中国科学院机构知识库网格系统: 检索

Cluster-based local modeling (CBLM) paradigm meets deep learning: A novel approach to soil moisture estimation 期刊论文 OAI收割
JOURNAL OF HYDROLOGY, 2024, 卷号: 635, 页码: 26
作者: Moosavi, Vahid; Zuravand, Golnaz; Shamsi, Seyed Rashid Fallah

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收藏 | 浏览/下载：22/0 | 提交时间：2024/07/24

Soil moisture modeling Clustering algorithms Global modeling approach Local modeling approach

Algorithms for the metric ring star problem with fixed edge-cost ratio 期刊论文 OAI收割
JOURNAL OF COMBINATORIAL OPTIMIZATION, 2021, 卷号: 42, 期号: 3, 页码: 499-523
作者: Chen, Xujin; Hu, Xiaodong; Jia, Xiaohua; Tang, Zhongzheng; Wang, Chenhao

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收藏 | 浏览/下载：37/0 | 提交时间：2022/04/02

Ring star Approximation algorithms Heuristics Local search Connected facility location

Identifying Top-k Influential Nodes Based on Discrete Particle Swarm Optimization With Local Neighborhood Degree Centrality 期刊论文 OAI收割
IEEE ACCESS, 2021, 卷号: 9, 页码: 21345-21356
作者: Han, Lihong; Zhou, Qingguo; Tang, Jianxin; Yang, Xuhui; Huang, Hengjun

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收藏 | 浏览/下载：24/0 | 提交时间：2021/12/10

Social networking (online) Particle swarm optimization Optimization Search problems Integrated circuit modeling Heuristic algorithms Social sciences Discrete particle swarm optimization local search strategy neighbourhood degree centrality top-k influential nodes social network

Distributed optimisation approach to least-squares solution of Sylvester equations 期刊论文 OAI收割
IET CONTROL THEORY AND APPLICATIONS, 2020, 卷号: 14, 期号: 18, 页码: 2968-2976
作者: Deng, Wen; Zeng, Xianlin; Hong, Yiguang

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收藏 | 浏览/下载：60/0 | 提交时间：2021/01/14

least squares approximations distributed control stability distributed algorithms continuous time systems matrix algebra convex programming multi-robot systems convex optimisation distributed optimisation approach least-squares solution Sylvester equations distributed algorithms multiagent network problem setup interconnected system local information data matrices neighbour agents continuous-time algorithms optimisation problem

Greedy Adaptive Search: A New Approach for Large-Scale Irregular Packing Problems in the Fabric Industry 期刊论文 OAI收割
IEEE ACCESS, 2020, 卷号: 8, 页码: 91476-91487
作者: Hu, Xiaoyin; Li, Jianshu; Cui, Jinchuan

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收藏 | 浏览/下载：58/0 | 提交时间：2020/09/23

Fabrics Search problems Industries Layout Heuristic algorithms Mathematical model Biological system modeling Evaluation function fabric no-fit polygon packing restricted local search

Spatial Resolution and Precision Properties of Scatterometer Reconstruction Algorithms 期刊论文 OAI收割
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2017, 卷号: 10, 期号: 5, 页码: 2372-2382
作者: Liu, Liling; Dong, Xiaolong; Lin, Wenming; Zhu, Jintai; Zhu, Di

收藏 | 浏览/下载：36/0 | 提交时间：2017/09/14

Local impulse response reconstruction algorithms resolution scatterometer spatial response function (SRF)

Performances of pure random walk algorithms on constraint satisfaction problems with growing domains 期刊论文 OAI收割
JOURNAL OF COMBINATORIAL OPTIMIZATION, 2016, 卷号: 32, 期号: 1, 页码: 51-66
作者: Xu, Wei; Gong, Fuzhou

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收藏 | 浏览/下载：17/0 | 提交时间：2018/07/30

Constraint satisfaction problems Model RB Random walk Local search algorithms

Activity Sensor: Check-In Usage Mining for Local Recommendation 期刊论文 OAI收割
ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY, 2015, 卷号: 6, 期号: 3
作者: Sang, Jitao; Mei, Tao; Xu, Changsheng

收藏 | 浏览/下载：24/0 | 提交时间：2015/09/17

Design Algorithms Performance Location-based service local recommendation check-in usage mining

The new approach for infrared target tracking based on the particle filter algorithm (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: Sun H.; Han H.-X.; Sun H.

收藏 | 浏览/下载：63/0 | 提交时间：2013/03/25

Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring precision and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure but in order to capture the change of the state space it need a certain amount of particles to ensure samples is enough and this number will increase in accompany with dimension and increase exponentially this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining" we expand the classic Mean Shift tracking framework.Based on the previous perspective we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value.Last because of the gray and fusion target motion information this approach also inhibit interference from the background ultimately improve the stability and the real-time of the target track. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

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：116/0 | 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).