Analysis of nutrient intake and energy consumption during college students' exercise based on big data technology

Abstract

In order to analyze the correlation between nutrient intake and energy consumption in college students' exercise, this paper combines big data technology to analyze the nutrition intake and energy consumption in college students' exercise process, so as to promote the balance of nutrient intake and energy consumption in college students' exercise. Moreover, this paper proposes a data-driven model predictive controller for designing multi-rate sampling systems based on model regression and system identification. In addition, this paper uses an extended dimension method to transform the multi-rate sampling system into an equivalent linear discrete time-invariant system to perform model optimization. Finally, this paper verifies the validity of the model in this paper through experimental research and gives some suggestions.