The unbalanced development strategy makes the regional development unbalanced. Therefore, in the development process, resources must be effectively utilized according to the level and characteristics of each region. C...
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The unbalanced development strategy makes the regional development unbalanced. Therefore, in the development process, resources must be effectively utilized according to the level and characteristics of each region. Considering the resource and environmental constraints, this paper measures and analyzes China's green economic efficiency and green total factor productivity. Moreover, by expounding the characteristics of high-dimensional data, this paper points out the problems of traditional clusteringalgorithms in high-dimensional data clustering. This paper proposes a density peak clusteringalgorithm based on sampling and residual squares, which is suitable for high-dimensional large data sets. The algorithm finds abnormal points and boundary points by identifying halo points, and finally determines clusters. In addition, from the experimental comparison on the data set, it can be seen that the improved algorithm is better than the DPC algorithm in both time complexity and clustering results. Finally, this article analyzes data based on actual cases. The research results show that the method proposed in this paper is effective.
The rapid development of the global shipping industry and the changes in complex marine environments have put forward higher requirements for ship formation and route optimization. The purpose of the research is to im...
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The rapid development of the global shipping industry and the changes in complex marine environments have put forward higher requirements for ship formation and route optimization. The purpose of the research is to improve the efficiency and accuracy of ship formation and route planning through improved algorithms. Based on this, a ship formation model combining improved particle swarm optimization algorithm and a generative route optimization method based on improved Douglas-Peucker algorithm are proposed. The particle swarm algorithm introduces dynamic adaptive parameter adjustment and the cross mutation strategy of genetic algorithm, while the Douglas-Peucker algorithm integrates density-based noise application spatial clustering algorithm to improve model performance. The test results show that the total navigation distance of the allocation path generated by the ship formation model is 605.3 meters, the calculation time is 31.8 seconds, and all ships can be accurately allocated to the target point. When the number of iterations is 1000, the route optimization model has a route coverage rate of 95.9% on the training set, an average error of 30.5 meters, and a computation time of 45.9 seconds, achieving zero collisions. The experimental results show that the improved algorithm outperforms traditional methods in accuracy and stability of formation target allocation and route planning, especially under complex sea conditions, and can significantly reduce computation time and errors. The research provides a new technological means for optimizing ship formations and routes, which has certain application potential and practical value.
This article deals with social infrastructure planning problems in urban city. Each facility must serve minimum pre-specified level of demand. The objective is to minimize the distance traveled by users to reach the f...
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ISBN:
(纸本)9780769549637;9781467356534
This article deals with social infrastructure planning problems in urban city. Each facility must serve minimum pre-specified level of demand. The objective is to minimize the distance traveled by users to reach the facilities this means also to maximize the accessibility to facilities. A location model that captures the above features is formulated and different solution methods are tested. clustering in spatial data mining is to group similar objects based on their connectivity, distance, or their relative density in space. In real word, there exist many physical obstacles such as rivers, lakes, highways and mountains, and their presence may affect the result of clustering significantly. In this paper, we study the problem of clustering in the presence of obstacles to solve location of public service facility problem. In this paper, CSPOD-DBSCAN algorithm (clustering with short path Obstructed Distance - Density-Based spatialclustering of Applications with Noise) is developed in the spirit of DBSCAN clusteringalgorithms. This algorithm is Density-based clusteringalgorithm using Dijkstra algorithm to calculate obstructed short path distance. The application of this algorithm is illustrated through a case study involving the location of schools in the districts of Mecca in Saudi Arabia.
clustering in spatial data mining is to group similar objects based on their distance, connectivity, or their relative density in space. In real word, there exist many physical obstacles such as rivers, lakes, highway...
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ISBN:
(纸本)9789898425799
clustering in spatial data mining is to group similar objects based on their distance, connectivity, or their relative density in space. In real word, there exist many physical obstacles such as rivers, lakes, highways and mountains, and their presence may affect the result of clustering substantially. Today existing telephone networks nearing saturation and demand for wire and wireless services continuing to grow, telecommunication engineers are looking at technologies that will deliver sites and can satisfy the required demand and grade of service constraints while achieving minimum possible costs. In this paper, we study the problem of clustering in the presence of obstacles to solve network planning problem. In this paper, COD-DBSCAN algorithm (clustering with Obstructed Distance-Density-Based spatialclustering of Applications with Noise) is developed in the spirit of DBSCAN clusteringalgorithms. We studied also the problem determine the place of Multi Service Access Node (MSAN) due to the presence of obstacles in area complained of the existence of many mountains such as in Saudi Arabia. This algorithm is Density-based clusteringalgorithm using BSP-tree and Visibility Graph to calculate obstructed distance. Experimental results and analysis indicate that the COD-DBSCAN algorithm is both efficient and effective.
With existing telephone networks nearing saturation and demand for wire and wireless services continuing to grow, telecommunication engineers are looking at technologies that will deliver sites and can satisfy the req...
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ISBN:
(纸本)9781424453849
With existing telephone networks nearing saturation and demand for wire and wireless services continuing to grow, telecommunication engineers are looking at technologies that will deliver sites and can satisfy the required demand and grade of service constraints while achieving minimum possible costs. The city data is given as a map of streets, intersection nodes coordinates, distribution of the subscribers' loads within the city and the location of base station in mobile network in this city. The available cable sizes, the cost per unit for each size and the maximum distance of wire that satisfied the allowed grade of service. Net Plan (Network Planning package) is developed in the spirit of DBSCAN and Agglomerative clusteringalgorithms. In this paper we studied the problem of congestion in Multi Service Access Node (MSAN) due to the increasing the number of subscribers which cause degradation in grade of service and in some time impossible to add new subscribers. The Net Plan algorithm is introduced to solve this problem. This algorithm is Density-based clusteringalgorithm using physical shortest paths available routes and the subscriber loads. In other hand decreasing the cost also is our deal in this paper so in the second phase in clustering process we modify the agglomerative algorithm that merge the neighboring cluster which satisfying certain condition. Experimental results and analysis indicate that the combination to algorithms was effective, leads to minimum costs for network construction and make the best grade of service.
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