
Employing methods to improve model precision This research addresses nonlinear restricted optimization through the application of
AI-integrated mathematical modelling. The incorporation of AI through mathematical modelling signifies a merging of traditional
mathematical methods with sophisticated AI approaches, encompassing both machine learning and deep learning. This integration
aims to develop models that demonstrate increased precision, effectiveness, and flexibility in adapting to changing environments and
new data as it arises. Mathematical modelling involves the articulation of real-world challenges using mathematical expressions, which
facilitates the analysis, simulation, alongside prediction of diverse outcomes. Mathematical models can be classified into various
categories, 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 modelling
purposes, and the implementation of Bayesian techniques.
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