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作品数：712被引量：881H指数：12
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Evaluation of the treatment variables on the shear strength of loess treated by microbial induced carbonate precipitation
《Journal of Mountain Science》2025年第3期1075-1086,共12页CHEN Yang ZHANG Runyan ZI Jiaojiao HAN Jianyong LIU Kaiwen 
This work is supported by the Young Talent Fund of Association for Science and Technology in Shaanxi,China(20240722);the Shaanxi Province Postdoctoral Research Project(2023BSHYDZZ138);the Open Research Fund of Key Laboratory of Construction and Safety of Water Engineering of the Ministry of Water Resources,China Institute of Water Resources and Hydropower Research(NO.IWHR-ENGI-202305);Open project of Engineering Research Center of Concrete Technology under Marine Environment,Ministry of Education(2024KFKT-YB12);Shandong Youth Innovation Team(No.2023KJ324).
This study presents an experimental investigation into the effects of microbial induced carbonate precipitation(MICP)treatment factors on the shear behavior of MICP-treated loess soil.Several groups of loess samples w...
关键词：Microbial induced carbonate precipitation(MICP) LOESS Treatment factors Shear strength Orthogonal analysis Microstructure 
Comparative Evaluation of Predictive Models for Malaria Cases in Sierra Leone
《Open Journal of Epidemiology》2025年第1期188-216,共29页Saidu Wurie Jalloh Herbert Imboga Mary H. Hodges Boniface Malenje 
Malaria remains a major public health challenge necessitating accurate predictive models to inform effective intervention strategies in Sierra Leone. This study compares the performance of Holt-Winters’ Exponential S...
关键词：Malaria Cases Artificial Neural Networks Holt-Winters HARMONIC Climate Variables Predictive Modelling Public Health 
Comparative analysis of machine learning and statistical models for cotton yield prediction in major growing districts of Karnataka,India
《Journal of Cotton Research》2025年第1期40-60,共21页THIMMEGOWDA M.N. MANJUNATHA M.H. LINGARAJ H. SOUMYA D.V. JAYARAMAIAH R. SATHISHA G.S. NAGESHA L. 
funded through India Meteorological Department,New Delhi,India under the Forecasting Agricultural output using Space,Agrometeorol ogy and Land based observations(FASAL)project and fund number:No.ASC/FASAL/KT-11/01/HQ-2010.
Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,su...
关键词：COTTON Machine learning models Statistical models Yield forecast Artificial neural network Weather variables 
Modeling net-charge fluctuations in heavy-ion collisions at the LHC
《Chinese Physics C》2025年第1期281-289,共9页G.O.Ambaryan A.S.Chernyshov G.Kh.Eyyubova V.L.Korotkikh I.P.Lokhtin S.V.Petrushanko A.M.Snigirev E.E.Zabrodin 
supported by the BASIS Foundation(23-2-10-2-1)。
Analysis of Pb+Pb data for net-charge fluctuations at LHC energies using the HYDJET++model is presented.The strongly intensive quantities D and Σ were used to remove the effects related to system volume fluctuations....
关键词：relativistic heavy-ion collisions net-charge fluctuations strongly intensive variables canonical charge conservation 
How Do Deep Learning Forecasting Models Perform for Surface Variables in the South China Sea Compared to Operational Oceanography Forecasting Systems?
《Advances in Atmospheric Sciences》2025年第1期178-189,共12页Ziqing ZU Jiangjiang XIA Xueming ZHU Marie DREVILLON Huier MO Xiao LOU Qian ZHOU Yunfei ZHANG Qing YANG 
supported by the National Natural Science Foundation of China(Grant Nos.42375062 and 42275158);the National Key Scientific and Technological Infrastructure project“Earth System Science Numerical Simulator Facility”(EarthLab);the Natural Science Foundation of Gansu Province(Grant No.22JR5RF1080)。
It is fundamental and useful to investigate how deep learning forecasting models(DLMs)perform compared to operational oceanography forecast systems(OFSs).However,few studies have intercompared their performances using...
