This text surrounds the development of the electric power SCADA system exactly, aiming at the present condition of the our country electric power charged barbed wire net currently, according to the oneself at the e- lectric power protect the profession after the electricity in seven years of development, design and adjust to try the experience on the scene from following severals carry on the treatise:Is the emergence to the system of SC- ADA and developments to introduce first Carry on the introduction elucidation to applied present condition and the development foregrounds of various terminal equipments communication agreement(rules invite) the next in order Then is the elucidation to the windows the bottom according to the mfc the plait distance environment an- d VC++6.0 plait distance softwares Carry on the more detailed treatise to the realization of the procedure struct- ure frame and the source code again End is the applied case example give examples.
标签： the development surrounds electric
上传时间： 2014-10-28
上传用户：liuchee
Implemented BFS, DFS and A* To compile this project, use the following command: g++ -o search main.cpp Then you can run it: ./search The input is loaded from a input file in.txt Here is the format of the input file: The first line of the input file shoud contain two chars indicate the source and destination city for breadth first and depth first algorithm. The second line of input file shoud be an integer m indicate the number of connections for the map. Following m lines describe the map, each line represents to one connection in this form: dist city1 city2, which means there is a connection between city1 and city2 with the distance dist. The following input are for A* The following line contains two chars indicate the source and destination city for A* algorithm. Then there is an integer h indicate the number of heuristic. The following h lines is in the form: city dist which means the straight-line distance from the city to B is dist.
标签： Implemented following compile command
上传时间： 2014-01-01
上传用户：lhc9102
this m file can Find a (near) optimal solution to the Traveling Salesman Problem (TSP) by setting up a Genetic Algorithm (GA) to search for the shortest path (least distance needed to travel to each city exactly once) Notes: 1. Input error checking included 2. Inputs can be specified in any order, so long as the parameter pairs are specified as a parameter , value
标签： Traveling Salesman solution Problem
上传时间： 2013-12-22
上传用户：ruixue198909
A system simulation environment in Matlab/Simulink of RFID is constructed in this paper. Special attention is emphasized on the analog/RF circuit.Negative effects are concerned in the system model,such as phase noise of the local oscillator,TX-RX coupling,reflection of the environment, AWGN noise,DC offset,I/Q mismatch,etc.Performance of the whole system can be evaluated by changing the coding method,parameters of building blocks,and operation distance.Finally,some simulation results are presented in this paper.
标签： environment constructed simulation Simulink
上传时间： 2014-01-09
上传用户：zhangliming420
Finds a (near) optimal solution to the Traveling Salesman Problem (TSP) by setting up a Genetic Algorithm (GA) to search for the shortest path (least distance needed to travel to each city exactly once)
标签： Traveling Salesman solution Problem
上传时间： 2013-12-04
上传用户：从此走出阴霾
Dijkstra算法求最短路径(C#版) using System using System.Collections using System.Text namespace Greedy { class Marx { private int[] distance private int row private ArrayList ways = new ArrayList() public Marx(int n,params int[] d) { this.row = n distance = new int[row * row] for (int i = 0 i < row * row i++) { this.distance[i] = d[i]
标签： System using Collections namespace
上传时间： 2013-12-29
上传用户：liglechongchong
Traveling Salesman Problem (TSP) has been an interesting problem for a long time in classical optimization techniques which are based on linear and nonlinear programming. TSP can be described as follows: Given a number of cities to visit and their distances from all other cities know, an optimal travel route has to be found so that each city is visited one and only once with the least possible distance traveled. This is a simple problem with handful of cities but becomes complicated as the number increases.
标签： interesting Traveling classical Salesman
上传时间： 2016-02-06
上传用户：rocwangdp
How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.
标签： the decision clusters Cluster
上传时间： 2013-12-21
上传用户：gxmm
压缩解压算法LZ77算法有许多派生算法(这里面包括 LZSS算法)。它们的算法原理上基本都相同，无论是哪种派生算法，LZ77算法总会包含一个动态窗口（Sliding Window）和一个预读缓冲器（Read Ahead Buffer）。动态窗口是个历史缓冲器，它被用来存放输入流的前n个字节的有关信息。一个动态窗口的数据范围可以从 0K 到 64K，而LZSS算法使用了一个4K的动态窗口。预读缓冲器是与动态窗口相对应的，它被用来存放输入流的前n个字节，预读缓冲器的大小通常在0 – 258 之间。这个算法就是基于这些建立的。用下n个字节填充预读缓存器（这里的n是预读缓存器的大小）。在动态窗口中寻找与预读缓冲器中的最匹配的数据，如果匹配的数据长度大于最小匹配长度 （通常取决于编码器，以及动态窗口的大小，比如一个4K的动态窗口，它的最小匹配长度就是2），那么就输出一对〈长度（length），距离（distance）〉数组。长度(length)是匹配的数据长度，而距离(distance)说明了在输入流中向后多少字节这个匹配数据可以被找到。
上传时间： 2014-01-22
上传用户：tzl1975
Basic hack v2.1 by xgx - http://www.ring0.donster.de/ Features: - Smooth Vector Aimbot - Full ESP ( Namen,Weapon,distance,Visible,Far) - polymorph,peb hiding to prevent VAC detection
标签： Features donster Aimbot Smooth
上传时间： 2013-12-18
上传用户：agent
