Application of Fuzzy System on Settlement of Shallow Footing on Granular Soil

The complex characteristics of cohesionless soil texture necessitate an examination of settlement simulation in cohesionless materials, making it a fundamental area of inquiry. This article discusses the development of integrated data intelligence algorithms with the objective of improving the relia...

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Main Author: Soroush Lesani
Format: Article
Language:English
Published: Bilijipub publisher 2023-12-01
Series:Advances in Engineering and Intelligence Systems
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Online Access:https://aeis.bilijipub.com/article_186522_14e85597d1444d663e772025f351f4a0.pdf
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author Soroush Lesani
author_facet Soroush Lesani
author_sort Soroush Lesani
collection DOAJ
description The complex characteristics of cohesionless soil texture necessitate an examination of settlement simulation in cohesionless materials, making it a fundamental area of inquiry. This article discusses the development of integrated data intelligence algorithms with the objective of improving the reliability and accuracy of estimate results for shallow foundations (Sm) on cohesionless soils. The proposed models integrate the reptile search algorithm (RSA) with support vector regression (SVR) analysis and adaptive neuro-fuzzy inference system (ANFIS). Based on the findings of the research, it can be seen that the RSSVR and RSANF systems have shown adept capabilities in the domain of estimate. During the training stage, the RSANF simulation gained the smallest performance index (PI) value of 0.0668, which was smaller than the PI of 0.0993 for RSSVR. Similarly, during the test stage, the RSANF simulation acquired a PI of 0.0904, which was fewer than the PI of 0.1038 related to RSSVR. The constituents mentioned above offer a new approach to enhance the precision of forecasting models and further our comprehension of predicting the Sm.
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spelling doaj-art-7a7693687d9a41349edf2b6a544fd2e72025-02-12T08:47:31ZengBilijipub publisherAdvances in Engineering and Intelligence Systems2821-02632023-12-0100204233310.22034/aeis.2023.412563.1127186522Application of Fuzzy System on Settlement of Shallow Footing on Granular SoilSoroush Lesani0Department of Civil Engineering, Iran University of Science and Technology, Tehran, 1684613114, IranThe complex characteristics of cohesionless soil texture necessitate an examination of settlement simulation in cohesionless materials, making it a fundamental area of inquiry. This article discusses the development of integrated data intelligence algorithms with the objective of improving the reliability and accuracy of estimate results for shallow foundations (Sm) on cohesionless soils. The proposed models integrate the reptile search algorithm (RSA) with support vector regression (SVR) analysis and adaptive neuro-fuzzy inference system (ANFIS). Based on the findings of the research, it can be seen that the RSSVR and RSANF systems have shown adept capabilities in the domain of estimate. During the training stage, the RSANF simulation gained the smallest performance index (PI) value of 0.0668, which was smaller than the PI of 0.0993 for RSSVR. Similarly, during the test stage, the RSANF simulation acquired a PI of 0.0904, which was fewer than the PI of 0.1038 related to RSSVR. The constituents mentioned above offer a new approach to enhance the precision of forecasting models and further our comprehension of predicting the Sm.https://aeis.bilijipub.com/article_186522_14e85597d1444d663e772025f351f4a0.pdfgranular soilshallow footingsettlementmachine learningfuzzy systemreptile search algorithm
spellingShingle Soroush Lesani
Application of Fuzzy System on Settlement of Shallow Footing on Granular Soil
Advances in Engineering and Intelligence Systems
granular soil
shallow footing
settlement
machine learning
fuzzy system
reptile search algorithm
title Application of Fuzzy System on Settlement of Shallow Footing on Granular Soil
title_full Application of Fuzzy System on Settlement of Shallow Footing on Granular Soil
title_fullStr Application of Fuzzy System on Settlement of Shallow Footing on Granular Soil
title_full_unstemmed Application of Fuzzy System on Settlement of Shallow Footing on Granular Soil
title_short Application of Fuzzy System on Settlement of Shallow Footing on Granular Soil
title_sort application of fuzzy system on settlement of shallow footing on granular soil
topic granular soil
shallow footing
settlement
machine learning
fuzzy system
reptile search algorithm
url https://aeis.bilijipub.com/article_186522_14e85597d1444d663e772025f351f4a0.pdf
work_keys_str_mv AT soroushlesani applicationoffuzzysystemonsettlementofshallowfootingongranularsoil