Effective Utilization of AI Techniques to Develop a Mathematical Model for Predicting Compressive Strength

K. Suseela*
Department of Civil Engineering, Moderator Gnanadhason Polytechnic College, Tamil Nadu, India.
Periodicity:June - August'2020
DOI : https://doi.org/10.26634/jste.9.2.17157

Abstract

Fiber-reinforced concrete is a composite material widely used in Civil Engineering, and the compressive strength is a significant parameter in designing reinforced and pre-stressed concrete structures. To evaluate high-performance concrete compressive strength in real-time is quite challenging because it consumes cost, time, and complex to compute. To overcome this obstacle, the proposed strategy is appropriate in the context of identifying compressive strength for high-performance concrete. This research intends to develop a mathematical model for determining the compressive strength of high-performance concrete. This research anticipates by incorporating Artificial Intelligence (AI) technique to develop a mathematical model. To develop a mathematical model via manual takes a long time and is complex to compute, this urge incorporating optimization techniques to resolve these issues. The optimization involved in this research are Genetic Algorithm (GA), Evolutionary Algorithm (EA), Particle Swarm Optimization (PSO), Social Spider Optimization (SSO), Monarch Butterfly Optimization (MBO), and Opposition based Monarch Butterfly Optimization (OMBO). The entire implementation is executed in the working platform MATLAB.

Keywords

Artificial Intelligence, Mathematical Modelling, Compressive Strength, Monarch Butterfly Optimization, Opposition Based Monarch Butterfly Optimization.

How to Cite this Article?

Suseela, K. (2020). Effective Utilization of AI Techniques to Develop a Mathematical Model for Predicting Compressive Strength. i-manager's Journal on Structural Engineering, 9(2), 37-42. https://doi.org/10.26634/jste.9.2.17157

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