2021年6期
刊物介紹
反映世界范圍內(nèi)，特別是中國巖石力學(xué)與工程的新成就、新理論、新方法、新經(jīng)驗、新動向，促進國內(nèi)外學(xué)術(shù)交流，特別歡迎國家重大項目、國家自然科學(xué)基金項目及其他重要項目的研究成果，倡導(dǎo)和鼓勵有實踐經(jīng)驗的作者撰稿，并優(yōu)先刊用這些稿件，本刊也發(fā)表少數(shù)側(cè)重于工程應(yīng)用的土力學(xué)方面的文章。為盡快交流最新的學(xué)術(shù)信息，本刊還發(fā)表短文和討論文章、近期博士學(xué)位論文摘要、會議簡訊、新書簡介與相關(guān)的學(xué)術(shù)動態(tài)等；提倡撰寫簡短的討論文章，活躍期刊學(xué)術(shù)氛圍。
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