An Improved KNearest Neighbor Algorithm
Method Using Finite Boreholes for Predicting FullArea Geological Features

ZHU Junsheng, WANG Sheng, BAI Jun, XU Zhengxuan, CHEN Minghao, LI Zhaoqi, LIU Xin, ZHANG Zihao, LIU Xingyi

doi:10.3973/j.issn.2096-4498.2023.S2.039

Tunnel Construction >

2023 , Vol. 43 >Issue S2: 348 - 358

DOI: https://doi.org/10.3973/j.issn.2096-4498.2023.S2.039

An Improved KNearest Neighbor Algorithm Method Using Finite Boreholes for Predicting FullArea Geological Features

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(1. State Key Laboratory of Geohazard Prevention and Geo-environment Protection, Chengdu University of Technology, Chengdu 610059, Sichuan, China; 2. China Railway Eryuan Engineering Group Co., Ltd., Chengdu 610031, China; 3. Water Conservancy and Electric Power Survey and Design Co., Ltd., Deyang 618000, Sichuan, China)

Online published: 2024-03-28

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Abstract

The original drilling data collected cannot be deeply excavated and utilized by traditional modeling methods. Therefore, an improved Knearest neighbor(KNN) algorithm is improved. This is a spatial adaptive interpolation fitting algorithm that is developed based on the original KNN algorithm. It incorporates automatic selection of 〖WT5BX〗k〖WT〗〖WT５《TNR》〗values based on different geological layers and utilizes the original geological data for further analysis. The data from a railway investigation project is selected as a data source to put into the improved KNN algorithm model, successfully obtaining the characteristic 〖WT5BX〗k〖WT〗〖WT5《TNR》〗values of each stratum in the site and accomplishing the geological modeling. By comparing the actual borehole and the borehole predicted by original KNN and improved KNN, it is found that the improved KNN algorithm is more accurate in predicting the thin layers, and the overall accuracy is higher. Compared with the original KNN algorithm and other common classification algorithms, the improved algorithm can obtain better stratum prediction results, especially for the thin stratum, and obtain higher precision and accuracy, which can better guide the prediction of underground 3D space.

Key words： machine learning; Knearest neighbor; prediction of fullarea geological features; geological modeling; drilling data

Cite this article

ZHU Junsheng, WANG Sheng, BAI Jun, XU Zhengxuan, CHEN Minghao, LI Zhaoqi, LIU Xin, ZHANG Zihao, LIU Xingyi . An Improved KNearest Neighbor Algorithm Method Using Finite Boreholes for Predicting FullArea Geological Features[J]. Tunnel Construction, 2023 , 43(S2) : 348 -358 . DOI: 10.3973/j.issn.2096-4498.2023.S2.039

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