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Rockburst prediction based on multi-featured drilling parameters and extreme tree algorithm for full-section excavated tunnel faces

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Journal of Rock Mechanics and Geotechnical Engineering 2025年第1期17卷 258-274页

作者： wenhao yi Mingnian Wang Qinyong Xia Yongyi He Hongqiang Sun School of Civil Engineering Southwest Jiaotong UniversityChengdu610031China Key Laboratory of Transportation Tunnel Engineering Ministry of EducationSouthwest Jiaotong UniversityChengdu610031China China Railway Third Bureau Group Co. Ltd.Taiyuan030001China

The suddenness, uncertainty, and randomness of rockbursts directly affect the safety of tunnel construction. The prediction of rockbursts is a fundamental aspect of mitigating or even eliminating rockburst hazards. To address the shortcomings of the current rockburst prediction models, which have a limited number of samples and rely on manual test results as the majority of their input features, this paper proposes rockburst prediction models based on multi-featured drilling parameters of rock drilling jumbo. Firstly, four original drilling parameters, namely hammer pressure (Ph), feed pressure (Pf), rotation pressure (Pr), and feed speed (VP), together with the rockburst grades, were collected from 1093 rockburst cases. Then, a feature expansion investigation was performed based on the four original drilling parameters to establish a drilling parameter feature system and a rockburst prediction database containing 42 features. Furthermore, rockburst prediction models based on multi-featured drilling parameters were developed using the extreme tree (ET) algorithm and Bayesian optimization. The models take drilling parameters as input parameters and rockburst grades as output parameters. The effects of Bayesian optimization and the number of drilling parameter features on the model performance were analyzed using the accuracy, precision, recall and F1 value of the prediction set as the model performance evaluation indices. The results show that the Bayesian optimized model with 42 drilling parameter features as inputs performs best, with an accuracy of 91.89%. Finally, the reliability of the models was validated through field tests.

关键词： Rockburst prediction Drilling parameters Feature system Extreme tree(ET) Bayesian optimization

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Intelligent classification model of surrounding rock of tunnel using drilling and blasting method

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Underground Space 2021年第5期6卷 539-550页

作者： Mingnian Wang Siguang Zhao Jianjun Tong Zhilong Wang Meng Yao Jiawang Li wenhao yi Key Laboratory of Transportation Tunnel Engineering Ministry of EducationSouthwest Jiaotong UniversityChengdu 610031China School of Civil Engineering Southwest Jiaotong UniversityChengdu 610031China

Classification of surrounding rock is the cornerstone of tunnel design and *** traditional methods are mainly qualitative and manual and require extensive professional knowledge and engineering *** minimize the effect of the empirical judgment on the accuracy of surrounding rock classification,it is necessary to reduce human *** intelligent classification technique based on information technology and artificial intelligence could overcome these *** this regard,using 299 groups of drilling parameters collected automatically using intelligent drill jumbos in tunnels for the Zhengzhou-Wanzhou high-speed railway in China,an intelligent-classification surrounding-rock database is constructed in this *** on a machine learning algorithm,an intelligent classification model is then developed,which has an overall accuracy of 91.9%.Finally,using the core of the model,the intelligent classification system for the surrounding rock of drilled and blasted tunnels is integrated,and the system is carried by intelligent jumbos to perform automatic recording and transmission of drilling parameters and intelligent classification of the surrounding *** approach provides a foundation for the dynamic design and construction(both conventional and intelligent)of tunnels.

关键词： Drilled and blasted tunnel Drilling parameter Machine learning Intelligent classification Surrounding rock

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Heterogeneity identification method for surrounding rock of large-section rock tunnel faces based on support vector machine

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Railway Sciences 2023年第1期2卷 48-67页

作者： wenhao yi Mingnian Wang Jianjun Tong Siguang Zhao Jiawang Li Dengbin Gui Xiao Zhang Southwest Jiaotong University ChengduChina

Purpose–The purpose of the study is to quickly identify significant heterogeneity of surrounding rock of tunnel face that generally occurs during the construction of large-section rock tunnels of high-speed ***/methodology/approach–Relying on the support vector machine(SVM)-based classification model,the nominal classification of blastholes and nominal zoning and classification terms were used to demonstrate the heterogeneity identification method for the surrounding rock of tunnel face,and the identification calculation was carried out for the five test ***,the suggestions for local optimization of the support structures of large-section rock tunnels were put ***–The results show that compared with the two classification models based on neural networks,the SVM-based classification model has a higher classification accuracy when the sample size is small,and the average accuracy can reach 87.9%.After the samples are replaced,the SVM-based classification model can still reach the same accuracy,whose generalization ability is ***/value–By applying the identification method described in this paper,the significant heterogeneity characteristics of the surrounding rock in the process of two times of blasting were identified,and the identification results are basically consistent with the actual situation of the tunnel face at the end of blasting,and can provide a basis for local optimization of support parameters.

