中国科学院机构知识库网格系统: 检索

Crop-climate model in support of adjusting local ecological calendar in the Taxkorgan, eastern Pamir Plateau 期刊论文 OAI收割
CLIMATIC CHANGE, 2021, 卷号: 167, 期号: 3-4, 页码: 56
作者: Yang,Huizhao; Ranjitkar,Sailesh; Xu,Wenxuan; Han,Lei; Yang,Jianbo

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收藏 | 浏览/下载：51/0 | 提交时间：2022/04/02

Climate change Local calendar Crop-climate model GDD Evapotranspiration Calendar adjustment FARMERS PERCEPTIONS GRAIN-YIELD VARIABILITY MAIZE CHINA WHEAT ADAPTATION IMPACTS UNCERTAINTIES PRODUCTIVITY

A review of progress in coupled ocean-atmosphere model developments for ENSO studies in China CNKI期刊论文 OAI收割
2020
作者: ZHANG Rong-Hua; YU Yongqiang; SONG Zhenya; REN Hong-Li; TANG Youmin

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收藏 | 浏览/下载：8/0 | 提交时间：2024/12/18

El Ni?o-Southern Oscillation(ENSO) coupled ocean-atmosphere models simulations and predictions model biases and uncertainties

Fixed-time observer based adaptive neural network time-varying formation tracking control for multi-agent systems via minimal learning parameter approach 期刊论文 OAI收割
IET CONTROL THEORY AND APPLICATIONS, 2020, 卷号: 14, 期号: 9, 页码: 1147-1157
作者: Xiong, Tianyi; Pu, Zhiqiang; Yi, Jianqiang; Tao, Xinlong

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收藏 | 浏览/下载：56/0 | 提交时间：2020/07/06

neurocontrollers multi-agent systems Lyapunov methods closed loop systems nonlinear control systems time-varying systems adaptive control observers uncertain systems position control radial basis function networks robust control control system synthesis learning (artificial intelligence) minimal learning-parameter approach fixed-time CLSO time-varying formation tracking problem formation tracking control scheme multiagent systems time-varying formation tracking control problem model uncertainties velocity measurements radial basis function neural networks fixed-time cascaded leader state observer fixed-time observer-based adaptive neural network time-varying formation tracking control RBFNN-based adaptive control scheme

Comparison of simulated backgrounds with in-orbit observations for HE, ME, and LE onboard Insight-HXMT 期刊论文 OAI收割
Astrophysics and Space Science, 2020, 卷号: 365, 页码: 158
作者: HXMT

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收藏 | 浏览/下载：53/0 | 提交时间：2022/02/08

Insight-HXMT Geant4 simulation Background observation Astrophysics - Instrumentation and Methods for Astrophysics Abstract: Insight-HXMT, the first X-ray astronomical satellite in China, aims to reveal new sources in the Galaxy and to study fundamental physics of X-ray binaries from 1 to 250 keV. It has three collimated telescopes, the High Energy X-ray telescope (HE), the Medium Energy X-ray telescope (ME), and the Low Energy X-ray telescope (LE). Before the launch, in-orbit backgrounds of these three telescopes had been estimated through Geant4 simulation, in order to investigate the instrument performance and the achievement of scientific goals. In this work, these simulated backgrounds are compared with in-orbit observations. Good agreements are shown for all three telescopes. For HE, (1) the deviation of the simulated background rate after two years of operation in space is 5 % from the observation (2) the total background spectrum and the relative abundance of the 67 keV line show long-term increases both in simulations and observations. For ME, (1) the deviation of simulated background rate is within 15 % from the observation, and (2) there are no obvious long-term increase features in the background spectra of simulations and observations. For LE, the background level given by simulations is also consistent with observations. The consistencies of these comparisons validate that the Insight-HXMT mass model, i.e., space environment components and models adopted, physics processes selected, and detector constructions built, is reasonable. However, the line features at 7.5 and 8.0 keV, which are obvious in the observed spectra of LE, are not evident in simulations. This might result from uncertainties in the LE constructions.

Adaptive sliding mode current control with sliding mode disturbance observer for PMSM drives 期刊论文 OAI收割
Isa Transactions, 2019, 卷号: 88, 页码: 113-126
作者: Y.F.Deng; J.L.Wang; H.W.Li; J.Liu; D.P.Tian

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收藏 | 浏览/下载：33/0 | 提交时间：2020/08/24

Adaptive sliding mode control,Model uncertainties,Sliding mode,disturbance observer,Permanent magnet synchronous motor,External

Improving Winter Wheat Yield Estimation from the CERES-Wheat Model to Assimilate Leaf Area Index with Different Assimilation Methods and Spatio-Temporal Scales 期刊论文 OAI收割
REMOTE SENSING, 2017, 卷号: 9, 期号: 3, 页码: 23
作者: Li, He; Chen, Zhongxin

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收藏 | 浏览/下载：14/0 | 提交时间：2019/09/25

assimilation crop model leaf area index particle filter four-dimensional variational uncertainties spatio-temporal

Improving Winter Wheat Yield Estimation from the CERES-Wheat Model to Assimilate Leaf Area Index with Different Assimilation Methods and Spatio-Temporal Scales 期刊论文 OAI收割
REMOTE SENSING, 2017, 卷号: 9, 期号: 3, 页码: 23
作者: Li, He; Chen, Zhongxin; Liu, Gaohuan; Jiang, Zhiwei; Huang, Chong

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收藏 | 浏览/下载：21/0 | 提交时间：2019/09/25

assimilation crop model leaf area index particle filter four-dimensional variational uncertainties spatio-temporal

Improving Winter Wheat Yield Estimation from the CERES-Wheat Model to Assimilate Leaf Area Index with Different Assimilation Methods and Spatio-Temporal Scales 期刊论文 OAI收割
REMOTE SENSING, 2017, 卷号: 9, 期号: 3, 页码: 23
作者: Li, He; Chen, Zhongxin; Liu, Gaohuan; Jiang, Zhiwei; Huang, Chong

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收藏 | 浏览/下载：23/0 | 提交时间：2019/09/25

assimilation crop model leaf area index particle filter four-dimensional variational uncertainties spatio-temporal

Risk and contributing factors of ecosystem shifts over naturally vegetated land under climate change in China SCI/SSCI论文 OAI收割
2016
作者: Yin Y. Y.; Tang, Q. H.; Wang, L. X.; Liu, X. C.

收藏 | 浏览/下载：31/0 | 提交时间：2016/12/16

environment simulator jules net primary production tibetan plateau model description change impacts carbon-cycle terrestrial co2 sensitivity uncertainties

Risk and contributing factors of ecosystem shifts over naturally vegetated land under climate change in China SCI/SSCI论文 OAI收割
2016
作者: Yin Y. Y.; Tang, Q. H.; Wang, L. X.; Liu, X. C.

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收藏 | 浏览/下载：27/0 | 提交时间：2017/11/09

environment simulator jules net primary production tibetan plateau model description change impacts carbon-cycle terrestrial co2 sensitivity uncertainties