Research The Data Mining System In Services Architecture For Forest Resource Survey

Forest resource survey plays an important role in forest aspect. As digital forestry widely applicated, the accumulation of fundation data on forest survey increases quickly. Therefore, how to distill valuable information from the mass data become the main issue of forest data mining. Besides, under the impact of global developing strategic of Internet, the application integration based WEB Service has been a major trend in information system. This paper studies the design and development in forest investigate data mining system based on WEB Service.Firstly,the paper summarized the recent actuality on data mining application in forest resource survey, and drew out characteristics and scene requirement for different algorithms employed in the field of forest resource survey. After analyzing the data mining models and characteristics based on WEB Service, data mining WEB Service were developed with.Net Framework in different models, which includes an attributes relation analyzing running in the local server and an improved Aprior algorithm for searching the frequent item sets from route datasets. Besides, this development primarily studied on system designment on aspects of accessing to a large data source, occupying the network resources, process scalability and etc.. In the third part, to examine the each WEB Services architecture with study area data is the main work. A decision-tree system was constructed based on subcompartment inventory data which directed toward JiuQu Forestry that is located in FuJian province. After defining the quality of characteristic data set, Threshold value was decided in the process of attribute reduction, with this reserach, a distributed system was designed by using the.Net framework and WSBPEL. For issuses of how to reduce the data fragmentation and sub-tree repeat on training the decision-tree, the paper presented a method of constructing characteristic data set based on fractal dimension, and analysed the influence of using fractal dimension and information gain to droping the redundancy attributes, as well as information loss of characteristic data set to constructing the decision-tree. In this part, the paper summarized the characteristics of this two kinds of decision-tree by the experimental results.As a vital data source for large area researching, remote sensing data plays a more and more important role in forest resource survey. In the next part of the paper, the model of data mining in the WEB Services architecture and integrating by work flow was investigated. On this foundation, a remote sensing image data mining basing on the value of feature texture system was designed by the.Net framework and WSBPELIn the next chapter, extracting the feature from image basing on frequent itemsets is proposed, this method first selects out the candidate frequent itemsets founding on the degree of frequency and the locality distributing, then constructs the feature set by defining the value of spatial control for every frequent itemset. The simulation is done with remote sensor image, because of the EM clustering algorithm maybe be dominated by its initializing, the experimentation is designed with specifying the different number of clusters for every feature set and determines by the log likelihood. Experiment results show that frequent feature set can provide satisfactory expression for distinguzing the forestr proportion in image.Since Tri-training applied in semi-supervised learning can improve the classification precision, and how to construct two redundance data sets is the key for Tri-training, the system running in WEB Services named CTSVMTRS was worked out in the research, with analysing on SVM algorithm and texture property of remote sensing image, which is for Tri-training SVMS in remote sensing image based on two data sets that one is from pixel value and another from calculating texture property is presented.This paper mainly analyses how to design a data mining system based on WEB Services directed toward common forest resource survey affair data and remote sensing data. After designing some classical data mining algorithms in this system, the key technic and algorithm ameliorating strategy were researched in the concrete implementing process. By analysing the related designments, two tests were carried out for ensuring the design's effective, one is for WEB service architecture and another is for improving of algorithms and appling to the forest resources survey, the result of experiment not only proves that these methods are effective, but also shows this research has reference value in the aspect of forest information system integration to a certain extent.