Related references
Note: Only part of the references are listed.Generic AI models for mass transfer coefficient prediction in amine-based CO2 absorber, Part II: RBFNN and RF model
Hong Quan et al.
AICHE JOURNAL (2023)
Estimation of thermal conductivity of plutonic drill cuttings from their mineralogy: A case study for the FORGE Well 58-32, Milford, Utah
Ruyang Yu et al.
GEOTHERMICS (2022)
Applying machine learning methods to estimate the thermal conductivity of bentonite for a high-level radioactive waste repository
Tian-xing Da et al.
NUCLEAR ENGINEERING AND DESIGN (2022)
Ensemble learning models with a Bayesian optimization algorithm for mineral prospectivity mapping
Jiangning Yin et al.
ORE GEOLOGY REVIEWS (2022)
Comparative analysis of seven machine learning algorithms and five empirical models to estimate soil thermal conductivity
Tianyue Zhao et al.
AGRICULTURAL AND FOREST METEOROLOGY (2022)
Artificial neural network for predicting the thermal conductivity of soils based on a systematic database
Kai-Qi Li et al.
GEOTHERMICS (2022)
Estimating the thermal conductivity of soils using six machine learning algorithms
Kai-Qi Li et al.
INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER (2022)
Application of Soft Computing Techniques for Predicting Thermal Conductivity of Rocks
Masoud Samaei et al.
APPLIED SCIENCES-BASEL (2022)
Prediction of undrained shear strength using extreme gradient boosting and random forest based on Bayesian optimization
Wengang Zhang et al.
GEOSCIENCE FRONTIERS (2021)
Estimation of diaphragm wall deflections for deep braced excavation in anisotropic clays using ensemble learning
Runhong Zhang et al.
GEOSCIENCE FRONTIERS (2021)
The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation
Davide Chicco et al.
PEERJ COMPUTER SCIENCE (2021)
Predictive mixing law models of rock thermal conductivity: Applicability analysis
Amin Tatar et al.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING (2021)
Reconstruction of the Cenozoic tectono-thermal history of the Dongpu Depression, Bohai Bay Basin, China: Constraints from apatite fission track and vitrinite reflectance data
Shu Jiang et al.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING (2021)
Geothermal gradient and heat flow of the Erlian Basin and adjacent areas, Northern China: Geodynamic implication
Wei Xu et al.
GEOTHERMICS (2021)
Rock thermal properties from well-logging data accounting for thermal anisotropy
A. Shakirov et al.
GEOTHERMICS (2021)
Prediction of thermal conductivity and damage in Indian Jalore granite for design of underground research laboratory
A. K. Verma et al.
NEURAL COMPUTING & APPLICATIONS (2021)
Prediction of solar energy guided by pearson correlation using machine learning
Imane Jebli et al.
ENERGY (2021)
Feasibility analysis of extreme learning machine for predicting thermal conductivity of rocks
Jianguo Kang et al.
ENVIRONMENTAL EARTH SCIENCES (2021)
Thermal conductivity of granitoids of varying composition up to 300 °C and implications for crustal thermal models
Labani Ray et al.
GEOPHYSICAL JOURNAL INTERNATIONAL (2021)
Study on heat extraction performance of multiple-doublet system in Hot Sedimentary Aquifers: Case study from the Xianyang geothermal field, Northwest China
Tingting Ke et al.
GEOTHERMICS (2021)
Thermal Diffusivity, Heat Capacity, and Thermal Conductivity of Oil Reservoir Rock at High Temperatures
Ilmutdin M. Abdulagatov et al.
INTERNATIONAL JOURNAL OF THERMOPHYSICS (2021)
A generalized model for effective thermal conductivity of soils considering porosity and mineral composition
Kai-Qi Li et al.
ACTA GEOTECHNICA (2021)
Thermal and Physical Properties of Deccan Basalt and Neoarchean Basement Cores From a Deep Scientific Borehole in the Koyna-Warna Seismogenic Region, Deccan Volcanic Province, Western India: Implications on Thermal Modeling and Seismogenesis
Labani Ray et al.
EARTH AND SPACE SCIENCE (2021)
On the importance of rock thermal conductivity and heat flow density in basin and petroleum system modelling
Evgeny Chekhonin et al.
BASIN RESEARCH (2020)
Assessment of soil thermal conduction using artificial neural network models
Tao Zhang et al.
COLD REGIONS SCIENCE AND TECHNOLOGY (2020)
Evaluating explorative prediction power of machine learning algorithms for materials discovery using k-fold forward cross-validation
Zheng Xiong et al.
COMPUTATIONAL MATERIALS SCIENCE (2020)
Robust well-log based determination of rock thermal conductivity through machine learning
Yury Meshalkin et al.
GEOPHYSICAL JOURNAL INTERNATIONAL (2020)
Meso-scale investigations on the effective thermal conductivity of multi-phase materials using the finite element method
Kai-Qi Li et al.
INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER (2020)
Application of machine learning methods to predict a thermal conductivity model for compacted bentonite
Hyun-Tae Bang et al.
ANNALS OF NUCLEAR ENERGY (2020)
Comparison of Machine Learning and Land Use Regression for fine scale spatiotemporal estimation of ambient air pollution: Modeling ozone concentrations across the contiguous United States
Xiang Ren et al.
ENVIRONMENT INTERNATIONAL (2020)
Thermal conductivity, density, petrological and geochemical characteristics of granitoids from Singhbhum Craton, eastern India
Nishu Chopra et al.
