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Novel rockburst prediction criterion with enhanced explainability employing CatBoost and nature-inspired metaheuristic technique

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Underground Space 2024年第6期19卷 101-118页

作者： yingui qiu Jian Zhou School of Resources and Safety Engineering Central South UniversityChangsha 410083China

Rockburst is a major challenge to hard rock engineering at great *** and timely assessment of rockburst risk can avoid unnecessary casualties and property *** the existence of various methods for rockburst assessment,there remains an urgent need for a comprehensive and reliable criterion that is easy to both apply and *** a new rockburst criterion based on simple parameters can potentially fill this *** its advantages,this criterion can facilitate a more effective and efficient prediction of rockburst potential,thereby contributing significantly to enhancing safety *** this paper,combined with the internal and external factors of rockburst,four control variables(i.e.,integrity index,stress index,brittleness index,and elastic energy index)were selected to be incorporated into a comprehensive rockburstability index(RBSI).Based on 116 sets of rockburst cases,the rockburst potential was accurately quantified and predicted using the categorical boosting(CatBoost)model and the nature-inspired metaheuristic African vultures optimization algorithm(AVOA).In its performance validation,the criterion achieved the highest accuracy of 90.48%,verifying the reliability and effectiveness of the proposed RBSI ***,an interpretive method was applied to analyze the variable influence on the criterion,facilitating the explanation of predictions and the analysis of the formula’s robustness under different *** general,compared with existing criterion methods involving relevant indicators,the newly proposed RBSI criterion enhances the accuracy of rockburst potential prediction,and it can effectively and swiftly evaluate the preliminary risk of ***,a graphical user interface was developed to provide a clear visualization of the assessment of rockburst potential.

关键词： Rockburst criterion CatBoost Metaheuristic optimization Model interpretation Graphical user interface

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A true triaxial strength criterion for rocks by gene expression programming

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Journal of Rock Mechanics and Geotechnical Engineering 2023年第10期15卷 2508-2520页

作者： Jian Zhou Rui Zhang yingui qiu Manoj Khandelwal School of Resources and Safety Engineering Central South UniversityChangsha410083China Institute of Innovation Science and SustainabilityFederation University AustraliaBallaratVIC3350Australia

Rock strength is a crucial factor to consider when designing and constructing underground *** study utilizes a gene expression programming(GEP)algorithm-based model to predict the true triaxial strength of rocks,taking into account the influence of rock genesis on their mechanical behavior during the model building process.A true triaxial strength criterion based on the GEP model for igneous,metamorphic and magmatic rocks was obtained by training the model using collected *** to the modified Weibols-Cook criterion,the modified Mohr-Coulomb criterion,and the modified Lade criterion,the strength criterion based on the GEP model exhibits superior prediction accuracy *** strength criterion based on the GEP model has better performance in R2,RMSE and MAPE for the data set used in this ***,the strength criterion based on the GEP model shows greater stability in predicting the true triaxial strength of rocks across different *** to the existing strength criterion based on the genetic programming(GP)model,the proposed criterion based on GEP model achieves more accurate predictions of the variation of true triaxial strength(s1)with intermediate principal stress(s2).Finally,based on the Sobol sensitivity analysis technique,the effects of the parameters of the three obtained strength criteria on the true triaxial strength of the rock are *** general,the proposed strength criterion exhibits superior performance in terms of both accuracy and stability of prediction results.

关键词： Gene expression programming(GEP) True triaxial strength Rock failure criteria Intermediate principal stress

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An Optimized System of Random Forest Model by Global Harmony Search with Generalized Opposition-Based Learning for Forecasting TBM Advance Rate

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2873-2897页

作者： yingui qiu Shuai Huang Danial Jahed Armaghani Biswajeet Pradhan Annan Zhou Jian Zhou School of Resources and Safety Engineering Central South UniversityChangsha410083China School of Civil and Environmental Engineering University of Technology SydneyNew South WalesAustralia Centre for Advanced Modelling and Geospatial Information Systems School of Civil and Environmental EngineeringFaculty of Engineering and Information TechnologyUniversity of Technology SydneyNew SouthWalesAustralia Civil and Infrastructure Engineering Discipline School of EngineeringRoyal Melbourne Institute of Technology(RMIT)MelbourneVictoria3001Australia

