节点部署优化 微粒群算法的改进 无线传感器网络
2019-12-21 21:06:35 132KB 微粒群算法
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Inputs: [AorV] Either A or V where A is a NxN adjacency matrix, where A(I,J) is nonzero if and only if an edge connects point I to point J NOTE: Works for both symmetric and asymmetric A V is a Nx2 (or Nx3) matrix of x,y,(z) coordinates [xyCorE] Either xy or C or E (or E3) where xy is a Nx2 (or Nx3) matrix of x,y,(z) coordinates (equivalent to V) NOTE: only valid with A as the first input C is a NxN cost (perhaps distance) matrix, where C(I,J) contains the value of the cost to move from point I to point J NOTE: only valid with A as the first input E is a Px2 matrix containing a list of edge connections NOTE: only valid with V as the first input E3 is a Px3 matrix containing a list of edge connections in the first two columns and edge weights in the third column NOTE: only valid with V as the first input [SID] (optional) 1xL vector of starting points. If unspecified, the algorithm will calculate the minimal path from all N points to the finish point(s) (automatically sets SID = 1:N) [FID] (optional) 1xM vector of finish points. If unspecified, the algorithm will calculate the minimal path from the starting point(s) to all N points (automatically sets FID = 1:N) Outputs: [costs] is an LxM matrix of minimum cost values for the minimal paths [paths] is an LxM cell containing the shortest path arrays [showWaitbar] (optional) a scalar logical that initializes a waitbar if nonzero Note: If the inputs are [A,xy] or [V,E], the cost is assumed to be (and is calculated as) the point to point Euclidean distance If the inputs are [A,C] or [V,E3], the cost is obtained from either the C matrix or from the edge weights in the 3rd column of E3 Example: % Calculate the (all pairs) shortest distances and paths using [A,C] inputs n = 7; A = zeros(n); xy = 10*rand(n,2) tri = delaunay(xy(:,1),xy(:,2)); I = tri(:); J = tri(:,[2 3 1]); J = J(:); IJ = I + n*(J-1); A(IJ) = 1 a = (1:n); b = a(ones(n,1),:); C = round(reshape(sqrt(sum((xy(b,:) -
2019-12-21 21:05:49 4KB 路由WSN
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NS-2学习的好教材,跟大家分享,pdf文档,学习ns-2中的wsn无线模拟技术 和ns2中的tcl脚本语言技术等
2019-12-21 21:05:30 507KB NS-2 WSN
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LEACH协议 全称是“低功耗自适应集簇分层型协议” Low Energy Adaptive Clustering Hierarchy 是一种无线传感器网络路由协议 基于LEACH协议的算法 称为LEACH算法
2019-12-21 21:04:57 8KB WSN 路由协议 MATLAB
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基于DV-Hop的无线传感网络定位算法的matlab仿真代码。研究定位误差与锚节点个数和通信半径的关系。设定在100*100的区域内,总节点数为100,分别计算出通信半径为15,25,50时,定位误差随锚节点个数3~30改变时的变化情况。
2019-12-21 21:04:51 7KB 无线传感网络 DV-Hop 定位 Matlab
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应用蚁群,物联网,WSN路由选择算法,北卡大学
2019-12-21 21:02:41 708KB 应用蚁群 WSN
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基于OPNET的无线传感器网络仿真 基于OPNET的无线传感器网络仿真
2019-12-21 21:02:35 791KB OPNET wsn
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WSN仿真-MATLAB基于COMPOW协议下的网络连通率和覆盖率,附源代码(注释详尽)。WSN仿真-MATLAB基于COMPOW协议下的网络连通率和覆盖率,附源代码(注释详尽)。
2019-12-21 20:48:06 141KB WSN仿真
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WSN仿真-MATLAB节点个数和节点通信半径与网络连通率的关系,附源代码(注释详细) WSN仿真-MATLAB节点个数和节点通信半径与网络连通率的关系,附源代码(注释详细)
2019-12-21 20:48:06 146KB WSN仿真
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WSN仿真-Leach分簇+能量消耗控制,附源代码(注释详细)WSN仿真-Leach分簇+能量消耗控制,附源代码(注释详细)
2019-12-21 20:48:06 3KB WSN仿真
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