检索范围:
排序: 展示方式:
《医学前沿(英文)》 2022年 第16卷 第3期 页码 496-506 doi: 10.1007/s11684-021-0828-7
Reliability prediction and its validation for nuclear power units in service
Jinyuan SHI,Yong WANG
《能源前沿(英文)》 2016年 第10卷 第4期 页码 479-488 doi: 10.1007/s11708-016-0425-7
关键词: nuclear power units in service reliability reliability prediction equivalent availability factors
Position-varying surface roughness prediction method considering compensated acceleration in milling
《机械工程前沿(英文)》 2021年 第16卷 第4期 页码 855-867 doi: 10.1007/s11465-021-0649-z
关键词: surface roughness prediction compensated acceleration milling thin-walled workpiece
Trend prediction technology of condition maintenance for large water injection units
Xiaoli XU, Sanpeng DENG
《机械工程前沿(英文)》 2010年 第5卷 第2期 页码 171-175 doi: 10.1007/s11465-009-0091-0
关键词: water injection units condition-based maintenance trend prediction
An energy consumption prediction approach of die casting machines driven by product parameters
《机械工程前沿(英文)》 页码 868-886 doi: 10.1007/s11465-021-0656-0
关键词: die casting machine energy consumption prediction product parameters
Liquefaction prediction using support vector machine model based on cone penetration data
Pijush SAMUI
《结构与土木工程前沿(英文)》 2013年 第7卷 第1期 页码 72-82 doi: 10.1007/s11709-013-0185-y
关键词: earthquake cone penetration test liquefaction support vector machine (SVM) prediction
《化学科学与工程前沿(英文)》 2022年 第16卷 第4期 页码 523-535 doi: 10.1007/s11705-021-2083-5
关键词: solubility prediction machine learning artificial neural network random decision forests
《结构与土木工程前沿(英文)》 页码 976-989 doi: 10.1007/s11709-022-0840-2
关键词: damage prediction ANN BOA FEM experimental modal analysis
The prediction of adsorption isotherms of ester vapors on hypercrosslinked polymeric adsorbent
Liuyan WU,Lijuan JIA,Xiaohan LIU,Chao LONG
《环境科学与工程前沿(英文)》 2016年 第10卷 第3期 页码 482-490 doi: 10.1007/s11783-015-0826-6
关键词: hypercrosslinked polymeric adsorbent adsorption isotherm ester prediction
Prediction of the shear wave velocity
Amoroso SARA
《结构与土木工程前沿(英文)》 2014年 第8卷 第1期 页码 83-92 doi: 10.1007/s11709-013-0234-6
关键词: horizontal stress index shear wave velocity flat dilatometer test cone penetration test
GLOBAL GENOMIC PREDICTION IN HORTICULTURAL CROPS: PROMISES, PROGRESS, CHALLENGES AND OUTLOOK
《农业科学与工程前沿(英文)》 2021年 第8卷 第2期
Horticultural crops are a major source of high value nutritious food, and new improved cultivars developed through breeding are required for sustainable production in the face of abiotic and biotic stresses, and to deliver novel, premium products to consumers. However, grower confidence in the performance of new germplasm, particularly across environmental variability, is important for commercial adoption and germplasm-environment matching to optimize production.
Ensemble unit and AI techniques for prediction of rock strain
《结构与土木工程前沿(英文)》 页码 858-870 doi: 10.1007/s11709-022-0831-3
关键词: prediction strain ensemble unit rank analysis error matrix
高建国
《中国工程科学》 2009年 第11卷 第6期 页码 129-131
地震预测预报的难度大,但并非了无痕迹或不可知,我国每次较大的地震都有案例总结。统计表明,近40 年来,有77 次地震在发生前均有中期、短期甚至临震预测,不能因为汶川地震预测的失败,就全面抹杀中国的地震预报成绩,即我国的地震预测成绩是应予肯定的,汶川地震也并非是无前兆的“怪震”。
关键词: 地震 地震预测 中国近30 多年的地震预报统计
Digital-Twin-Enhanced Quality Prediction for the Composite Materials Article
Yucheng Wang, Fei Tao, Ying Zuo, Meng Zhang, Qinglin Qi
《工程(英文)》 2023年 第22卷 第3期 页码 23-33 doi: 10.1016/j.eng.2022.08.019
Composite materials are widely used in many fields due to their excellent properties. Quality defects in composite materials can lead to lower quality components, creating potential risk of accidents. Experimental and simulation methods are commonly used to predict the quality of composite materials. However, it is difficult to predict the quality of composite materials accurately due to the uncertain curing environment and incomplete feature space. To address this problem, a digital twin (DT) visual model of a composite material is first constructed. Then, a static autoclave DT virtual model is coupled with a variable composite material DT virtual model to construct a model of the curing process. Features are added to the proposed model by generating simulated data to enhance the quality prediction. An extreme learning machine (ELM) for quality prediction is trained with the generated data. Finally, the effectiveness of the proposed method is verified through result analysis.
关键词: Digital twin Quality prediction Composites Coupling models
《结构与土木工程前沿(英文)》 页码 224-238 doi: 10.1007/s11709-022-0812-6
关键词: soil consolidation coefficient machine learning random forest Relief
标题 作者 时间 类型 操作
Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis
期刊论文
Reliability prediction and its validation for nuclear power units in service
Jinyuan SHI,Yong WANG
期刊论文
Position-varying surface roughness prediction method considering compensated acceleration in milling
期刊论文
Trend prediction technology of condition maintenance for large water injection units
Xiaoli XU, Sanpeng DENG
期刊论文
Liquefaction prediction using support vector machine model based on cone penetration data
Pijush SAMUI
期刊论文
Machine learning-based solubility prediction and methodology evaluation of active pharmaceutical ingredients
期刊论文
Vibration-based crack prediction on a beam model using hybrid butterfly optimization algorithm with artificial
期刊论文
The prediction of adsorption isotherms of ester vapors on hypercrosslinked polymeric adsorbent
Liuyan WU,Lijuan JIA,Xiaohan LIU,Chao LONG
期刊论文
Digital-Twin-Enhanced Quality Prediction for the Composite Materials
Yucheng Wang, Fei Tao, Ying Zuo, Meng Zhang, Qinglin Qi
期刊论文