2021年6期
刊物介绍
反映世界范围内，特别是中国岩石力学与工程的新成就、新理论、新方法、新经验、新动向，促进国内外学术交流，特别欢迎国家重大项目、国家自然科学基金项目及其他重要项目的研究成果，倡导和鼓励有实践经验的作者撰稿，并优先刊用这些稿件，本刊也发表少数侧重于工程应用的土力学方面的文章。为尽快交流最新的学术信息，本刊还发表短文和讨论文章、近期博士学位论文摘要、会议简讯、新书简介与相关的学术动态等；提倡撰写简短的讨论文章，活跃期刊学术氛围。
Journal of Rock Mechanics and Geotechnical Engineering
- Prediction of rockhead using a hybrid N-XGBoost machine learning framework
- Interpretable deep learning for roof fall hazard detection in underground mines
- Classification of clustered microseismic events in a coal mine using machine learning
- Comparison of machine learning methods for ground settlement prediction with different tunneling datasets
- An evolutionary adaptive neuro-fuzzy inference system for estimating field penetration index of tunnel boring machine in rock mass
- Spatial distribution modeling of subsurface bedrock using a developed automated intelligence deep learning procedure:A case study in Sweden
- Real-time rock mass condition prediction with TBM tunneling big data using a novel rock-machine mutual feedback perception method
- Information and knowledge behind data from underground rock grouting
- Tunnel boring machine vibration-based deep learning for the ground identification of working faces
- Deep learning-based evaluation of factor of safety with confidence interval for tunnel deformation in spatially variable soil
- Suggestion of advanced regression model on friction angle of fault gouge in South Korea
- Prediction of blasting mean fragment size using support vector regression combined with five optimization algorithms
- Hybrid ensemble soft computing approach for predicting penetration rate of tunnel boring machine in a rock environment
- Prediction of flyrock distance induced by mine blasting using a novel Harris Hawks optimization-based multi-layer perceptron neural network
- Data-driven estimation of joint roughness coefficient
- Prediction of flyrock induced by mine blasting using a novel kernel-based extreme learning machine
- Predicting roof displacement of roadways in underground coal mines using adaptive neuro-fuzzy inference system optimized by various physics-based optimization algorithms
- Improved prediction of shear wave velocity for clastic sedimentary rocks using hybrid model with core data
- Analysis of ground surface settlement in anisotropic clays using extreme gradient boosting and random forest regression models
- An intelligent procedure for updating deformation prediction of braced excavation in clay using gated recurrent unit neural networks
- Artificial neural network optimized by differential evolution for predicting diameters of jet grouted columns
- Random failure mechanism method for assessment of working platform bearing capacity with a linear trend in undrained shear strength