Jiayao Wang

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Spatial clustering is an important research topic in spatial data mining (SDM). Many methods have been proposed in the literature, but few of them have taken into account constraints that may be present in the data or constraints on the clustering. These constraints have significant influence on the results of the clustering process of large spatial data.(More)
Obstructed distance is an important research topic in Spatial Clustering with Obstacles now. The obstacles constraint is generally ignored in computing distance between two points, and it leads to the clustering result which is of no value, so obstructed distance has a great effect upon clustering result. The paper proposes an algorithm based on Ant Colony(More)
Evolutionary Location Intelligence on implementing a position based routing, that make forwarding decision based on the geographical position of a packet's destination is concentrated in this paper. One distinct advantage of this model is not necessary to maintain explicit routes. Position based routing does scale well even if the network is highly dynamic.(More)
Spatial clustering with obstacles constraints (SCOC) has been a new topic in spatial data mining (SDM). In this paper, we propose an advanced hybrid particle swarm optimization (HPSO) with GA mutation for SCOC. In the process of doing so, we first use HPSO to get obstructed distance, and then we developed a novel HPKSCOC based on HPSO and K-Medoids to(More)
Spatial clustering with obstacles constraints (SCOC) has been a new topic in spatial data mining (SDM).In this paper, we propose an advanced Particle swarm optimization (PSO) and differential evolution (DE) method for SCOC. In the process of doing so,we first developed a novel spatial obstructed distance using PSO-DV(particle swarm optimization with(More)
In order to provide intelligent and integrative Web Map Service applications for common users, this paper introduced agent-based methodology to realize flexible Web Map Services Aggregation on the Internet. According to the service aggregation procedure, we designed modules of agent-based user interface, service registry, service planning and service(More)
Spatial clustering is an important research topic in Spatial Data Mining (SDM). Although many methods have been proposed in the literature, very few have taken into account constraints that may be present in the data or constraints on the clustering. These constraints have significant influence on the results of the clustering process of large spatial data.(More)
This paper proposes a particle swarm optimization (PSO) method for solving Spatial Clustering with Obstacles Constraints (SCOC). In the process of doing so, we first use PSO to get obstructed distance, and then we developed the PSO K-Medoids SCOC (PKSCOC) to cluster spatial data with obstacles constraints. The experimental results show that PKSCOC performs(More)