http://ir.wsyu.edu.cn/handle/470302/2 学院在原计算机与电子系、信息科学与技术系的基础上于2012年组建成立。全院目前拥有计算机科学与技术、软件工程、光电信息科学与工程、通信工程、物联网工程、电子信息工程6个本科专业，其中光电信息科学与工程专业为湖北省重点本科培育专业。 Wed, 22 Mar 2023 12:16:52 GMT 2023-03-22T12:16:52Z http://ir.wsyu.edu.cn:80/retrieve/380/信息科学与工程学院.jpg http://ir.wsyu.edu.cn/handle/470302/2 http://ir.wsyu.edu.cn/handle/470302/10310 Title: PM2.5 concentration estimation with 1-km resolution at high coverage over urban agglomerations in China using the BPNN-KED approach and potential application Authors: 朱忠敏 Abstract: Fine particle matter (PM 2.5) significantly affects the atmospheric environment and human health. The satellite-derived aerosol optical depth (AOD), which could represent the concentration of atmospheric particles to a certain extent, is widely used for estimating ambient PM 2.5 concentration, in combination with diverse auxiliary information. However, the general satellite-derived PM 2.5 products exhibit limitation in the application and aggregate analysis of PM 2.5 in urban areas, because of the moderate spatial resolution to match the urban landscape and low spatial coverage making it hard to describe airmass trajectory. In order to explore the potential application value of PM 2.5 concentration products with relatively high spatial coverage and resolution, a two-stage machine learning and geo-statistics coupled model incorporating with a feedback mechanism was proposed in this study. To be specific, we firstly develop a hybrid back-propagation neural network coupled kriging with external drifting approach (BPNN-KED) for estimating 1-km daily PM 2.5 concentration maps at high coverage over four urban agglomerations in China. The model performs well, with R2 up to 0.83 and root mean square error of 14.7 μg/m3 from cross-validation. The daily PM 2.5 maps display an average spatial coverage exceeding 95%, and on an average, each grid produces 350 days of valid estimations annually. In addition, the extra value of the high-coverage PM 2.5 estimates were explored through the more accurate aggregate analysis of urban PM 2.5 pollution level. The advantage of the high-coverage PM 2.5 estimation is demonstrated through daily PM 2.5 hotspot identification over urban areas, providing substantially fine spatially resolved PM 2.5 trends, which offers the potential for daily pollutant emission sources location through satellite remote sensing technology. Moreover, the spatiotemporally continuous PM 2.5 concentrations possess the ability to capture polluted air mass trajectories, thereby offering observational support not only for evaluating the contribution from exogenous pollutants to local PM 2.5 concentrations and but also for providing empirical references for haze warning. • A model coupled machine learning with geostatistics was proposed to estimate PM 2.5 concentrations. • Comprehensive analysis of 1-km PM 2.5 concentration in four urban agglomerations. • Daily spatial coverage of PM 2.5 estimates exceeds 95%, filling in over 70% of the data-missing from satellite AOD. • PM 2.5 distributions indicate severe haze pollution in urban and croplands, as well as in winter. • Potential applications in urban PM 2.5 hotspots location and polluted air mass trajectories capture. Fri, 01 Jan 2021 00:00:00 GMT http://ir.wsyu.edu.cn/handle/470302/10310 2021-01-01T00:00:00Z http://ir.wsyu.edu.cn/handle/470302/10309 Title: Satellite-derived aerosol optical depth fusion combining active and passive remote sensing based on bayesian maximum entropy Authors: 朱忠敏 Abstract: Satellite-derived aerosol optical depth (AOD) is an important parameter for studies related to atmospheric environment, climate change, and biogeochemical cycle. Unfortunately, the relatively high data missing ratio of satellite-derived AOD limits the atmosphere-related research and applications to a certain extent. Accordingly, numerous AOD fusion algorithms have been proposed in recent years. However, most of these algorithms focused on merging AOD products from multiple passive sensors, which cannot complementarily recover the AOD missing values due to cloud obscuration and the misidentification between optically thin cloud and aerosols. In order to address these issues, a spatiotemporal AOD fusion framework combining active and passive remote sensing based on Bayesian maximum entropy methodology (AP-BME) is developed to provide satellite-derived AOD data sets with high spatial coverage and good accuracy in large scale. The results demonstrate that AP-BME fusion significantly improves the spatial coverage of AOD, from an averaged spatial completeness of 27.9%–92.8% in the study areas, in which the spatial coverage improves from 91.1% to 92.8% when introducing Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) AOD data sets into the fusion process. Meanwhile, the accuracy of recovered AOD nearly maintains that of the original satellite AOD products, based on evaluation against ground-based Aerosol Robotic Network (AERONET) AOD. Moreover, the efficacy of the active sensor in AOD fusion is discussed through overall accuracy comparison and two case analyses, which shows that the provision of key aerosol information by the active sensor on haze condition or under thin cloud is important for not only restoring the real haze situations but also avoiding AOD overestimation caused by cloud optical depth (COD) contamination in AOD fusion results. Sat, 01 Jan 2022 00:00:00 GMT http://ir.wsyu.edu.cn/handle/470302/10309 2022-01-01T00:00:00Z http://ir.wsyu.edu.cn/handle/470302/10187 Title: 基于SpringBoot和Vue的挖掘机配件销售系统设计与实现 Authors: 陈健 Sat, 01 Jan 2022 00:00:00 GMT http://ir.wsyu.edu.cn/handle/470302/10187 2022-01-01T00:00:00Z http://ir.wsyu.edu.cn/handle/470302/10186 Title: 在线歌曲个性化智能推荐平台设计与实现 Authors: 潘安 Sat, 01 Jan 2022 00:00:00 GMT http://ir.wsyu.edu.cn/handle/470302/10186 2022-01-01T00:00:00Z

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