关键词： Rock tunnel Surrounding rock Heterogeneity Support vector machine High-speed railway

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混凝土模拟孔溶液中外加电流阴极保护对阳极体系的酸化侵蚀效应

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材料研究学报 2016年第12期30卷 931-939页

作者：王羊洋胡捷郭文昊赵翼韦江雄余其俊华南理工大学材料科学与工程学院广州510640 广东省建筑材料低碳技术工程技术研究中心广州510640

测定了外加电流阴极保护技术作用下混凝土模拟孔溶液的p H值变化,建立了通电量Q与混凝土模拟孔溶液中氢氧根浓度cOH-的定量关系,量化表征了钛网阳极表面的腐蚀产物。结果表明,相同极化时间条件下,电流密度越高,阳极区模拟孔溶液中cOH-越... 详细信息

测定了外加电流阴极保护技术作用下混凝土模拟孔溶液的p H值变化,建立了通电量Q与混凝土模拟孔溶液中氢氧根浓度cOH-的定量关系,量化表征了钛网阳极表面的腐蚀产物。结果表明,相同极化时间条件下,电流密度越高,阳极区模拟孔溶液中cOH-越低,钛网表面腐蚀产物越多;相同极化电流密度条件下,含Cl-模拟孔溶液中OH-消耗速率要大于无Cl-模拟孔溶液中OH-消耗速率;外加电流阴极保护过程中混凝土模拟孔溶液cOH-与Q之间的关系符合Logistic回归方程,基于该方程可预测外加电流阴极保护技术中外部阳极处的p H下降程度,进而评估其对阳极体系的酸化侵蚀作用。

关键词：材料失效与保护外加电流阴极保护混凝土模拟孔溶液外部阳极酸化侵蚀

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Extended exPerience of retroPeritoneoscoPic live donor nePhrectomy in a single center

Extended exPerience of retroPeritoneoscoPic live donor nePhr...

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第十六届全国泌尿外科学术会议

作者： Jianfei Ye,Lulin Ma,wenhao Tang,yi Huang,Lei Zhao, Xiaofei Hou,Guoliang Wang DePartment of Urology,Peking University Third HosPital, Beijing,100191.100191

PurPose:To review our 5-year exPerience of retroPeritoneoscoPic live donor nePhrectomy(RPLDN). Patients and Methods:Between December 2003 and March 2009,114 related renal donors underwent consecutive

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基于多元地质信息的钻爆法隧道围岩级别智能判识及软件系统

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隧道建设(中英文) 2024年第12期44卷 2451-2468,I0053-I0070页

作者：王明年童建军易文豪彭鑫西南交通大学土木工程学院四川成都610031 极端环境岩土和隧道工程智能建养全国重点实验室四川成都610031

为提升施工阶段围岩级别判识的智能化水平,提升围岩级别智能判识的准确性,提出一种基于多元地质信息和信息融合的围岩级别智能判识方法,并开发基于多元地质信息的钻爆法隧道围岩级别智能判识软件系统,实现隧道工程多元信息的自动采集和... 详细信息

为提升施工阶段围岩级别判识的智能化水平,提升围岩级别智能判识的准确性,提出一种基于多元地质信息和信息融合的围岩级别智能判识方法,并开发基于多元地质信息的钻爆法隧道围岩级别智能判识软件系统,实现隧道工程多元信息的自动采集和围岩级别自动化判识。依托我国西部山区隧道工程,采集随钻参数、掌子面高清数码图像、超前地质预报信息、地勘信息等4项多元地质信息,开展数据标准化、结构化处理及特征提取,构建基于多元地质信息的围岩级别智能判识模型,共判定844个断面的围岩级别,模型平均准确率达到95.45%,平均精确率为95.05%,平均召回率为93.25%,平均F_(1)分数为94.14%,对软硬不均及局部破碎围岩具有较好的识别效果。

关键词：钻爆法隧道多元地质信息围岩级别智能判识图像识别信息融合

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Partial multi-label learning via label-specific feature corrections

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Science China(Information Sciences) 2025年第03期68卷 95-109页

