Mix Ratio of High-strength Concrete Based on Chaotic Particle Swarm Optimization

Abstract

The optimization of the mix ratio of high-strength and high-performance concrete needs to solve the variable design problem of many factors. The purpose of this paper is to study the optimal design of high-strength concrete mix proportions based on chaotic particle swarm optimization. This paper introduces the research background and significance of this paper, the research status of deep learning prediction, concrete compressive strength prediction and intelligent design of concrete mix ratio at home and abroad, and introduces the relevant theoretical basis, mainly including the concept of high strength concrete and chaotic particle swarm algorithm. A multi-objective optimization model for high-strength and high-performance concrete based on experimental data is proposed. Each part of the model is introduced in detail, and the system established by the intelligent design model of concrete mix ratio proposed in this paper is firstly introduced briefly, then the various functions of the system are explained, and finally the system is given method, and select a real building concrete production mix data set for testing. The optimized high-strength and high-performance concrete has higher strength and a slump of 216.4mm.