As massive underground projects have become popular in dense urban cities,a problem has arisen:which model predicts the best for Tunnel Boring Machine(TBM)performance in these tunneling projects?However,performance level of TBMs in complex geological conditions is still a great challenge for practitioners and *** the other hand,a reliable and accurate prediction of TBM performance is essential to planning an applicable tunnel construction *** performance of TBM is very difficult to estimate due to various geotechnical and geological factors and machine *** previously-proposed intelligent techniques in this field are mostly based on a single or base model with a low level of ***,this study aims to introduce a hybrid randomforest(RF)technique optimized by global harmony search with generalized oppositionbased learning(GOGHS)for forecasting TBM advance rate(AR).Optimizing the RF hyper-parameters in terms of,e.g.,tree number and maximum tree depth is the main objective of using the GOGHS-RF *** the modelling of this study,a comprehensive databasewith themost influential parameters onTBMtogetherwithTBM AR were used as input and output variables,*** examine the capability and power of the GOGHSRF model,three more hybrid models of particle swarm optimization-RF,genetic algorithm-RF and artificial bee colony-RF were also constructed to forecast TBM *** of the developed models was performed by calculating several performance indices,including determination coefficient(R2),root-mean-square-error(RMSE),and mean-absolute-percentage-error(MAPE).The results showed that theGOGHS-RF is a more accurate technique for estimatingTBMAR compared to the other applied *** newly-developedGOGHS-RFmodel enjoyed R2=0.9937 and 0.9844,respectively,for train and test stages,which are higher than a pre-developed ***,the importance of the input parameters was interpreted through the SHapley Additive exPlanations(SHA

关键词： Tunnel boring machine random forest GOGHS optimization PSO optimization GA optimization ABC optimization SHAP

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Estimation of the TBM advance rate under hard rock conditions using XGBoost and Bayesian optimization

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Underground Space 2021年第5期6卷 506-515页

作者： Jian Zhou yingui qiu Shuangli Zhu Danial Jahed Armaghani Manoj Khandelwal Edy Tonnizam Mohamad School of Resources and Safety Engineering Central South UniversityChangsha 410083China Department of Civil Engineering Faculty of EngineeringUniversity of Malaya50603 Kuala LumpurMalaysia School of Engineering Information Technology and Physical SciencesFederation University AustraliaBallaratAustralia Centre of Tropical Geoengineering(GEOTROPIK) School of Civil EngineeringFaculty of EngineeringUniversiti Teknologi Malaysia81310 Johor BahruMalaysia

The advance rate(AR)of a tunnel boring machine(TBM)under hard rock conditions is a key parameter in the successful implementation of tunneling *** this study,we improved the accuracy of prediction models by employing a hybrid model of extreme gradient boosting(XGBoost)with Bayesian optimization(BO)to model the TBM *** develop the proposed models,1286 sets of data were collected from the Peng Selangor Raw Water Transfer tunnel project in *** database consists of rock mass and intact rock features,including rock mass rating,rock quality designation,weathered zone,uniaxial compressive strength,and Brazilian tensile *** specifications,including revolution per minute and thrust force,were considered to predict the TBM *** accuracies of the predictive models were examined using the root mean squares error(RMSE)and the coefficient of determination(R^(2))between the observed and predicted yield by employing a five-fold cross-validation *** showed that the BO algorithm can capture better hyper-parameters for the XGBoost prediction model than can the default XGBoost *** robustness and generalization of the BO-XGBoost model yielded prominent results with RMSE and R^(2) values of 0.0967 and 0.9806(for the testing phase),*** results demonstrated the merits of the proposed BO-XGBoost *** addition,variable importance through mutual information tests was applied to interpret the XGBoost model and demonstrated that machine parameters have the greatest impact as compared to rock mass and material properties.

关键词： TBM performance Advance rate XGBoost Bayesian optimization Predictive modeling

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Predicting TBM penetration rate in hard rock condition:A comparative study among six XGB-based metaheuristic techniques

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Geoscience Frontiers 2021年第3期12卷 201-213页

作者： Jian Zhou yingui qiu Danial Jahed Armaghani Wengang Zhang Chuanqi Li Shuangli Zhu Reza Tarinejad School of Resources and Safety Engineering Central South UniversityChangsha 410083China Institute of Research and Development Duy Tan UniversityDa Nang 550000Vietnam School of Civil Engineering Chongqing UniversityChongqing 400045China Faculty of Civil Engineering University of Tabriz29 Bahman Blvd51666 TabrizIran

