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	Spatio-temporal evolution and dynamic simulation of the urban resilience of Beijing-Tianjin-Hebei urban agglomeration 期刊论文 OAI收割 JOURNAL OF GEOGRAPHICAL SCIENCES, 2022, 卷号: 32, 期号: 9, 页码: 1766-1790 作者: Mu Xufang; Fang Chuanglin; Yang Zhiqi \| 收藏 \| 浏览/下载：23/0 \| 提交时间：2022/09/26 urban agglomeration urban resilience Beijing-Tianjin-Hebei (BTH) evaluation system gray prediction model
	Spatio-temporal evolution and dynamic simulation of the urban resilience of Beijing-Tianjin-Hebei urban agglomeration 期刊论文 OAI收割 JOURNAL OF GEOGRAPHICAL SCIENCES, 2022, 卷号: 32, 期号: 9, 页码: 1766-1790 作者: Mu Xufang; Fang Chuanglin; Yang Zhiqi \| 收藏 \| 浏览/下载：45/0 \| 提交时间：2022/09/26 urban agglomeration urban resilience Beijing-Tianjin-Hebei (BTH) evaluation system gray prediction model
	Migration node selection strategy based on gray prediction algorithm in trusted environment 会议论文 OAI收割 Guangzhou, China, January 14-16, 2022 作者: Wang C(王晨); Zhang BW(张博文); Chen X(陈鑫) \| 收藏 \| 浏览/下载：61/0 \| 提交时间：2022/04/13 gray prediction task migration trusted security model
	Gray Matter Volume Predicts Individual Body Mass Index and Its Development during Adolescence 会议论文 OAI收割 Xi'an, China, May 21-23, 2021 作者: Wang, Haiyan; Jiang, Tianzi \| 收藏 \| 浏览/下载：33/0 \| 提交时间：2021/06/17 BMI Individualized prediction Adolescence Development Gray matter volume
	Prediction of trust propensity from intrinsic brain morphology and functional connectome 期刊论文 OAI收割 HUMAN BRAIN MAPPING, 2020, 页码: 17 作者: Feng, Chunliang; Zhu, Zhiyuan; Cui, Zaixu; Ushakov, Vadim; Dreher, Jean-Claude \| 收藏 \| 浏览/下载：68/0 \| 提交时间：2020/11/30 functional decoding gray matter individualized prediction large-scale brain networks trust propensity
	Gray BP neural network based prediction of rice protein interaction network. 期刊论文 OAI收割 Cluster Computing, 2018 作者: Wang X(王雪) \| 收藏 \| 浏览/下载：17/0 \| 提交时间：2021/12/15 Gray value BP neural network Rice protein interaction Prediction
	Research on infrared dim-point target detection and tracking under sea-sky-line complex background (EI CONFERENCE) 会议论文 OAI收割 International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China 作者: Dong Y.-X.; Zhang H.-B.; Li Y.; Li Y.; Li Y. 收藏 \| 浏览/下载：113/0 \| 提交时间：2013/03/25 Target detection and tracking technology in infrared image is an important part of modern military defense system. Infrared dim-point targets detection and recognition under complex background is a difficulty and important strategic value and challenging research topic. The main objects that carrier-borne infrared vigilance system detected are sea-skimming aircrafts and missiles. Due to the characteristics of wide field of view of vigilance system the target is usually under the sea clutter. Detection and recognition of the target will be taken great difficulties.There are some traditional point target detection algorithms such as adaptive background prediction detecting method. When background has dispersion-decreasing structure the traditional target detection algorithms would be more useful. But when the background has large gray gradient such as sea-sky-line sea waves etc.The bigger false-alarm rate will be taken in these local area.It could not obtain satisfactory results. Because dim-point target itself does not have obvious geometry or texture feature in our opinion from the perspective of mathematics the detection of dim-point targets in image is about singular function analysis.And from the perspective image processing analysis the judgment of isolated singularity in the image is key problem. The foregoing points for dim-point targets detection its essence is a separation of target and background of different singularity characteristics.The image from infrared sensor usually accompanied by different kinds of noise. These external noises could be caused by the complicated background or from the sensor itself. The noise might affect target detection and tracking. Therefore the purpose of the image preprocessing is to reduce the effects from noise also to raise the SNR of image and to increase the contrast of target and background. According to the low sea-skimming infrared flying small target characteristics the median filter is used to eliminate noise improve signal-to-noise ratio then the multi-point multi-storey vertical Sobel algorithm will be used to detect the sea-sky-line so that we can segment sea and sky in the image. Finally using centroid tracking method to capture and trace target. This method has been successfully used to trace target under the sea-sky complex background. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
	灰色理论在邵阳地区大旱预测中的应用(英文) 期刊论文 OAI收割 Agricultural Science & Technology, 2010, 期号: 1, 页码: 138-139+162 谭德权; 张果军; 吕校华; 沈谨; 戚平; 王卫农收藏 \| 浏览/下载：31/0 \| 提交时间：2013/03/06 Shaoyang district Gray disaster theory Great drought prediction