The telecom industry is a typical data denseness *** Mining technology could offer decision making support for the telecom merchants'next scheme. This paper is about the key problems of the data mining application...
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The telecom industry is a typical data denseness *** Mining technology could offer decision making support for the telecom merchants'next scheme. This paper is about the key problems of the data mining application in the fiber network and the methods of *** will explain it through two examples, the one is to use the algorithrn of related regulation excavation to analyze the telecom alarm *** practical work,it will help the telecom administration department to make prognostic alarm and deal with the obstacles rapidly,the another one is to use the most common used dijkstra algorithm in shortcut algorithm about the single source point to analyze the problem of the random two nodes'shortest path in fiber network, and draw the flow chart of the algorithm's implement.
This article is conducting a study on the demand forecast from the distribution network system composed of m-distribution centers and *** analyze the characteristics of the regional logistics network. Use the dijkstra...
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This article is conducting a study on the demand forecast from the distribution network system composed of m-distribution centers and *** analyze the characteristics of the regional logistics network. Use the dijkstra shortest path algorithm and gain the shortest path distribution,based on which the inventory demand forecasting model which can obtain the total demand of each distribution center is ***,an example is given to show that the model is correct and feasible.
In this figure, it finds a vertex to another vertex k shortest path algorithm. Provided there are n vertices and edges in the diagram. If the path loops, the time complexity of the algorithm is allowed O（w+nlog n +kw...
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In this figure, it finds a vertex to another vertex k shortest path algorithm. Provided there are n vertices and edges in the diagram. If the path loops, the time complexity of the algorithm is allowed O（w+nlog n +kwlogk）. If the request path does not contain the loop, the time complexity of the algorithm O(kn（w +nlogn） +kwlogk). The algorithm utilizes a simple extension of the dijkstra algorithm determined the end of the length of the shortest path to the other vertices, and then, based on these data, branch and bound method to identify the required path. Experimental results show that the actual running time has relations with the structure of FIG.
This paper introduces an optimal method entitled Dhouib-Matrix-SPP (DM-SPP) in order to solve the Shortest Path Problem with a complexity time of 0 (n + m) where n and m are respectively the number of vertices and edg...
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This paper introduces an optimal method entitled Dhouib-Matrix-SPP (DM-SPP) in order to solve the Shortest Path Problem with a complexity time of 0 (n + m) where n and m are respectively the number of vertices and edges. DM-SPP is a rapid method, it can reduce reasonably the research time and consequently the running time as well as the energy consumption. It is composed of five simple steps repeated in (n-1) iterations and for more clarification a guided step-by-step application of the novel method DM-SPP is presented. Moreover, several examples are solved wherein a fully complete and random distribute graphs are analyzed with the variation of the number of vertices from 20 to 6000 and the number of edges from 49 to 17097565. DM-SPP is coded under Python programming language and all experimental results demonstrate that DM-SPP can rapidly generate the optimal short path. Furthermore, by comparing the complexity time required by DM-SPP to the time prerequisite by dijkstra algorithm, it can be concluded that DM-SPP and dijkstra are concurrent for small instances and for larger instances DM-SPP can easily outperform dijkstra and especially for the case of incomplete undirected graphs which are more realistic in the real-world viewing that all graphs are really not complete. The performance of DM-SPP is statistically confirmed with the Mann-Whitney U nonparametric test Further research trends will focus on the test of DM-SPP for the uncertain Shortest Path problem and the resolution of the autonomous mobile robot path planning problem.
Quantified environment model was the basis for quantitative study on path planning of mobile robots. By using free-space method, the two-dimensional weighted network topology was created according to mobile robot envi...
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Quantified environment model was the basis for quantitative study on path planning of mobile robots. By using free-space method, the two-dimensional weighted network topology was created according to mobile robot environment. The path length of environment was modeled with length matrix and the path width of environment was modeled with width matrix. The quantitative path planning was implemented by comparing the path width with the size of robot body and changing the path width in the dijkstra algorithm. The efficiency of dijkstra algorithm was also improved. The simulation showed that the path planning algorithm was correct and valid.
A genetic algorithmic approach to the shortest path (SP) routing problem in large network was presented in order to improve the efficiency of computation. Encoding chromosome with variable length was applied for impro...
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A genetic algorithmic approach to the shortest path (SP) routing problem in large network was presented in order to improve the efficiency of computation. Encoding chromosome with variable length was applied for improving the efficiency of solving problem. A search capability that can improve quality of solution and enhance rate of convergence for network with lots of nodes is found by making crossover and mutation. Because crossover and mutation may generate infeasible chromosomes, a simple repair function is used to cure all the infeasible chromosomes, which keep the diversity of the population and can be used for computation of genetic algorithm to improve the efficiency of computation. Simulation results for SP in the large network indicate that the using time of GA is less than that of dijkstra algorithm in the same network. So the efficiency of the genetic algorithm is much better than that of the dijkstra algorithm for SP in large network.
This paper defines the adjacent cost matrix and the path matrix based on the directed weighted-graph, and defines a new operator that 'summarization then minimum' replace 'multiplication then summarization...
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This paper defines the adjacent cost matrix and the path matrix based on the directed weighted-graph, and defines a new operator that 'summarization then minimum' replace 'multiplication then summarization' between two adjacent cost matrixs, named 'minimum of summarization sequence between two multiplication position elements of the two matrixs'. Based on this new matrix operator, this paper proposes a new algorithm to the shortest path problem within a directed graph. This algorithm can get the global shortest path out for any types of graph. dijkstra algorithm is a well-known good solution to the shortest path problem, but it will result out a fake path to some kinds of graph. The algorithm presented by this paper completely overcome this phenomena out of Dijikstra algorithm.
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