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公平的有向传感器网络方向优化和节点调度算法 被引量:21
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作者 温俊 蒋杰 窦文华 《软件学报》 EI CSCD 北大核心 2009年第3期644-659,共16页
为了解决有向传感器网络中点目标覆盖控制问题,分别提出了两种方向优化算法和一个节点调度协议:改进的贪婪(enhanced greedy algorithm,简称EGA)、公平的方向优化(equitable direction optimization,简称EDO)算法和邻居节点调度协议(nei... 为了解决有向传感器网络中点目标覆盖控制问题,分别提出了两种方向优化算法和一个节点调度协议:改进的贪婪(enhanced greedy algorithm,简称EGA)、公平的方向优化(equitable direction optimization,简称EDO)算法和邻居节点调度协议(neighbors sensing scheduling,NSS).EGA基于覆盖最多未覆盖的目标数选取工作方向,其不足是可能忽略临界目标.EDO优化算法调节节点的工作方向,优先覆盖临界目标,公平分配感知资源,减小目标覆盖度的差异,EDO算法使用效用值评价每个方向对网络覆盖质量的贡献大小,影响效用值的因素包括每个方向上的目标数、目标的覆盖度和邻居节点的方向决策,EDO总是选择效用值最大的方向作为工作方向.NSS协议引入局部覆盖集的概念,通过局部覆盖集判断当前节点是否为冗余节点,并在考虑节点剩余能量时决定节点是否可以转为睡眠,调度协议允许一个节点加入多个覆盖集,覆盖集轮流工作,使网络生存期最大化.仿真实验结果表明,分布式的EDO算法比EGA算法具有更好的方向优化性能,临界目标的覆盖质量提高了30%,同时明显地提高了网络生存期. 展开更多
关键词 有向传感器网络 多覆盖集 效用函数 节点调度
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A multi-resolution global land cover dataset through multisource data aggregation 被引量:24
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作者 YU Le WANG Jie +3 位作者 LI XueCao LI CongCong ZHAO YuanYuan GONG Peng 《Science China Earth Sciences》 SCIE EI CAS 2014年第10期2317-2329,共13页
Recent developments of 30 m global land characterization datasets (e.g., land cover, vegetation continues field) represent the finest spatial resolution inputs for global scale studies. Here, we present results from... Recent developments of 30 m global land characterization datasets (e.g., land cover, vegetation continues field) represent the finest spatial resolution inputs for global scale studies. Here, we present results from further improvement to land cover map- ping and impact analysis of spatial resolution on area estimation for different land cover types. We proposed a set of methods to aggregate two existing 30 m resolution circa 2010 global land cover maps, namely FROM-GLC (Finer Resolution Observa- tion and Monitoring-Global Land Cover) and FROM-GLC-seg (Segmentation), with two coarser resolution global maps on development, i.e., Nighttime Light Impervious Surface Area (NL-ISA) and MODIS urban extent (MODIS-urban), to produce an improved 30 m global land cover map-FROM-GLC-agg (Aggregation). It was pos-processed using additional coarse res- olution datasets (i.e., MCD12Q1, GlobCover2009, MOD44W etc.) to reduce land cover type confusion. Around 98.9% pixels remain 30 m resolution after some post-processing to this dataset. Based on this map, majority aggregation and proportion ag- gregation approaches were employed to create a multi-resolution hierarchy (i.e., 250 m, 500 m, 1 km, 5 km, 10 km, 25 km, 50 km, 100 km) of land cover maps to meet requirements for different resolutions from different applications. Through accuracy assessment, we found that the best overall accuracies for the post-processed base map (at 30 m) and the three maps subse- quently aggregated at 250 m, 500 m, 1 km resolutions are 69.50%, 76.65%, 74.65%, and 73.47%, respectively. Our analysis of area-estimation biases for different land cover types at different resolutions suggests that maps at coarser than 5 km resolution contain at least 5% area estimation error for most land cover types. Proportion layers, which contain precise information on land cover percentage, are suggested for use when coarser resolution land cover data are required. 展开更多
关键词 spatial aggregation LANDSAT MODIS BIODIVERSITY climate change MULTI-RESOLUTION majority vote
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