用人工神经网络确定路基和颗粒基层的加州承载比

IF 1.3 Q3 ENGINEERING, MULTIDISCIPLINARY

International Journal of Engineering and Technology Innovation Pub Date : 2023-07-04 DOI:10.46604/ijeti.2023.11053

Jose Manuel Palomino Ojeda, Billy Alexis Cayatopa Calderon, Lenin Quiñones Huatangari, Wilmer Rojas Pintado

{"title":"用人工神经网络确定路基和颗粒基层的加州承载比","authors":"Jose Manuel Palomino Ojeda, Billy Alexis Cayatopa Calderon, Lenin Quiñones Huatangari, Wilmer Rojas Pintado","doi":"10.46604/ijeti.2023.11053","DOIUrl":null,"url":null,"abstract":"The objective of the research is to estimate the value of the California bearing ratio (CBR) through the application of ANN. The methodology consists of creating a database with soil index and CBR variables of the subgrades and granular base of pavements in Jaen, Peru, carried out in the soil mechanics laboratories of the city and the National University of Jaen. In addition, the Python library Seaborn is for variable selection and relevance, and the scikit-learn and Keras libraries were used for the learning, training, and validation stage. Five ANN are proposed to estimate the CBR value, obtaining an error of 4.47% in the validation stage. It can be concluded that this method is effective and valid to determine the CBR value in subgrades and granular bases of any pavement for its evaluation or design.","PeriodicalId":43808,"journal":{"name":"International Journal of Engineering and Technology Innovation","volume":"399 7","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Determination of the California Bearing Ratio of the Subgrade and Granular Base Using Artificial Neural Networks\",\"authors\":\"Jose Manuel Palomino Ojeda, Billy Alexis Cayatopa Calderon, Lenin Quiñones Huatangari, Wilmer Rojas Pintado\",\"doi\":\"10.46604/ijeti.2023.11053\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The objective of the research is to estimate the value of the California bearing ratio (CBR) through the application of ANN. The methodology consists of creating a database with soil index and CBR variables of the subgrades and granular base of pavements in Jaen, Peru, carried out in the soil mechanics laboratories of the city and the National University of Jaen. In addition, the Python library Seaborn is for variable selection and relevance, and the scikit-learn and Keras libraries were used for the learning, training, and validation stage. Five ANN are proposed to estimate the CBR value, obtaining an error of 4.47% in the validation stage. It can be concluded that this method is effective and valid to determine the CBR value in subgrades and granular bases of any pavement for its evaluation or design.\",\"PeriodicalId\":43808,\"journal\":{\"name\":\"International Journal of Engineering and Technology Innovation\",\"volume\":\"399 7\",\"pages\":\"\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2023-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Engineering and Technology Innovation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46604/ijeti.2023.11053\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Engineering and Technology Innovation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46604/ijeti.2023.11053","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}

引用次数: 0

摘要

本研究的目的是通过应用人工神经网络来估计加州承载比（CBR）的值。该方法包括创建一个数据库，其中包含秘鲁Jaen市土壤力学实验室和Jaen国立大学进行的路基和路面颗粒基层的土壤指数和CBR变量。此外，Python库Seaborn用于变量选择和相关性，scikit-learn和Keras库用于学习、培训和验证阶段。提出了五种人工神经网络来估计CBR值，在验证阶段获得了4.47%的误差。可以得出结论，该方法对确定任何路面路基和颗粒基层的CBR值进行评估或设计都是有效的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Determination of the California Bearing Ratio of the Subgrade and Granular Base Using Artificial Neural Networks

The objective of the research is to estimate the value of the California bearing ratio (CBR) through the application of ANN. The methodology consists of creating a database with soil index and CBR variables of the subgrades and granular base of pavements in Jaen, Peru, carried out in the soil mechanics laboratories of the city and the National University of Jaen. In addition, the Python library Seaborn is for variable selection and relevance, and the scikit-learn and Keras libraries were used for the learning, training, and validation stage. Five ANN are proposed to estimate the CBR value, obtaining an error of 4.47% in the validation stage. It can be concluded that this method is effective and valid to determine the CBR value in subgrades and granular bases of any pavement for its evaluation or design.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

International Journal of Engineering and Technology Innovation ENGINEERING, MULTIDISCIPLINARY-

CiteScore

2.80

自引率

0.00%

发文量

审稿时长

12 weeks

期刊介绍： The IJETI journal focus on the field of engineering and technology Innovation. And it publishes original papers including but not limited to the following fields: Automation Engineering Civil Engineering Control Engineering Electric Engineering Electronic Engineering Green Technology Information Engineering Mechanical Engineering Material Engineering Mechatronics and Robotics Engineering Nanotechnology Optic Engineering Sport Science and Technology Innovation Management Other Engineering and Technology Related Topics.