GEOTHERMICS (2020)
A unified soil thermal conductivity model based on artificial neural network
Nan Zhang et al.
INTERNATIONAL JOURNAL OF THERMAL SCIENCES (2020)
A comparison of dimension reduction techniques for support vector machine modeling of multi-parameter manufacturing quality prediction
Yun Bai et al.
JOURNAL OF INTELLIGENT MANUFACTURING (2019)
Machine learning for data-driven discovery in solid Earth geoscience
Karianne J. Bergen et al.
SCIENCE (2019)
Hyperparameters and tuning strategies for random forest
Philipp Probst et al.
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY (2019)
A new compositionally based thermal conductivity model for plutonic rocks
S. Jennings et al.
GEOPHYSICAL JOURNAL INTERNATIONAL (2019)
Cyclic soft stimulation (CSS): a new fluid injection protocol and traffic light system to mitigate seismic risks of hydraulic stimulation treatments (vol 6, 27, 2018)
Hannes Hofmann et al.
GEOTHERMAL ENERGY (2019)
Evaluate best-mixing model for estimating thermal conductivity for granitoids from mineralogy: A case study for the granitoids of the Bundelkhand craton, central India
Nishu Chopra et al.
GEOTHERMICS (2018)
Calculation of Thermal Conductivity of Low-Porous, Isotropic Plutonic Rocks of the Crust at Ambient Conditions From Modal Mineralogy and Porosity: A Viable Alternative for Direct Measurement?
S. Fuchs et al.
JOURNAL OF GEOPHYSICAL RESEARCH-SOLID EARTH (2018)
Numerical simulation of diverse thermal in situ upgrading processes for the hydrocarbon production from kerogen in oil shale reservoirs
Kyung Jae Lee et al.
ENERGY EXPLORATION & EXPLOITATION (2017)
A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring
Yufei Xia et al.
EXPERT SYSTEMS WITH APPLICATIONS (2017)
Thermal conductivity estimation model considering the effect of water saturation explaining the heterogeneity of rock thermal conductivity
Katharina Albert et al.
GEOTHERMICS (2017)
Dimension Reduction With Extreme Learning Machine
Liyanaarachchi Lekamalage Chamara Kasun et al.
IEEE TRANSACTIONS ON IMAGE PROCESSING (2016)
Effective Thermal Conductivity Modeling of Sandstones: SVM Framework Analysis
Alireza Rostami et al.
INTERNATIONAL JOURNAL OF THERMOPHYSICS (2016)
Experimental investigations on the thermal conductivity characteristics of Beishan granitic rocks for China's HLW disposal
X. G. Zhao et al.
TECTONOPHYSICS (2016)
Study cases of thermal conductivity prediction from P-wave velocity and porosity
Lionel Esteban et al.
GEOTHERMICS (2015)
Tracking the thermal properties of the lower continental crust: Measured versus calculated thermal conductivity of high-grade metamorphic rocks (Southern Granulite Province, India)
Labani Ray et al.
GEOTHERMICS (2015)
Indirect measure of thermal conductivity of rocks through adaptive neuro-fuzzy inference system and multivariate regression analysis
Mohsen Hajihassani et al.
MEASUREMENT (2015)
Machine learning: Trends, perspectives, and prospects
M. I. Jordan et al.
SCIENCE (2015)
Estimating thermal conductivity from core and well log data
Irena Gasior et al.
ACTA GEOPHYSICA (2014)
Modeling and analysis of the thermal conductivities of air saturated sandstone, quartz and limestone using computational intelligence
V. Gitifar et al.
INTERNATIONAL JOURNAL OF THERMAL SCIENCES (2014)
Evaluation of common mixing models for calculating bulk thermal conductivity of sedimentary rocks: Correction charts and new conversion equations
Sven Fuchs et al.
GEOTHERMICS (2013)
Application of an expert system to predict thermal conductivity of rocks
Manoj Khandelwal
NEURAL COMPUTING & APPLICATIONS (2012)
Prediction of thermal conductivity of rocks by soft computing
Manoj Khandelwal
INTERNATIONAL JOURNAL OF EARTH SCIENCES (2011)
Effect of pressure, temperature, and oil-saturation on the thermal conductivity of sandstone up to 250 MPa and 520 K
Zumrud Z. Abdulagatova et al.
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING (2010)
An effective thermal conductivity model of geological porous media for coupled thermo-hydro-mechanical systems with multiphase flow
Fuguo Tong et al.
INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES (2009)
Prediction of thermal conductivity of rock through physico-mechanical properties
T. N. Singh et al.
BUILDING AND ENVIRONMENT (2007)
Using neural networks to predict thermal conductivity from geophysical well logs
Bruno Goutorbe et al.
GEOPHYSICAL JOURNAL INTERNATIONAL (2006)
A tutorial on support vector regression
AJ Smola et al.
STATISTICS AND COMPUTING (2004)
Prediction of thermal conductivity of granite rocks from porosity and density data at normal temperature and pressure:: in situ thermal conductivity measurements
A Maqsood et al.
JOURNAL OF PHYSICS D-APPLIED PHYSICS (2004)
Stochastic gradient boosting
JH Friedman
COMPUTATIONAL STATISTICS & DATA ANALYSIS (2002)
Greedy function approximation: A gradient boosting machine
JH Friedman
ANNALS OF STATISTICS (2001)
Share Paper
