Results 21 to 30 of about 447 (169)

An interpretable probabilistic prediction algorithm for shield movement performance

Frontiers in Earth Science
Total thrust and torque are two key indicators of shield movement performance. Most existing data-driven machine learning studies focus on developing more accurate models for predicting total thrust and torque but overlook the interpretability of the ...
Yapeng Zhang, Yapeng Zhang, Long Liu, Long Liu, Jian Wu, Jian Wu, Shaoxiang Zeng, Shaoxiang Zeng, Jianquan Hu, Yuanqin Tao, Yuanqin Tao, Yong Huang, Yong Huang, Xuetao Zhou, Xuetao Zhou, Xu Liang   +15 more
doaj   +2 more sources

Uncertainty and explainable analysis of machine learning model for reconstruction of sonic slowness logs

Artificial Intelligence in Geosciences, 2023
Logs are valuable information for oil and gas fields as they help to determine the lithology of the formations surrounding the borehole and the location and reserves of subsurface oil and gas reservoirs.
Hua Wang, Yuqiong Wu, Yushun Zhang, Fuqiang Lai, Zhou Feng, Bing Xie, Ailin Zhao   +6 more
doaj   +2 more sources

Identification of sepsis biomarkers through glutamine metabolism-mediated immune regulation: a comprehensive analysis employing mendelian randomization, multi-omics integration, and machine learning [PDF]

Frontiers in Immunology
BackgroundSepsis is a global health challenge associated with high morbidity and mortality rates. Early diagnosis and treatment are challenging because of the limited understanding of its underlying mechanisms.
Zhuang’e Shi, Fuping Wang, Lishun Yang, Lishun Yang, Couwen Li, Bing Gong, Ruanxian Dai, Guobing Chen   +7 more
doaj   +2 more sources

Explainable Artificial Intelligence to Unveil Intrinsic Characteristics of Conditioning Factors Governing Forest Fire Susceptibility [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Forest fires are typically triggered by natural factors or human negligence and accidents, spreading across vast areas and causing extensive damage to vegetation, wildlife, and ecosystems.
A. Teke, T. Kavzoglu
doaj   +3 more sources

Snow Avalanche Susceptibility Mapping Using Novel Tree-Based Machine Learning Algorithms (XGBoost, NGBoost, and LightGBM) With eXplainable Artificial Intelligence (XAI) Approach

Stochastic Environmental Research and Risk Assessment, 2023
This study examines the use of snow avalanche susceptibility maps (SASMs) to identify areas prone to avalanches and develop measures to mitigate the risk in the Province of Sondrio, Italy. Various machine learning classifiers such as Random Forest, Gradient Boosting Machines, and AdaBoost, as well as newer classifiers like XGBoost, LightGBM, and ...
Suleyman Sefa Bilgilioğlu, Muzaffer Can Iban   +1 more
exaly   +3 more sources

Natural Gradient Boosting for Probabilistic Prediction of Soaked CBR Values Using an Explainable Artificial Intelligence Approach [PDF]

Buildings
The California bearing ratio (CBR) value of subgrade is the most used parameter for dimensioning flexible and rigid pavements. The test for determining the CBR value is typically conducted under soaked conditions and is costly, labour-intensive, and time-
Esteban Díaz, Giovanni Spagnoli
doaj   +2 more sources

Data-driven discovery and parameter estimation of mathematical models in biological pattern formation. [PDF]

PLoS Computational Biology
Mathematical modeling has been utilized to explain biological pattern formation, but the selections of models and parameters have been made empirically. In the present study, we propose a data-driven approach to validate the applicability of mathematical
Hidekazu Hishinuma, Hisako Takigawa-Imamura, Takashi Miura   +2 more
doaj   +2 more sources

The Application of Wind Power Prediction Based on the NGBoost–GRU Fusion Model in Traffic Renewable Energy System

Sustainability
In the context of the “double carbon” goals and energy transformation, the integration of energy and transportation has emerged as a crucial trend in their coordinated development. Wind power prediction serves as the cornerstone technology for ensuring efficient operations within this integrated framework.
Li Fudong
exaly   +2 more sources

Development of a visualized risk prediction system for sarcopenia in older adults using machine learning: a cohort study based on CHARLS [PDF]

Frontiers in Public Health
IntroductionThe older adult are at high risk of sarcopenia, making early identification and scientific intervention crucial for healthy aging.MethodsThis study utilized data from the China Health and Retirement Longitudinal Study (CHARLS), including a ...
Jinsong Du, Jinsong Du, Xinru Tao, Le Zhu, Heming Wang, Wenhao Qi, Xiaoqiang Min, Xiaoqiang Min, Shujie Wei, Xiaoyan Zhang, Qiang Liu   +10 more
doaj   +2 more sources

Advanced machine learning for pillar stress prediction and design optimisation in hardrock platinum mining: enhancing safety and sustainability on the Great Dyke of Zimbabwe

Geomechanics and Geophysics for Geo-Energy and Geo-Resources
This study advances pillar stress prediction and design optimisation in hardrock platinum mining on the Great Dyke of Zimbabwe using advanced machine learning (ML) techniques, addressing significant gaps in traditional methods.
Tawanda Zvarivadza, Hendrik Grobler, Sohan Singh Rajpurohit, Senzeni Moyo, Moshood Onifade, Manoj Khandelwal   +5 more
doaj   +2 more sources