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- 저자 : Fengchang (검색결과 4 건)
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Risk Regionalization of Meteorological Calamities Based on GIS and Rough Set Theory
Fengchang Xue,Jin Hu,Jin Wang 보안공학연구지원센터 2016 International Journal of u- and e- Service, Scienc Vol.9 No.1
The calculation of risk regionalization of meteorological calamities, usually determines the weight factors involved in the calculation by a subjective evaluation and objective calculation method, and the information should be more accurate or perfect. As the determination of the weight factors of meteorological disasters have limitations by subjective evaluation method and the objective calculation method, since the acquisition of information with multiple dimensions, has uncertainty. We propose a calculation method of meteorological disaster risk zoning of a rough set theory with GIS technology, and use this technology to evaluate the division of spatial unit and spatial factors index. The spatial unit of conditional attributes and decision attributes determine the weight of influence factors based on meteorological disasters. We can also determine the regionalization of the risk of meteorological calamities based on GIS spatial technology. The result indicated that the application of rough sets theory, combined with GIS technology can fully describe the relationship of spatial data though the information is still incomplete and uncertain. Moreover, it can be better to solve the practical problems in the calculation of meteorological disaster risk zoning.
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Evaluating Agricultural Drought Hazard Risk Based on GIS-MCE
Fengchang Xue,Xiaoyi Song,DongDong Shen,Jin Wang 보안공학연구지원센터 2015 International Journal of Signal Processing, Image Vol.8 No.12
Multi-Criteria Evaluation (MCE)is one of applications of multiple criteria decision making(MCDM). GIS is an information system that is designed to work with data referenced by spatial or geographic coordinates. GIS combined with MCE can achieve measurable evaluation of drought risk. Technologies of evaluating agriculture meteorological drought risk with GIS-MCE are introduced, Taking precipitation anomaly as main drought evaluation index, the paper calculated the spatial distribution of meteorological factors to the whole region by the interpolation method of IDW. In addition, use multiple regression analysis method to study the correlation of meteorological factors, geography factors and social economic factors. The study fully reflects the important role of population density and regional economic development for drought division, making the drought spatial distribution model more accurate and comprehensive. Ultimately, In considering each factor effects, calculate the multi-factor comprehensive division map by GIS-MCE method, which including establishing evaluation criteria and weight by Delphi method, obtaining the spatial distribution of factors of the meteorological drought risk by diffusing spatial attribute value and implementing evaluation by spatial overlay calculation. The results indicated that technology of GIS-MCE can combine multiple source information associating with agriculture meteorological drought risk and achieve measurable result.
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Abnormal Event Detection Based on Saliency Information
Zhijun Fang,Fengchang Fei,Yuming Fang,Lei Shu,Wanggen Wan 보안공학연구지원센터 2015 International Journal of Multimedia and Ubiquitous Vol.10 No.9
Abnormal event detection is a challenging task in video analysis. In this paper, we propose a new abnormal event detection algorithm for surveillance videos. It is well accepted that human eyes are extremely sensitive to abnormal events and they can quickly pay attention to the locations of these abnormal events in visual scenes. Thus, the characteristics of the Human Visual System (HVS) can be used for abnormal event detection. By exploiting the characteristics of the HVS, we propose an abnormal event detection algorithm based on saliency information. Firstly, the saliency information is extracted from video frames based on the feature contrast. The motion information of video frames is calculated by the multi-scale histogram optical flow (MHOF). Based on the features of saliency information and MHOF, the Support Vector Machine (SVM) is used to train and predict the abnormal events in visual scenes. Experimental results show that the proposed abnormal event detection method can obtain much better performance than the existing ones over the public video database.
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A Novel Objective Quality Assessment for Super-Resolution Images
Lei Shu,Yuming Fang,Zhijun Fang,Yong Yang,Fengchang Fei,Naixue Xiong 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.5
A novel objective quality assessment method is proposed for super-resolution images in this manuscript. We not only estimate the preserved information of each spatial location in the super-resolution image by structural similarity, but also compute the local phase coherence (LPC) with which we can detect the image blur in the super-resolution image. After the preserved structural information and blur information is obtained, an overall evaluation of visual quality of the super-resolution image can be computed. Experimental results show that the proposed objective quality assessment method can be used in the real applications with the original high-resolution images unavailable.
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