文献类型：期刊文献

英文题名：Slope Sliding Force Prediction via Belief Rule-Based Inferential Methodology

作者：Feng, Jing[1];Xu, Xiaobin[1];Liu, Pan[1];Ma, Peng[2];Ma, Chengrong[3];Tao, Zhigang[4,5]

机构：[1]Hangzhou Dianzi Univ, Sch Automat, Hangzhou 310018, Peoples R China;[2]Nanjing Smart Waterway Corp Ltd, Nanjing 210000, Peoples R China;[3]Shaoxing Univ, Coll Civil Engn, Shaoxing 312000, Peoples R China;[4]State Key Lab Geomech & Deep Underground Engn, Beijing 100083, Peoples R China;[5]China Univ Min & Technol, Sch Mech & Civil Engn, Beijing 100083, Peoples R China

年份：2021

卷号：14

期号：1

起止页码：965

外文期刊名：INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS

收录：SCI-EXPANDED(收录号：WOS:000629154200001)、、EI(收录号：20211310142360)、Scopus(收录号：2-s2.0-85103091553)、WOS

基金：This work was supported by the Zhejiang Province Key R&D projects (No.2019C03104), the NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization (No.U1709215), the Zhejiang Provincial Basic Public Welfare Research Project (No. LGF21F020013), the Open Research Project of the State Key Laboratory of Industrial Control Technology, Zhejiang University, China (No. ICT20028), the Second Tibetan Plateau Scientific Expedition and Research Program (No. 2019QZKK0707), the NSFC (No. 61751304).

语种：英文

外文关键词：Slope landslide; Sliding force; Belief rule base; SLP optimization algorithm; West-East Gas Pipeline Project

外文摘要：Slope sliding force can be measured by an anchor cable sensor with the negative Poisson's ratio (NPR) property. It is capable of reflecting the stability of the slope intuitively. Thus, predicting the variation trend of the sliding force is able to achieve early warning for landslide disaster, thereby avoiding losses to the lives and property of the people. In this paper, due to the uncertain variation of the sliding force, a belief rule-based (BRB) sliding force prediction model is established to describe the nonlinear and uncertain relationship between the history/current sliding force and the future sliding force. In this model, the activated belief rules are fused by adopting the evidence reasoning (ER) algorithm. And based on the fused results, the sliding force at a future time can be predicted accurately. Moreover, considering the variation of the sliding force on different slopes or different monitoring points in the same slope, a parameter transfer strategy of BRB model together with a corresponding online update method are proposed to achieve the adaptive design of the BRB prediction model. Finally, the effectiveness of the proposed sliding force prediction methods has been verified by experiments on the sub-section of the China West-East Gas Pipeline Project. (C) 2021 The Authors. Published by Atlantis Press B.V.