Comparison of Machine Learning Approaches with Traditional Methods for Predicting the Compressive Strength of Rice Husk Ash Concrete

Muhammad Nasir Amin,Ammar Iqtidar,Kaffayatullah Khan,Muhammad Ghulam Qadir,Muhammad Faisal Javed,Faisal I Shalabi

doi:10.3390/cryst11070779

Abstract

Efforts are being devoted to reducing the harmful effect of the construction industry around the globe, including the use of rice husk ash as a partial replacement of cement. However, no method is available to date to predict the compressive strength (CS) of rice husk ash blended concrete (RHAC). In this study, advanced machine learning techniques (artificial neural network, artificial neuro-fuzzy inference system) were used to predict the CS of RHAC. Based on the published literature, six inputs, i.e., age of specimen, percentage of rice husk ash, percentage of superplasticizer, aggregates, water, and amount of cement, were selected. Results obtained from machine learning methods were compared with traditional methods such as linear and non-linear regressions. It was observed that the performance of machine learning methods was superior to traditional methods for determining the CS of RHAC. This study will prove beneficial in minimizing the cost and time of executing laboratory experiments for designing the optimum content portions of RHAC.

Highlights

Concrete is considered the most versatile and extensively used human-made material for infrastructure development on the earth
Different models for the prediction of the compressive strength (CS) of rice husk ash blended concrete (RHAC) were developed in this study
The models developed in this study were based on a wide range of data which consist of different parameters demonstrated by experimental studies that are available in the literature

Summary

Introduction

Concrete is considered the most versatile and extensively used human-made material for infrastructure development on the earth. The global consumption of concrete is increasing day by day due to rapid urbanization in emerging countries. Cement, which is the main constituent of concrete, is a major contributor to greenhouse gases and is responsible for around 7% of total global carbon dioxide emissions [1,2,3]. With the increase in the fuel prices around globe, the per unit cost of cement has increased [4]. Keeping in view these concerns about the environment, the cost of construction materials, the shortage of raw materials, and the high energy demand, the practice of utilizing alternate materials for construction is becoming a common concern across the globe

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Results

Conclusion