A reliable and accurate prediction of the tunnel boring machine(TBM)performance can assist in minimizing the relevant risks of high capital costs and in scheduling tunneling *** research aims to develop six hybrid models of extreme gradient boosting(XGB)which are optimized by gray wolf optimization(GWO),particle swarm optimization(PSO),social spider optimization(SSO),sine cosine algorithm(SCA),multi verse optimization(MVO)and moth flame optimization(MFO),for estimation of the TBM penetration rate(PR).To do this,a comprehensive database with 1286 data samples was established where seven parameters including the rock quality designation,the rock mass rating,Brazilian tensile strength(BTS),rock mass weathering,the uniaxial compressive strength(UCS),revolution per minute and trust force per cutter(TFC),were set as inputs and TBM PR was selected as model *** with the mentioned six hybrid models,four single models i.e.,artificial neural network,random forest regression,XGB and support vector regression were also built to estimate TBM PR for comparison *** models were designed conducting several parametric studies on their most important parameters and then,their performance capacities were assessed through the use of root mean square error,coefficient of determination,mean absolute percentage error,and *** of this study confirmed that the best predictive model of PR goes to the PSO-XGB technique with system error of(0.1453,and 0.1325),R^(2) of(0.951,and 0.951),mean absolute percentage error(4.0689,and 3.8115),and a10-index of(0.9348,and 0.9496)in training and testing phases,*** developed hybrid PSO-XGB can be introduced as an accurate,powerful and applicable technique in the field of TBM performance *** conducting sensitivity analysis,it was found that UCS,BTS and TFC have the deepest impacts on the TBM PR.

关键词： TBM penetration rate Hard rock XGB-based hybrid model Predictive model Metaheuristic optimization

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典型地质条件下采动覆岩变形破坏规律的试验研究

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武汉理工大学学报（信息与管理工程版） 2017年第3期39卷 275-280页

作者：王新丰李隆钦邱引贵湘潭大学岩土力学与工程安全湖南省重点实验室湖南湘潭411105 湘潭大学环境与资源学院湖南湘潭411105 湘潭大学土木工程与力学学院湖南湘潭411105

为了研究典型地质条件下厚煤层采动过程中的覆岩运移规律和顶板破断机理,以某矿16223典型地质工作面的厚煤层开采为工程背景,基于相似原理和量纲分析理论,运用相似模型试验系统分析工作面采动期间的顶板破断过程、垮落形态、覆岩变形特... 详细信息

为了研究典型地质条件下厚煤层采动过程中的覆岩运移规律和顶板破断机理,以某矿16223典型地质工作面的厚煤层开采为工程背景,基于相似原理和量纲分析理论,运用相似模型试验系统分析工作面采动期间的顶板破断过程、垮落形态、覆岩变形特征及应力演化规律。研究表明:采动覆岩具有初始破坏的突发性、中期破坏的阶段性和后期破坏的延展性特征,裂隙发育和贯通过程呈现方向性和区间性特点,覆岩的失稳变形表现出非线性和不连续性,顶板应力在岩层活动的不同时期存在明显的应力分区和不均匀特性。研究结论可为典型地质条件下的煤层开采技术研发和岩层控制措施制定提供借鉴和参考。

关键词：典型地质采动覆岩破坏规律模型试验岩层控制

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基于政策量化的中国耕地保护政策演进过程

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中国土地科学 2020年第7期34卷 69-78页

作者：王文旭曹银贵苏锐清邱敏周伟中国地质大学(北京)土地科学技术学院北京100083 自然资源部土地整治重点实验室北京100035

研究目的:探讨中国耕地保护政策的演进特征和规律,为政策制定提供理论依据和支撑。研究方法:政策文献计量法和内容分析法。研究结果:中国耕地保护政策的政策力度不强、涉及范围较广、政策措施较为丰富、反馈机制不足、监督体系仍需完善... 详细信息

研究目的:探讨中国耕地保护政策的演进特征和规律,为政策制定提供理论依据和支撑。研究方法:政策文献计量法和内容分析法。研究结果:中国耕地保护政策的政策力度不强、涉及范围较广、政策措施较为丰富、反馈机制不足、监督体系仍需完善;政策演进共经历了政策出台早期探索、体系建立探索、体系初步形成、体系基本完善、体系趋于成熟5个阶段,耕地保护内涵实现了“数量—数量、质量—数量、质量、生态”的转变;中国耕地保护政策的政策工具类型逐渐多样化,政策工具的内容逐渐具体、可操作性增强。研究结论:未来应提升政策的整体权威性,完善监督机制;健全多部门协同联动机制,强化“三位一体”保护;进一步丰富政策工具形式,提升耕地保护效率。

关键词：耕地保护政策量化内容分析法政策工具土地利用

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重庆市长寿区旱改水潜力评价与优化研究

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中国农业资源与区划 2022年第12期43卷 172-182页

作者：罗傲蓝何灏曹银贵邱敏中国地质大学(北京)土地科学技术学院重庆市长寿区土地房屋勘测规划院自然资源部土地整治重点实验室

[目的]文章以重庆市长寿区为例，对其旱地改水田潜力进行测算，以期提高耕地质量，促进耕地内部结构调整和占补平衡，保障地区粮食安全和生态系统安全。[方法]基于2010—2018年旱改水空间分布特征研究，构建旱改水适宜性评价模型，该模... 详细信息

