Scholarlink

This article present a systematically investigated research of ANFIS modelling for predicting compressive strength, Modulus of elasticity and modulus of rupture with combined effect of Expanded Clay Aggregate and micro fibres for which the data is taken from various literatures and those of experimental data. All the performance parameters have been predicted using the membership functions available in the ANFIS software which includes the performance parameters such as compressive strength, flexural strength and tensile strength predicted using the ANFIS tool correlated well with the performance parameters obtained through experiments. The range of RMSE, MAPE and R2(co-efficient of determination) were predicted to calculate the efficiency of results taken from ANFIS (Adaptive Neuro-Fuzzy Inference System).

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

An Adaptive Neuro-Fuzzy Inference System Based Modeling for Expanded Clay Based Light Weight Concrete with Micro-Reinforcement

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • K. K. Gaayathri,
  • J. Anita Jessie,
  • R. Sivaji,
  • Peerzada Danish,
  • Iftekhar Gull,
  • Nadeem Gulzar Shahmir,
  • S. Ganesh

摘要

This article present a systematically investigated research of ANFIS modelling for predicting compressive strength, Modulus of elasticity and modulus of rupture with combined effect of Expanded Clay Aggregate and micro fibres for which the data is taken from various literatures and those of experimental data. All the performance parameters have been predicted using the membership functions available in the ANFIS software which includes the performance parameters such as compressive strength, flexural strength and tensile strength predicted using the ANFIS tool correlated well with the performance parameters obtained through experiments. The range of RMSE, MAPE and R2(co-efficient of determination) were predicted to calculate the efficiency of results taken from ANFIS (Adaptive Neuro-Fuzzy Inference System).