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	Building the concept semantic space for large text database 期刊论文 OAI收割 COMPUTER SYSTEMS SCIENCE AND ENGINEERING, 2015, 卷号: 30, 期号: 5, 页码: 421-429 作者: Wei, Xiao; Zeng, Daniel Dajun; Wu, Wei; Dai, Yeming 收藏 \| 浏览/下载：27/0 \| 提交时间：2016/03/19 text database concept semantic space multiple semantic granularities multiple semantic dimensions semantic link network concept extraction
	Algorithm research of flexible graphplan based on heuristic (EI CONFERENCE) 会议论文 OAI收割 9th International Conference for Young Computer Scientists, ICYCS 2008, November 18, 2008 - November 21, 2008, Zhang Jia Jie, Hunan, China 作者: Xu S. 收藏 \| 浏览/下载：20/0 \| 提交时间：2013/03/25 Classic Graphplan has too much restriction on capturing the full subtlety of many real problems. Flexible Graphplan is defined which supports the soft constraints often found in reality. Heuristic concept is introduced to the process of plan extraction in flexible graphplan in order to improve the efficiency of plan extraction and the quality of plan. A novel algorithm using the new heuristic function which is applied by improved sum mutex heuristic to deal with planning problems is proposed. Sum mutex heuristic which is in common use as heuristic function takes into account only static propositional mutexes and ignores the mutexes of actions. The performance of the new algorithm on many benchmark problems is remarkably robust. It can solve many planning problems which can't be solved by the heuristic state space search planning system using sum mutex heuristic. 2008 IEEE.
	Intelligent MRTD testing for thermal imaging system using ANN (EI CONFERENCE) 会议论文 OAI收割 ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China Sun J.; Ma D. 收藏 \| 浏览/下载：26/0 \| 提交时间：2013/03/25 The Minimum Resolvable Temperature Difference (MRTD) is the most widely accepted figure for describing the performance of a thermal imaging system. Many models have been proposed to predict it. The MRTD testing is a psychophysical task for which biases are unavoidable. It requires laboratory conditions such as normal air condition and a constant temperature. It also needs expensive measuring equipments and takes a considerable period of time. Especially when measuring imagers of the same type the test is time consuming. So an automated and intelligent measurement method should be discussed. This paper adopts the concept of automated MRTD testing using boundary contour system and fuzzy ARTMAP but uses different methods. It describes an Automated MRTD Testing procedure basing on Back-Propagation Network. Firstly we use frame grabber to capture the 4-bar target image data. Then according to image gray scale we segment the image to get 4-bar place and extract feature vector representing the image characteristic and human detection ability. These feature sets along with known target visibility are used to train the ANN (Artificial Neural Networks). Actually it is a nonlinear classification (of input dimensions) of the image series using ANN. Our task is to justify if image is resolvable or uncertainty. Then the trained ANN will emulate observer performance in determining MRTD. This method can reduce the uncertainties between observers and long time dependent factors by standardization. This paper will introduce the feature extraction algorithm demonstrate the feasibility of the whole process and give the accuracy of MRTD measurement.