Comptes Rendus Mecanique最新文献_第8页

Nonintrusive data-based learning of a switched control heating system using POD, DMD and ANN 基于POD、DMD和ANN的开关控制加热系统非侵入式数据学习

IF 0.8 4区工程技术

Comptes Rendus Mecanique Pub Date : 2019-11-01 DOI: 10.1016/j.crme.2019.11.005

Tarik Fahlaoui, Florian De Vuyst

引用次数: 1

Evaluation of hip fracture risk using a hyper-parametric model based on the Locally Linear Embedding technique 基于局部线性嵌入技术的超参数模型评估髋部骨折风险

IF 0.8 4区工程技术

Comptes Rendus Mecanique Pub Date : 2019-11-01 DOI: 10.1016/j.crme.2019.11.010

Enrique Nadal , David Muñoz , Nieves Vivó , Irene Lucas , Juan José Ródenas

引用次数: 5

Risk analysis: Survival data analysis vs. machine learning. Application to Alzheimer prediction 风险分析:生存数据分析与机器学习。阿尔茨海默病预测的应用

IF 0.8 4区工程技术

Comptes Rendus Mecanique Pub Date : 2019-11-01 DOI: 10.1016/j.crme.2019.11.007

Catherine Huber-Carol , Shulamith Gross , Filia Vonta

{"title":"Risk analysis: Survival data analysis vs. machine learning. Application to Alzheimer prediction","authors":"Catherine Huber-Carol , Shulamith Gross , Filia Vonta","doi":"10.1016/j.crme.2019.11.007","DOIUrl":"10.1016/j.crme.2019.11.007","url":null,"abstract":"<div><p>We present here the statistical models that are most in use in survival data analysis. The parametric ones are based on explicit distributions, depending only on real unknown parameters, while the preferred models are semi-parametric, like Cox model, which imply unknown functions to be estimated. Now, as big data sets are available, two types of methods are needed to deal with the resulting curse of dimensionality including non informative factors which spoil the informative part relative to the target: on one hand, methods that reduce the dimension while maximizing the information left in the reduced data, and then applying classical stochastic models; on the other hand algorithms that apply directly to big data, i.e. artificial intelligence (AI or machine learning). Actually, those algorithms have a probabilistic interpretation. We present here several of the former methods. As for the latter methods, which comprise neural networks, support vector machines, random forests and more (see second edition, January 2017 of Hastie, Tibshirani et al. (2005) <span>[1]</span>), we present the neural networks approach. Neural networks are known to be efficient for prediction on big data. As we analyzed, using a classical stochastic model, risk factors for Alzheimer on a data set of around 5000 patients and <span><math><mi>p</mi><mo>=</mo><mn>17</mn></math></span> factors, we were interested in comparing its prediction performance with the one of a neural network on this relatively small sample size data.</p></div>","PeriodicalId":50997,"journal":{"name":"Comptes Rendus Mecanique","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.crme.2019.11.007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124069274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Data-driven modeling and learning in science and engineering 科学和工程领域的数据驱动建模和学习

IF 0.8 4区工程技术

Comptes Rendus Mecanique Pub Date : 2019-11-01 DOI: 10.1016/j.crme.2019.11.009

Francisco J. Montáns , Francisco Chinesta , Rafael Gómez-Bombarelli , J. Nathan Kutz

引用次数: 147

Identification of nonlinear dynamical system equations using dynamic mode decomposition under invariant quantity constraints 在不变量约束下用动态模态分解辨识非线性动力系统方程

IF 0.8 4区工程技术

Comptes Rendus Mecanique Pub Date : 2019-11-01 DOI: 10.1016/j.crme.2019.11.013

Florian De Vuyst , Pierre Villon

引用次数: 1

Incremental dynamic mode decomposition: A reduced-model learner operating at the low-data limit 增量动态模式分解:在低数据限制下运行的简化模型学习器

IF 0.8 4区工程技术

Comptes Rendus Mecanique Pub Date : 2019-11-01 DOI: 10.1016/j.crme.2019.11.003

Agathe Reille , Nicolas Hascoet , Chady Ghnatios , Amine Ammar , Elias Cueto , Jean Louis Duval , Francisco Chinesta , Roland Keunings

引用次数: 10

Data-driven computation for history-dependent materials 历史材料的数据驱动计算

IF 0.8 4区工程技术

Comptes Rendus Mecanique Pub Date : 2019-11-01 DOI: 10.1016/j.crme.2019.11.008

Pierre Ladevèze, David Néron, Paul-William Gerbaud

引用次数: 28

A non-intrusive approach for the reconstruction of POD modal coefficients through active subspaces 一种通过活动子空间重构POD模态系数的非侵入式方法

IF 0.8 4区工程技术

Comptes Rendus Mecanique Pub Date : 2019-11-01 DOI: 10.1016/j.crme.2019.11.012

Nicola Demo, Marco Tezzele, Gianluigi Rozza

{"title":"A non-intrusive approach for the reconstruction of POD modal coefficients through active subspaces","authors":"Nicola Demo, Marco Tezzele, Gianluigi Rozza","doi":"10.1016/j.crme.2019.11.012","DOIUrl":"10.1016/j.crme.2019.11.012","url":null,"abstract":"<div><p>Reduced order modeling (ROM) provides an efficient framework to compute solutions of parametric problems. Basically, it exploits a set of precomputed high-fidelity solutions—computed for properly chosen parameters, using a full-order model—in order to find the low dimensional space that contains the solution manifold. Using this space, an approximation of the numerical solution for new parameters can be computed in real-time response scenario, thanks to the reduced dimensionality of the problem. In a ROM framework, the most expensive part from the computational viewpoint is the calculation of the numerical solutions using the full-order model. Of course, the number of collected solutions is strictly related to the accuracy of the reduced order model. In this work, we aim at increasing the precision of the model also for few input solutions by coupling the proper orthogonal decomposition with interpolation (PODI)—a data-driven reduced order method—with the active subspace (AS) property, an emerging tool for reduction in parameter space. The enhanced ROM results in a reduced number of input solutions to reach the desired accuracy. In this contribution, we present the numerical results obtained by applying this method to a structural problem and in a fluid dynamics one.</p></div>","PeriodicalId":50997,"journal":{"name":"Comptes Rendus Mecanique","volume":null,"pages":null},"PeriodicalIF":0.8,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.crme.2019.11.012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124927340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

ANM analysis of a wrinkled elastic thin membrane 皱褶弹性薄膜的核磁共振分析

IF 0.8 4区工程技术

Comptes Rendus Mecanique Pub Date : 2019-10-01 DOI: 10.1016/j.crme.2019.10.001

Siham Khalil , Youssef Belaasilia , Abdellah Hamdaoui , Bouazza Braikat , Mohammad Jamal , Noureddine Damil , Zitouni Azari

引用次数: 6

Non-global existence of solutions to pseudo-parabolic equations with variable exponents and positive initial energy 变指数正初始能量伪抛物型方程解的非整体存在性

IF 0.8 4区工程技术

Comptes Rendus Mecanique Pub Date : 2019-10-01 DOI: 10.1016/j.crme.2019.09.003

Menglan Liao

引用次数: 18