首先,设计了节点自适应传感半径调整算法(AASR,adaptive adjustment of sensing radius),通过节点自适应选择最佳的覆盖范围,有效地进行节点覆盖控制,减少节点能量虚耗,提高覆盖效率。其次,从调整效果、能量消耗和覆盖冗余度3个方面对...首先,设计了节点自适应传感半径调整算法(AASR,adaptive adjustment of sensing radius),通过节点自适应选择最佳的覆盖范围,有效地进行节点覆盖控制,减少节点能量虚耗,提高覆盖效率。其次,从调整效果、能量消耗和覆盖冗余度3个方面对节点自适应传感半径调整算法进行了模拟实验和分析。仿真结果表明,AASR能够有效提高节点生存时间,减少能量消耗,提高覆盖率。展开更多
Forest land is the essential and important natural resource that provides strong support for human survival and development. Research on forest land changes at the county level about its characteristics, rules, and sp...Forest land is the essential and important natural resource that provides strong support for human survival and development. Research on forest land changes at the county level about its characteristics, rules, and spatial patterns is, therefore, important for regional resource protection and the sustainable development of the social economy. In this study we selected the GIS and Geoda software package to explore the spatial disparities of forest land changes at the Beijing-Tianjin-Hebei area county level, based on the global and local spatial autocorrelation analyses of exploratory spatial data. The results show that： 1） during 1985-2000, the global spatial autocorrelation of forest land change is significant in the study area. The global Moran＇s I value is 0.3122 for the entire time period and indicates significant positive spatial correlation （p 〈 0.05）. Moran＇s I value of forest land change decreases from 0.3084 at the time stage I to 0.3024 at the time stage II; 2） the spatial clustering characteristics of forest land changes appear on the whole in Beijing- Tianjin-Hebei area. Moran＇s 1 value decreases from the time stage I to time stage II, which means that trend of spatial clustering of forest land change is weakened in the Beijing-Tianjin-Hebei area; 3） the grid map of the local Moran＇s I for each county reflects local spatial homo- geneity of forest land change, which means that spatial clustering about regions of high value and low value is especially significant. The regions with ＂High-High＂ correlation are mainly located in the north hilly area. However, the regions with ＂Low-Low＂ correlation were distributed in the middle of the study area. Therefore, protection strategies and concrete measures should be put in place for each regional cluster in the study area.展开更多
文摘首先,设计了节点自适应传感半径调整算法(AASR,adaptive adjustment of sensing radius),通过节点自适应选择最佳的覆盖范围,有效地进行节点覆盖控制,减少节点能量虚耗,提高覆盖效率。其次,从调整效果、能量消耗和覆盖冗余度3个方面对节点自适应传感半径调整算法进行了模拟实验和分析。仿真结果表明,AASR能够有效提高节点生存时间,减少能量消耗,提高覆盖率。
文摘Forest land is the essential and important natural resource that provides strong support for human survival and development. Research on forest land changes at the county level about its characteristics, rules, and spatial patterns is, therefore, important for regional resource protection and the sustainable development of the social economy. In this study we selected the GIS and Geoda software package to explore the spatial disparities of forest land changes at the Beijing-Tianjin-Hebei area county level, based on the global and local spatial autocorrelation analyses of exploratory spatial data. The results show that： 1） during 1985-2000, the global spatial autocorrelation of forest land change is significant in the study area. The global Moran＇s I value is 0.3122 for the entire time period and indicates significant positive spatial correlation （p 〈 0.05）. Moran＇s I value of forest land change decreases from 0.3084 at the time stage I to 0.3024 at the time stage II; 2） the spatial clustering characteristics of forest land changes appear on the whole in Beijing- Tianjin-Hebei area. Moran＇s 1 value decreases from the time stage I to time stage II, which means that trend of spatial clustering of forest land change is weakened in the Beijing-Tianjin-Hebei area; 3） the grid map of the local Moran＇s I for each county reflects local spatial homo- geneity of forest land change, which means that spatial clustering about regions of high value and low value is especially significant. The regions with ＂High-High＂ correlation are mainly located in the north hilly area. However, the regions with ＂Low-Low＂ correlation were distributed in the middle of the study area. Therefore, protection strategies and concrete measures should be put in place for each regional cluster in the study area.