关键词：forecast error deep learning forecasting model operational oceanography forecasting system VALIDATION intercomparison 
Prognostic prediction models for postoperative patients with stageⅠtoⅢcolorectal cancer based on machine learning
《World Journal of Gastrointestinal Oncology》2024年第12期4597-4613,共17页Xiao-Lin Ji Shuo Xu Xiao-Yu Li Jin-Huan Xu Rong-Shuang Han Ying-Jie Guo Li-Ping Duan Zi-Bin Tian 
Supported by National Natural Science Foundation of China,No.81802777.
BACKGROUND Colorectal cancer(CRC)is characterized by high heterogeneity,aggressiveness,and high morbidity and mortality rates.With machine learning(ML)algorithms,patient,tumor,and treatment features can be used to dev...
关键词：Colorectal cancer Machine learning Prognostic prediction model Survival times Important variables 
Enhancing forest insect outbreak detection by integrating tree-ring and climate variables
《Journal of Forestry Research》2024年第6期279-293,共15页Yao Jiang Zhou Wang Zhongrui Zhang Xiaogang Ding Shaowei Jiang Jianguo Huang 
supported by the Xinjiang Regional Collaborative Innovation Project(2022E01045);Zhejiang University(108000*1942222R1).
Annual tree rings are widely recognized as valuable tools for quantifying and reconstructing historical forest disturbances.However,the influence of climate can complicate the detection of disturbance signals,leading ...
关键词：Forest disturbance Insect outbreaks Machine learning Tree-ring analysis 
Prediction of damage potential in mainshock–aftershock sequences using machine learning algorithms
《Earthquake Engineering and Engineering Vibration》2024年第4期919-938,共20页Zhou Zhou Wang Meng Han Miao Yu Xiaohui Lu Dagang 
China Postdoctoral Science Foundation under Grant No.2022M710333;the Beijing Postdoctoral Research Foundation under Grant No.2023-zz-141;the National Natural Science Foundation of China under Grant Nos.52278492 and 52078176。
Assessing the potential damage caused by earthquakes is crucial for a community’s emergency response.In this study,four machine learning(ML)methods—random forest,extremely randomized trees,AdaBoost(AB),and gradient ...
关键词：machine learning mainshock-aftershock damage potential prediction the high-correlation variables SDOF systems 
Spatial distribution characteristics of climate-induced landslides in the Eastern Himalayas
《Journal of Mountain Science》2024年第10期3396-3412,共17页UWIZEYIMANA David LIU Weiming HUANG Yu HABUMUGISHA Jules Maurice ZHOU Yanlian YANG Zewen 
supported by the Second Tibetan Plateau Scientific Expedition and Research (STEP) (2019QZKK0903);the National Natural Science Foundation of China (No. 42071017);the science and technology research program of the Chinese Academy of Sciences' Institute of Mountain Hazards and Environment (No.IMHE-ZDRW-03);the Alliance of International Science Organizations (ANSO) provided funding for a master's degree
Climate warming is constantly causing hydro-meteorological perturbations,especially in high-altitude mountainous regions,which lead to the occurrences of landslides.The impact of climatic variables(i.e.,precipitation ...
关键词：Landslide inventory Climate variables Normalized difference vegetation index CRYOSPHERE Eastern Himalaya 
Optimal hydrogen-battery energy storage system operation in microgrid with zero-carbon emission
《Global Energy Interconnection》2024年第5期616-628,共13页Huayi Wu Zhao Xu Youwei Jia 
supported by the National Natural Science Foundation of China under Grant No.72331008,and No.72271211,and PolyU research project 1-YXBL.
To meet the greenhouse gas reduction targets and address the uncertainty introduced by the surging penetration of stochastic renewable energy sources,energy storage systems are being deployed in microgrids.Relying sol...
关键词：MICROGRID Hybrid hydrogen-battery storage Outer-inner column-and-constraint generation algorithm Adaptive robust optimization Integer recourse variables 
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