A Neuro-Fuzzy Predictor Trained by an Elitism Artificial Electric Field Algorithm for Estimation of Compressive Strength of Concrete Structures

Abstract

Machine learning based forecasting are found better to manual and statistical methods in estimating compressive strength of concrete structures. However, there is need of exploring an effective, automated and accurate predictor for this domain. This article proposes an artificial electric field algorithm-based neuro-fuzzy network (AEFA+NFN) for prediction of compressive strength of concrete structures. A single hidden layer neural network (SHNN) is used as the base model and its inputs are fuzzified using Gaussian triangular membership function with a degree of membership to different classes. The optimal number of input data, hidden neurons, bias and weights for hidden layer are decided by AEFA. The model is evaluated on samples from a publicly available dataset with curing ages at 3, 7, 14, and 28 days. Considering four sample series, the AEFA+NFN produced an average MAPE of 0.092073 and ARV of 0.139731 which are better compared to others. The experimental outcomes and analysis are in favor of the AEFA+NFN based forecasting.

Author Biographies

Chaudhury Sanjeev Kumar Dash, Department of Computer Science & Engineering, Silicon Institute of Technology, Silicon Hills, Patia,Bhubaneswar – 751024, India

Dept. of CSEAsssoc. Professor

Sarat Chandra Nayak, CMR College of Engineering & Technology, Hyderabad-501401, India

Department of Artificial Intelligence Engineering &  Machine LearningAssociate Professor

Ajit Kumar Behera, Department of Computer Science & Engineering, Silicon Institute of Technology, Silicon Hills, Patia,Bhubaneswar – 751024, India

Dept. of Computer ScienceAssociate Professor

Satchidananda Dehuri, Department of Information and Communication Technology, Fakir Mohan University, Vyasa Vihar, Balasore-756019, Odisha, India.

ICT. Dept.Professor

Authors

  • Chaudhury Sanjeev Kumar Dash Department of Computer Science & Engineering, Silicon Institute of Technology, Silicon Hills, Patia,Bhubaneswar – 751024, India
  • Sarat Chandra Nayak CMR College of Engineering & Technology, Hyderabad-501401, India
  • Ajit Kumar Behera Department of Computer Science & Engineering, Silicon Institute of Technology, Silicon Hills, Patia,Bhubaneswar – 751024, India
  • Satchidananda Dehuri Department of Information and Communication Technology, Fakir Mohan University, Vyasa Vihar, Balasore-756019, Odisha, India.

DOI:

https://doi.org/10.31449/inf.v47i5.3951

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Published

05/22/2023

How to Cite

Dash, C. S. K., Nayak, S. C., Behera, A. K., & Dehuri, S. (2023). A Neuro-Fuzzy Predictor Trained by an Elitism Artificial Electric Field Algorithm for Estimation of Compressive Strength of Concrete Structures. Informatica, 47(5). https://doi.org/10.31449/inf.v47i5.3951

Issue

Vol. 47 No. 5 (2023): Online-only issue

Section

Online-only

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