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Simulating Tree Plasticity with a Functional-Structural Plant Model: Being Realistic in Behavior 会议论文
, Venice, Italy, Oct.27-Nov.1,2013
作者:  Haoyu Wang;  Jing Hua;  Mengzhen Kang;  Xiujuan Wang;  Philippe de Reffye;  Baogang Hu
Adobe PDF(1219Kb)  |  收藏  |  浏览/下载：38/12  |  提交时间：2023/05/05
A knowledge-and-data-driven modeling approach for simulating plant growth and the dynamics of CO2/O-2 concentrations in a closed system of plants and humans by integrating mechanistic and empirical models 期刊论文
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2018, 卷号: 148, 期号: -, 页码: 280-290
作者:  Fan, Xing-Rong;  Wang, Xiujuan;  Kang, Mengzhen;  Hua, Jing;  Guo, Shuangsheng;  de Reffye, Philippe;  Hu, Bao-Gang
浏览  |  Adobe PDF(827Kb)  |  收藏  |  浏览/下载：371/97  |  提交时间：2019/12/16
Closed Ecological Life Support System  Functional-structural Plant Model  Knowledge-and-data-driven Model  Mass Balance Model  Model Evaluation  And Model Verification  
A knowledge-and-data-driven modeling approach for simulating plant growth and the dynamics of CO2/O2 concentrations in a closed system of plants and humans by integrating mechanistic and empirical models 期刊论文
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2018, 卷号: 148, 期号: 0, 页码: 280-290
作者:  Fan, Xing-Rong;  Wang, Xiujuan;  Kang, Mengzhen;  Hua, Jing;  Guo, Shuangsheng;  de Reffye, Philippe;  Hu, Bao-Gang
浏览  |  Adobe PDF(827Kb)  |  收藏  |  浏览/下载：395/92  |  提交时间：2018/10/10
Closed Ecological Life Support System  Functional-structural Plant Model  Knowledge-and-data-driven Model  Mass Balance Model  Model Evaluation  And Model Verification  
Parameter Identifiability in Statistical Machine Learning: A Review 期刊论文
NEURAL COMPUTATION, 2017, 卷号: 29, 期号: 5, 页码: 1151-1203
作者:  Ran, Zhi-Yong;  Hu, Bao-Gang
浏览  |  Adobe PDF(466Kb)  |  收藏  |  浏览/下载：326/97  |  提交时间：2017/07/18
Parameter Identifiability  Statistical Machine Learning  
Robust Recognition via Information Theoretic Learning 专著
Newyork, USA:Springer, 2014
作者:  Ran He(赫然);  Baogang Hu;  Xiaotong Yuan;  Liang Wang
浏览  |  Adobe PDF(2846Kb)  |  收藏  |  浏览/下载：412/123  |  提交时间：2016/08/11
Analytic Study of a Stochastic Plant Architectural Model: Application to the GreenLab Model 期刊论文
Mathematics and Computers in Simulation., 2008, 期号: 78, 页码: 57-75
作者:  Kang, Mengzhen;  Cournède, Paul-Henry;  de Reffye, Philippe;  Hu, Bao-Gang
浏览  |  Adobe PDF(1163Kb)  |  收藏  |  浏览/下载：210/38  |  提交时间：2016/04/13
Greenlab  Analytical Moments  Recurrent Computation  Bud Probability  Stochastic Functional–structural Plant Model  
Analytical study of a stochastic plant growth model: Application to the GreenLab model 期刊论文
MATHEMATICS AND COMPUTERS IN SIMULATION, 2008, 卷号: 78, 期号: 1, 页码: 57-75
作者:  Kang, M. Z.;  Cournede, P. H.;  de Reffye, P.;  Auclair, D.;  Hu, B. G.
浏览  |  Adobe PDF(1284Kb)  |  收藏  |  浏览/下载：258/65  |  提交时间：2015/11/08
Greenlab  Analytical Moments  Recurrent Computation  Bud Probability  Stochastic Functional-structural Plant Model  
A knowledge-and-data-driven modeling approach for simulating plant growth: A case study on tomato growth 期刊论文
ECOLOGICAL MODELLING, 2015, 卷号: 312, 页码: 363-373
作者:  Fan, Xing-Rong;  Kang, Meng-Zhen;  Heuvelink, Ep;  de Reffye, Philippe;  Hu, Bao-Gang;  Kang MZ(康孟珍)
浏览  |  Adobe PDF(1168Kb)  |  收藏  |  浏览/下载：511/65  |  提交时间：2015/09/23
Data-driven Model  Knowledge-driven Model  Greenlab  Knowledge-and-data-driven Model  Model Integration  Plant Growth Modeling  
An identifying function approach for determining parameter structure of statistical learning machines 期刊论文
NEUROCOMPUTING, 2015, 卷号: 162, 页码: 209-217
作者:  Ran, Zhi-Yong;  Hu, Bao-Gang
Adobe PDF(386Kb)  |  收藏  |  浏览/下载：318/77  |  提交时间：2015/09/17
Identifying Function  Structural Identifiability  Statistical Learning Machine  Kullback-leibler Divergence  Parameter Redundancy  Reparameterization  
Determining structural identifiability of parameter learning machines 期刊论文
NEUROCOMPUTING, 2014, 卷号: 127, 期号: 1, 页码: 88-97
作者:  Ran, Zhi-Yong;  Hu, Bao-Gang
浏览  |  Adobe PDF(515Kb)  |  收藏  |  浏览/下载：301/74  |  提交时间：2015/08/12
Identifiability  Parameter Learning Machine  Exhaustive Summary  Kullback-leibler Divergence  Parameter Redundancy