Soil Consistency Prediction Based on Cone Penetration Test (CPT) Using ANN (Artificial Neural Network) and Multinomial Regression (Case Study: Surabaya Region)

Soil Consistency Prediction Based on Cone Penetration Test (CPT) Using ANN (Artificial Neural Network) and Multinomial Regression (Case Study: Surabaya Region)

The development of Surabaya city can be seen from the many developments in the town. Many soil investigation tests have been carried out with the many products that have been and will be carried out in Surabaya. One of the soil investigation tests is the Sondir test, the CPT (cone penetration test)....

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Published in:Lecture Notes in Civil Engineering
Main Author: Wahyuni F.; Wildani Z.; Purnamasari R.
Format: Conference paper
Language:English
Published: Springer Science and Business Media Deutschland GmbH 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200354705&doi=10.1007%2f978-981-97-0751-5_51&partnerID=40&md5=4bf4558afb623113b422fcce1c8cc40a
id 2-s2.0-85200354705
spelling 2-s2.0-85200354705
Wahyuni F.; Wildani Z.; Purnamasari R.
Soil Consistency Prediction Based on Cone Penetration Test (CPT) Using ANN (Artificial Neural Network) and Multinomial Regression (Case Study: Surabaya Region)
2024
Lecture Notes in Civil Engineering
466

10.1007/978-981-97-0751-5_51
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200354705&doi=10.1007%2f978-981-97-0751-5_51&partnerID=40&md5=4bf4558afb623113b422fcce1c8cc40a
The development of Surabaya city can be seen from the many developments in the town. Many soil investigation tests have been carried out with the many products that have been and will be carried out in Surabaya. One of the soil investigation tests is the Sondir test, the CPT (cone penetration test). CPT is a soil investigation method that is quite affordable and easy to do, which produces parameters in the form of soil consistency at each soil depth. Based on soil data from 2017 to 2021, CPT data is spread across various areas in Surabaya. Thus, this research aims to find predictions of soil consistency in the Surabaya area from existing soil data using the ANN (artificial neural network) and multinomial logistic regression methods. From this study, it was found that from 3196 scattered soil data, it showed that the coefficient of determination (R2) was 98.44%. This means that the proportion of the variability of Depth (m), Qonus value (qu), and Area can explain the consistency of the soil and is an excellent model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Springer Science and Business Media Deutschland GmbH
23662557
English
Conference paper
author Wahyuni F.; Wildani Z.; Purnamasari R.
spellingShingle Wahyuni F.; Wildani Z.; Purnamasari R.
Soil Consistency Prediction Based on Cone Penetration Test (CPT) Using ANN (Artificial Neural Network) and Multinomial Regression (Case Study: Surabaya Region)
author_facet Wahyuni F.; Wildani Z.; Purnamasari R.
author_sort Wahyuni F.; Wildani Z.; Purnamasari R.
title Soil Consistency Prediction Based on Cone Penetration Test (CPT) Using ANN (Artificial Neural Network) and Multinomial Regression (Case Study: Surabaya Region)
title_short Soil Consistency Prediction Based on Cone Penetration Test (CPT) Using ANN (Artificial Neural Network) and Multinomial Regression (Case Study: Surabaya Region)
title_full Soil Consistency Prediction Based on Cone Penetration Test (CPT) Using ANN (Artificial Neural Network) and Multinomial Regression (Case Study: Surabaya Region)
title_fullStr Soil Consistency Prediction Based on Cone Penetration Test (CPT) Using ANN (Artificial Neural Network) and Multinomial Regression (Case Study: Surabaya Region)
title_full_unstemmed Soil Consistency Prediction Based on Cone Penetration Test (CPT) Using ANN (Artificial Neural Network) and Multinomial Regression (Case Study: Surabaya Region)
title_sort Soil Consistency Prediction Based on Cone Penetration Test (CPT) Using ANN (Artificial Neural Network) and Multinomial Regression (Case Study: Surabaya Region)
publishDate 2024
container_title Lecture Notes in Civil Engineering
container_volume 466
container_issue
doi_str_mv 10.1007/978-981-97-0751-5_51
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85200354705&doi=10.1007%2f978-981-97-0751-5_51&partnerID=40&md5=4bf4558afb623113b422fcce1c8cc40a
description The development of Surabaya city can be seen from the many developments in the town. Many soil investigation tests have been carried out with the many products that have been and will be carried out in Surabaya. One of the soil investigation tests is the Sondir test, the CPT (cone penetration test). CPT is a soil investigation method that is quite affordable and easy to do, which produces parameters in the form of soil consistency at each soil depth. Based on soil data from 2017 to 2021, CPT data is spread across various areas in Surabaya. Thus, this research aims to find predictions of soil consistency in the Surabaya area from existing soil data using the ANN (artificial neural network) and multinomial logistic regression methods. From this study, it was found that from 3196 scattered soil data, it showed that the coefficient of determination (R2) was 98.44%. This means that the proportion of the variability of Depth (m), Qonus value (qu), and Area can explain the consistency of the soil and is an excellent model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
publisher Springer Science and Business Media Deutschland GmbH
issn 23662557
language English
format Conference paper
accesstype
record_format scopus
collection Scopus
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