Prediction of strength and durability properties of HPC composites using Adaptive Neuro-fuzzy Inference System

Prediction of strength and durability properties of HPC composites using Adaptive Neuro-fuzzy Inference System

High-Performance Concrete (HPC) is a high-quality concrete that requires special conformity and performance requirements. The objective of this study was to investigate the possibilities of adapting neural expert systems like Adaptive Neuro-Fuzzy Inference System (ANFIS) in the development of a simu...

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Main Authors: Magudeaswaran. P, Kumar C. Vivek, Ravinder Rathod
Format: Article
Language:English
Published: EDP Sciences 2020-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/44/e3sconf_icmed2020_01102.pdf
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spelling doaj-b0bb25c77a804bd3a2a645c7c07cb2132021-04-02T18:08:43ZengEDP SciencesE3S Web of Conferences2267-12422020-01-011840110210.1051/e3sconf/202018401102e3sconf_icmed2020_01102Prediction of strength and durability properties of HPC composites using Adaptive Neuro-fuzzy Inference SystemMagudeaswaran. P0Kumar C. Vivek1Ravinder Rathod2Professor, Civil Engineering, Adithya Institute of TechnologyAssistant Professor, Civil Engineering Department, GRIETAssistant Professor, Civil Engineering Department, GRIETHigh-Performance Concrete (HPC) is a high-quality concrete that requires special conformity and performance requirements. The objective of this study was to investigate the possibilities of adapting neural expert systems like Adaptive Neuro-Fuzzy Inference System (ANFIS) in the development of a simulator and intelligent system and to predict durability and strength of HPC composites. These soft computing methods emulate the decision-making ability of human expert benefits both the construction industry and the research community. These new methods, if properly utilized, have the potential to increase speed, service life, efficiency, consistency, minimizes errors, saves time and cost which would otherwise be squandered using the conventional approaches.https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/44/e3sconf_icmed2020_01102.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Magudeaswaran. P
Kumar C. Vivek
Ravinder Rathod
spellingShingle Magudeaswaran. P
Kumar C. Vivek
Ravinder Rathod
Prediction of strength and durability properties of HPC composites using Adaptive Neuro-fuzzy Inference System
E3S Web of Conferences
author_facet Magudeaswaran. P
Kumar C. Vivek
Ravinder Rathod
author_sort Magudeaswaran. P
title Prediction of strength and durability properties of HPC composites using Adaptive Neuro-fuzzy Inference System
title_short Prediction of strength and durability properties of HPC composites using Adaptive Neuro-fuzzy Inference System
title_full Prediction of strength and durability properties of HPC composites using Adaptive Neuro-fuzzy Inference System
title_fullStr Prediction of strength and durability properties of HPC composites using Adaptive Neuro-fuzzy Inference System
title_full_unstemmed Prediction of strength and durability properties of HPC composites using Adaptive Neuro-fuzzy Inference System
title_sort prediction of strength and durability properties of hpc composites using adaptive neuro-fuzzy inference system
publisher EDP Sciences
series E3S Web of Conferences
issn 2267-1242
publishDate 2020-01-01
description High-Performance Concrete (HPC) is a high-quality concrete that requires special conformity and performance requirements. The objective of this study was to investigate the possibilities of adapting neural expert systems like Adaptive Neuro-Fuzzy Inference System (ANFIS) in the development of a simulator and intelligent system and to predict durability and strength of HPC composites. These soft computing methods emulate the decision-making ability of human expert benefits both the construction industry and the research community. These new methods, if properly utilized, have the potential to increase speed, service life, efficiency, consistency, minimizes errors, saves time and cost which would otherwise be squandered using the conventional approaches.
url https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/44/e3sconf_icmed2020_01102.pdf
work_keys_str_mv AT magudeaswaranp predictionofstrengthanddurabilitypropertiesofhpccompositesusingadaptiveneurofuzzyinferencesystem
AT kumarcvivek predictionofstrengthanddurabilitypropertiesofhpccompositesusingadaptiveneurofuzzyinferencesystem
AT ravinderrathod predictionofstrengthanddurabilitypropertiesofhpccompositesusingadaptiveneurofuzzyinferencesystem
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