人工智能-机器学习-计算机模拟仿真及通信技术在连锁加油站管理系统中的应用.pdf
2022-05-08 09:09:58
3.55MB
asp.net大型多门店连锁汽车4S店维修保养管理系统源码 带数据库说明文档
开发环境： VS2012 SQL2008
采用SQL-Server大型数据库，系统数据绝对稳定安全，并实现了海量模糊查询，局域网即时通讯、条码识别等大量的高新科技
一、源码介绍
采用SQL-Server大型数据库，系统数据绝对稳定安全，并实现了海量模糊查询，局域网即时通讯、条码识别等大量的高新科技，并集成了短信群发等许多先进实用的新功能，并继承了完美软件操作方便、功能强大等的传统风格，凝聚了数万用户的智慧结晶。接车、派工、领料、结算流程清晰，用户操作起来得心应手，省时省心。报表中心提供了维修、工时费、材料费、员工提成、车次排行、车型排行、进货、库存、帐务等一系列报表，统计方法科学，数据准确。
2022-04-30 14:05:33
59.92MB
Complex Networks Toolbox for MatLab is designed to analyze large-scale graphs, model them, explore with simulations of dynamic processes and generate appealing and insightful layouts.
example：
function [BetweenneessCentrality, varargout]= GraphBetweennessCentrality(Graph,SourceNodes)
% Computes betweenneess centrality of each node.
%
% Receives:
% Graph - Graph Struct - the graph loaded with GraphLoad
% SourceNodes - array of double - (optional) nodes, from which passes start. Default: [] (all nodes).
%
% Returns:
% BetweenneessCentrality - array of double - Betweenneess Centrality for each node.
% Nodes - array of double - (optional)List of all nodes for which betweennessn centrality is computed
%
% Algorithm:
% http://www.boost.org/libs/graph/doc/betweenness_centrality.html
%
% See Also:
% mexGraphAllNodeShortestPasses
%
warning('Use the more optimized mexGraphBetweennessCentrality.dll');
error(nargchk(1,2,nargin));
error(nargoutchk(0,2,nargout));
if ~exist('SourceNodes') | isempty(SourceNodes)
SourceNodes = unique(Graph.Data(:,1));
end
Nodes = unique(Graph.Data(:,1:2));
%TotalPasses = zeros(GraphCountNumberOfNodes(Graph),GraphCountNumberOfNodes(Graph));
Betweenness = zeros(GraphCountNumberOfNodes(Graph),1);
for Node = Nodes(:).'
[ShortesPasses PassesHistogram]= mexGraphAllNodeShortestPasses(Graph,Node);
%TotalPasses = TotalPasses + sum(PassesHistogram(2:end));
tic
for i = 1 : numel(ShortesPasses)
%T = ShortesPasses(i).Passes(end);
%TotalPasses(Node,ShortesPasses(i).Passes(end)) = size(ShortesPasses(i).Passes,2); % compute total number of shortes passes from Node to some other node.
Passes = ShortesPasses(i).Passes(2:end-1,:);
NodesOnTheWay = unique(Passes);
if numel(NodesOnTheWay)==1
Count = 1; % hist behaves differently in this case.
else
Count = hist(Passes(:),NodesOnTheWay);
2022-04-26 20:46:45
24.47MB
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