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593篇 您的检索式:作者名="Lacasse"
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1State-of-the-art review of soft computing applications in underground excavations显示文摘Soft computing techniques are becoming even more popular and particularly amenable to model the complex behaviors of most geotechnical engineering systems since they have demonstrated superior predictive capacity,compared to the traditional methods.This paper presents an overview of some soft computing techniques as well as their applications in underground excavations.A case study is adopted to compare the predictive performances of soft computing techniques including eXtreme Gradient Boosting(XGBoost),Multivariate Adaptive Regression Splines(MARS),Artificial Neural Networks(ANN),and Support Vector Machine(SVM) in estimating the maximum lateral wall deflection induced by braced excavation.This study also discusses the merits and the limitations of some soft computing techniques,compared with the conventional approaches available.Wengang Zhang Runhong Zhang Chongzhi Wu Anthony Teck Chee Goh Suzanne Lacasse Zhongqiang Liu Hanlong Liu 2020Geoscience Frontiers2020,11,4:33
2边坡位移智能预测算法显示文摘目的:边坡位移预测是实现滑坡灾害预报的有效手段,对降低滑坡灾害导致的损失具有重要意义。本文针对三峡库区广泛分布的'阶跃型'滑坡,采用三种不同的机器学习算法:长短期记忆(LSTM)神经网络、随机森林(RF)算法和门控递归单元(GRU),预测三个不同的三峡库区边坡位移,并对比三种算法的预测精度,从而选择适用于边坡位移预测的机器学习算法。创新点:1.建立了基于时间序列分解和机器学习算法的动态预测模型,并能够准确预测边坡位移。2.对比了不同的机器学习算法预测边坡周期项位移的精度。方法:1.基于时间序列分解原理,将边坡累积位移分解为趋势项位移和周期项位移。2.利用多项式拟合对边坡趋势项位移进行预测。3.基于位移影响因素采用三种机器学习模型(LSTM、GRU和RF)预测边坡周期项位移。结论:1.本文提出的基于时间序列分解和机器学习算法的动态预测模型可以准确预测三峡库区'阶跃型'边坡位移。2.LSTM和GRU算法可以充分利用滑坡历史信息,精确预测边坡位移的周期项。Zhong-qiang LIU Dong GUO Suzanne LACASSE Jin-hui LI Bei-bei YANG Jung-chan CHOI 2020Journal of Zhejiang University-Science A(Applied Physics & Engineering)2020,21,6:12
3Modelling of shallow landslides with machine learning algorithms显示文摘This paper introduces three machine learning(ML)algorithms,the‘ensemble'Random Forest(RF),the‘ensemble'Gradient Boosted Regression Tree(GBRT)and the Multi Layer Perceptron neural network(MLP)and applies them to the spatial modelling of shallow landslides near Kvam in Norway.In the development of the ML models,a total of 11 significant landslide controlling factors were selected.The controlling factors relate to the geomorphology,geology,geo-environment and anthropogenic effects:slope angle,aspect,plan curvature,profile curvature,flow accumulation,flow direction,distance to rivers,water content,saturation,rainfall and distance to roads.It is observed that slope angle was the most significant controlling factor in the ML analyses.The performance of the three ML models was evaluated quantitatively based on the Receiver Operating Characteristic(ROC)analysis.The results show that the‘ensemble'GBRT machine learning model yielded the most promising results for the spatial prediction of shallow landslides,with a 95%probability of landslide detection and 87%prediction efficiency.Zhongqiang Liu Graham Gilbert Jose Mauricio Cepeda Asgeir Olaf Kydland Lysdahl Luca Piciullo Heidi Hefre Suzanne Lacasse 2021Geoscience Frontiers2021,12,1:3
4Nuntritional support for individuals with COPD: a meta-analysis显示文摘Ferreira IM Broods D Lacasse Y 2000Chest2000,117,3:2
5The inhibitors of apoptosis (IAPs) and their emerging role in cancer 显示文摘 Baird S Komeluk RG 1998Oncogene1998,17,25:1
6Clinical assessment of symptom clusters显示文摘Lacasse C Beck SL 2007Seminars in Oncology Nursing2007,23,2:1
7The inhibitors of apoptosis(1APs) and their emerging role in cancer显示文摘LaCasse EC Baird S Komeluk RG 1998Oncogene1998,17,:1
8The inhibitors of apoptosis (IAPs) and their emerging role in cancer显示文摘LaCasse E C Baird S Korneluk R G 1998Oncogene1998,17,25:1
9Nutritional intervention in COPD:a systematic overview显示文摘Ferreira I Brooks D Lacasse Y 2001Chest2001,119,2:1
10Pulmonary Rehabilitation for Chronic Obstructive Pulmonary Disease显示文摘Y Lacasse L Brosseau S Milne S Martin E Wong GH Guyatt RS Goldstein 2002Physiotherapy2002,,12:1
11The inhibitors of apoptosis (IAPs) and their emerging role in cancer显示文摘LaCasse EC Baird S Korneluk RG 1998Oncogene1998,17,25:1
12The inhibitors of apoptosis(IAPs) and their emerging role in cancer 显示文摘LaCasse EC Baird S Korneluk RG 1998Oncogene1998,17,25:1
13Improved fracture toughness of carbon fiber composite functionalized with multi wailed carbon nanotubes 显示文摘Kepple K L Sanborn G P Lacasse P A 2008Carbon2008,46,15:1
14Meta analysis of respirtory rehabilitation in chronic obstructive pulmonary disease显示文摘LACASSE Y WONG E GUYATT GH 1996Lancet1996,348,:1
15Interpolation strategies for reducing IFOV artifacts in microgrid polarimeter imagery显示文摘RATLIFF B M LACASSE C F TYO J S 2009Optics Express2009,17,11:1
16Midthigh mus- cle cross - sectional area is a better predictor of mortality than body mass index in patients with chronic obstructive pulmonary disease 显示文摘MARQUIS K DEBIGARE R LACASSE Y 2002Am J Respir Crit Care Med2002,166,6:1
17The inhibitors of apoptosis (IAPs) as cancer targets显示文摘Hunter A M LaCasse E C Korneluk R G 2007Apoptosis2007,12,9:1
18Nutritional suppon for individuals with COPD显示文摘Ferreire IV Brooks D Lacasse Y 2000Chest2000,117,67:1
19Nutritional support for individual with CODP: a meta-analysis显示文摘Ferreira I M Broods D Lacasse Y 2000Chest2000,117,3:1
20Nutritio COPD:a systematic overview显示文摘Ferreira I Book D Lacasse Y 2001Chest2001,119,:1
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