Prediction of Compressive Strength of Geopolymer Concrete Based on Support Vector Machine and Modified Cuckoo Algorithm

Daming Zhang,Fangjin Sun,Tiantian Liu,Shengwen Tang

doi:10.1155/2021/4286810

Abstract

Coal gangue-based geopolymer concrete is an environmentally friendly material made from coal gangue, solid waste from the coal mine. Compressive strength is one of the most important indexes for concretes. Different oxide contents of coal gangue will affect the compressive strength of the geopolymer concrete directly. However, there is little study on the relationship between oxide contents and compressive strength of the geopolymer concrete. Experiments are commonly used methods of determining the compressive strength of concretes, including geopolymer concrete, which is time-consuming and inefficient. Therefore, in the work here, a support vector machine and a modified cuckoo algorithm are utilized to predict the compressive strength of geopolymer concrete. An orthogonal factor is introduced to modify the traditional cuckoo algorithm to update new species and accelerate computation convergence. Then, the modified cuckoo algorithm is employed to optimize the parameters in the support vector machine model. Then, the compressive strength predictive model of coal gangue-based geopolymer concrete is established with oxide content of raw materials as the input and compressive strength as the output of the model. The compressive strength of coal gangue-based geopolymer concrete is predicted with different oxide contents in raw materials, and the effects of different oxide contents and oxide combinations on compressive strength are studied and analyzed. The results show that the support vector machine and the modified cuckoo algorithm are valid and accurate in predicting the compressive strength of geopolymer concrete. And, coal gangue geopolymer concrete compressive strength is significantly affected by oxide contents.

Highlights

In order to overcome the shortcomings of high energy consumption and heavy pollution of traditional concrete, the authors have successfully made coal gangue-based geopolymer by mixing coal gangue, fly ash, and standard sand [1, 2]
In order to overcome the shortcomings of the traditional cuckoo algorithm, such as large search range and low search efficiency, this paper proposes to introduce the orthogonal crossover operator into the traditional cuckoo algorithm to obtain the improved cuckoo algorithm to quickly find the optimal solution
Based on the prediction model and algorithm proposed in the previous chapter, this chapter studies and establishes the mapping relationship between the oxides in raw materials and the compressive strength of coal gangue based geopolymer concrete

Summary

Introduction

In order to overcome the shortcomings of high energy consumption and heavy pollution of traditional concrete, the authors have successfully made coal gangue-based geopolymer by mixing coal gangue, fly ash, and standard sand [1, 2]. Khatib Zada Farhan et al [8] assessed important parameters involved in geopolymer materials Raw materials such as coal gangue and fly ash contain oxides with different compositions and contents. Erefore, it is of great importance to study appropriate intelligent algorithms to predict the compressive strength and reveal the effects of different oxide contents on the compressive strength of coal gangue-based geopolymer concrete. The compressive strength of coal ganguebased geopolymer concrete is predicted based on a support vector machine and improved cuckoo algorithm. E prediction model between the compressive strength of coal gangue-based geopolymer concrete and the oxide content of raw materials was established. E existing data are used to train the prediction model; after meeting the accuracy requirements, the compressive strength of coal gangue-based geopolymer concrete with different oxide content in raw materials and oxide combination is predicted. E influence of oxide content on the compressive strength of coal gangue-based geopolymer concrete is studied and analyzed

Preparation of Coal Gangue-Based Geopolymer Concrete

Prediction of Compressive Strength of Coal Gangue-Based Geopolymer Concrete

Findings

Conclusions