Data Mining Method for Bank Slope Monitoring Based on Association Rules

CHEN Bo; ZHAN Ming-qiang; HUANG Zi-shen

doi:10.11988/ckyyb.20210457

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Journal of Changjiang River Scientific Research Institute ›› 2022, Vol. 39 ›› Issue (8) : 58-64. DOI: 10.11988/ckyyb.20210457

ENGINEERING SAFETY AND DISASTER PREVENTION

Data Mining Method for Bank Slope Monitoring Based on Association Rules

CHEN Bo^1,2, ZHAN Ming-qiang^1,2, HUANG Zi-shen³

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Abstract

The monitoring data of slope records the whole process information of slope instability disaster.The data mining of bank slope monitoring database runs slowly.FP-Growth association rule algorithm is introduced into slope safety monitoring data mining.The causal association rule and spatial association rule in slope monitoring data are mined by FP-Growth association rule algorithm.The causality between environmental variables and affected variables of slope monitoring and the correlation among affected variables of multiple measuring points are mined respectively.Effective information reflecting slope operation characteristics is extracted from slope spatio-temporal monitoring data containing multi-measuring points and multi-items.Calculation example shows that FP-Growth association rule algorithm is simple in implementation and reliable in mining results,hence providing a good approach for monitoring data mining of similar reservoir bank slopes.

Key words

reservoir bank slope monitoring / data mining / FP-Growth algorithm / cause-effect association rule / spatial association rule

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CHEN Bo, ZHAN Ming-qiang, HUANG Zi-shen. Data Mining Method for Bank Slope Monitoring Based on Association Rules[J]. Journal of Changjiang River Scientific Research Institute. 2022, 39(8): 58-64 https://doi.org/10.11988/ckyyb.20210457

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