作者： Jun-yi HANG Min-Ling ZHANG School of Computer Science and Engineering Southeast University Key Laboratory of Computer Network and Information Integration(Southeast University) Ministry of Education

Partial multi-label learning（PML） allows learning from rich-semantic objects with inaccurate annotations, where a set of candidate labels are assigned to each training example but only some of them are valid. Existing approaches rely on disambiguation to tackle the PML problem, which aims to correct noisy candidate labels by recovering the ground-truth labeling information ahead of prediction model induction. However, this dominant strategy might be suboptimal as it usually needs extra assumptions that cannot be fully satisfied in real-world scenarios. Instead of label correction, we investigate another strategy to tackle the PML problem, where the potential ambiguity in PML data is eliminated by correcting instance features in a label-specific manner. Accordingly, a simple yet effective approach named PASE, i.e., partial multi-label learning via label-specific feature corrections, is proposed. Under a meta-learning framework, PASElearns to exert label-specific feature corrections so that potential ambiguity specific to each class label can be eliminated and the desired prediction model can be induced on these corrected instance features with the provided candidate labels. Comprehensive experiments on a wide range of synthetic and real-world data sets validate the effectiveness of the proposed approach.

关键词： machine learning multi-label learning partial multi-label learning label-specific features feature correction

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General synthesis of a dual-atomic-site catalyst library

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Science China Materials 2025年第2期68卷 679-680页

作者： Jingfang Zhang yi Huang School of Chemical Engineering&Pharmacy Wuhan Institute of TechnologyWuhan 430205China College of Chemistry Central China Normal UniversityWuhan 430079China

Single-atom catalysts(SACs),as a bridge between homogeneous and heterogeneous catalysts,have attracted tremendous attention over the past *** atomically dispersed metal active sites,SACs possess maximum atom utilization efficiency and exceptionally high activity towards various catalytic reactions[1].Compared with their nanoparticle counterparts,the unique but uniform configurations of the catalytic sites endow SACs with great potential for mechanism investigation at the atomic level[2,3].Despite of these advantages,SACs are facing the problem of linear scaling relations between intermediates in terms of complicated reactions involving co-adsorption of *** is difficult for a single-atom site to participate in all catalytic steps with high efficiencies,especially for some reactions that need adjacent active sites[4].In this regard,dualatomic-site catalysts(DACs)are emerging as a fascinating frontier in heterogeneous catalysis[5].It has been verified that the synergistic effect of the adjacent atomic pairs in DACs can break the linear scaling relations and optimize the adsorption energy of different intermediates,thus improving the intrinsic catalytic ***,it is of great significance to develop a general synthetic strategy for DACs.

关键词： atomic adsorption synthesis

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Seismic isolation design and resilience improvement of railway station considering the influence of near-fault pulse-like ground motions

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Earthquake Engineering and Engineering Vibration 2025年第1期24卷 257-270页

作者： Pan yi Song Jiayu Chen Qi Liu Yongxin School of Civil Engineering Southwest Jiaotong UniversityChengdu 610031China Key Laboratory of Seismic Engineering of Sichuan Province Chengdu 610031China

To improve the resilience of railway stations,a typical station was selected as the research object,and an isolation design was ***-four groups of near-fault pulse-like ground motions were *** seismic resilience of the no-isolation railway stations(NIRS)and the isolation railway stations(IRS)were compared to provide a numerical result of the improvement in *** results show that in the station isolation design,the station's functional requirements and structural characteristics should be considered and the appropriate placement of isolation bearings is under the waiting *** the action of a rare earthquake,the repair cost,repair time,rate of harm and death of the IRS were decreased by 8.04 million,18.30 days,6.93×10^(-3)and 1.21×10^(-3),respectively,when compared to the *** IRS received a seismic resilience grade of three-stars and the NIRS only one-star,indicating that rational isolation design improves the seismic resilience of ***,for the design of stations close to earthquake faults,it is suggested to utilize appropriate isolation techniques to improve their seismic resilience.

关键词： railway station near-fault pulse-like ground motion isolation design seismic resilience resilience improvement

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Constrained Networked Predictive Control for Nonlinear Systems Using a High-Order Fully Actuated System Approach

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 478-480页

作者： yi Huang Guo-Ping Liu yi Yu Wenshan Hu the School of Electrical Engineering and Automation Wuhan University IEEE the Center for Control Science and Technology Southern University of Science and Technology the Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University

Dear Editor,In this letter, a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated (HOFA) systems with noises. The method can effectively deal with nonlinearities, constraints, and noises in the system, optimize the performance metric, and present an upper bound on the stable output of the system.

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