[目的]文章以重庆市长寿区为例，对其旱地改水田潜力进行测算，以期提高耕地质量，促进耕地内部结构调整和占补平衡，保障地区粮食安全和生态系统安全。[方法]基于2010—2018年旱改水空间分布特征研究，构建旱改水适宜性评价模型，该模型涵盖地形条件、土壤条件、耕作条件3个评价维度，包括海拔高程、地形坡度、表层土壤质地等10个评价指标。然后利用模型评价旱改水整治潜力，并识别整治的障碍因素，最后基于评价结果，提出旱改水的整治措施建议。[结果]（1） 2010—2018年长寿区旱地改水田整体集中度较高，主要分布在北部和中部地区，其中，密度最高的乡镇是海棠镇、云台镇和葛兰镇。（2）总的来说，重庆市长寿区旱地改水田整体适宜性不高，高度适宜和中度适宜改为水田的旱地面积分别为159.81hm2、8 115.64hm2，两者占全域总面积的25.22%，这些地块主要分布在区域中部、北部的石堰镇、葛兰镇、云台镇等乡镇；勉强适宜和不适宜改为水田的旱地占比为74.78%，这些地块限制性因素较多，难以改造为水田。[结论]综上，未来长寿区可通过改造有效土层厚度低、地形坡度较陡、田块面积小、灌溉保证率低等障碍因素推动耕地旱改水工作。

关键词：耕地利用土地整治旱地改水田空间分布潜力评价

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基于产权效应的耕地保护决策行为分析

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中国农业资源与区划 2022年第7期43卷 74-84页

作者：邱敏何灏曹银贵苏锐清王文旭中国地质大学(北京)土地科学技术学院重庆市长寿区土地房屋勘测规划院自然资源部土地整治重点实验室

[目的]耕地保护是维护国家社会安全、生态安全和粮食安全的重要基石，探讨中国耕地保护决策的演进历程及产权路径，以期为新时代完善耕地保护制度提供理论支撑。[方法]文章基于渐进决策理论，运用文献研究法与系统分析法识别耕地保护决... 详细信息

[目的]耕地保护是维护国家社会安全、生态安全和粮食安全的重要基石，探讨中国耕地保护决策的演进历程及产权路径，以期为新时代完善耕地保护制度提供理论支撑。[方法]文章基于渐进决策理论，运用文献研究法与系统分析法识别耕地保护决策变迁模式并分析路径依赖特征。[结果]农地产权的排他性与激励性逐渐强化，有限性相对减弱，为保护耕地营造了安全稳定的产权环境；中国耕地保护经历了体系形成、逐步完善、趋向成熟的阶段，遵循渐进决策模式，在平稳过渡中不断优化；耕地保护渐进决策深受产权阶段性变迁的影响，主要体现在制度环境、市场管理与农户行为路径。在制度上表现为冲突、迁移、协同的效应演变，在市场上表现为滞后、服务与激励的特征变化，农户行为则反映了群体效应、外部效应、预期效应的变化。[结论]随着产权变迁，产权效应耦合变化推动耕地保护决策发展。未来应优化农地产权制度结构、健全农地市场的公共服务管理、合理实现耕地生态产品的价值，以促进耕地保护决策良性发展。

关键词：土地管理耕地保护农地改革决策模式产权效应

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我国耕地保护政策研究:基于背景、效果与未来趋势

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中国农业资源与区划 2020年第10期41卷 40-51页

作者：王文旭曹银贵苏锐清邱敏宋蕾周伟中国地质大学(北京)土地科学技术学院自然资源部土地整治重点实验室

[目的]我国耕地保护政策对保护耕地、保障粮食安全具有重要意义。研究我国耕地保护政策出台的背景及前后关系、相同政策在不同区域内的执行效果差异,能够为更针对性地提出政策建议提供参考。[方法]主要运用了资料分析和定性描述的方法,... 详细信息

[目的]我国耕地保护政策对保护耕地、保障粮食安全具有重要意义。研究我国耕地保护政策出台的背景及前后关系、相同政策在不同区域内的执行效果差异,能够为更针对性地提出政策建议提供参考。[方法]主要运用了资料分析和定性描述的方法,首先按照耕地保护政策内涵划分为5个阶段,其次从时间、空间两个尺度,判断了耕地保护政策的数量、质量保护效果差异,最后提出了未来政策出台的方向和趋势。[结果]时间尺度上:1986年、1997年、2004年出台的政策对耕地数量保护的成效明显; 2014—2016年耕地质量保护效果略优于2009—2014年;目前数量保护成效较好,但质量保护远未达到要求。空间尺度上:耕地数量保护效果西部地区最好,东北地区次之,中部地区优于东部地区;耕地质量保护效果中部地区最佳,东北地区次之,东部地区优于西部地区。[结论]未来政策可向规范补充耕地全国统筹、完善耕地质量保护法律体系、调动农户保护耕地积极性等方向发展。

关键词：土地利用耕地保护执行效果差异性对策

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