本文選題：虛開增值稅發(fā)票行為 + 有向圖��； 參考：《西安科技大學(xué)》2017年碩士論文

【摘要】：在偵破虛開增值稅發(fā)票案件的實踐中,從資金交易流中找到資金環(huán)路是檢測虛開增值稅發(fā)票行為的關(guān)鍵環(huán)節(jié)。資金交易流可以抽象成由頂點和邊組成的有向圖,因此研究基于有向圖的虛開增值稅發(fā)票行為檢測方法是非常必要的。本文首先研究了虛開增值稅發(fā)票行為中的增值稅發(fā)票環(huán)路虛開行為表象與檢測方法,將從資金交易流中搜索資金環(huán)路問題抽象成對具有多重邊的有向圖環(huán)路搜索問題,其次研究了有向圖的存儲以及圖的環(huán)路搜索常用算法,并對算法的適用性進行比較,發(fā)現(xiàn)常用的環(huán)路搜索算法均不能很好地解決具有多重邊的有向圖環(huán)路搜索問題,因此,提出了基于深度優(yōu)先的有向圖環(huán)路搜索算法。先對原始數(shù)據(jù)預(yù)處理,將資金交易流和賬戶信息使用賬號編號關(guān)聯(lián)起來,找出每個頂點的邊集合并按交易時間升序排列,避免在運算過程中多次遍歷所有邊,通過約束邊的權(quán)值來避免遍歷無效邊,搜索過程采用逐層退回的方式來保證能遍歷到有效的多重邊且能找到有向圖中的所有環(huán)路,并在單機上驗證了算法的正確性。但是當(dāng)有向圖的邊數(shù)增大到100萬條以上時,算法執(zhí)行會發(fā)生內(nèi)存溢出,從而無法得到結(jié)果。針對該問題又提出了一種基于Spark的有向圖環(huán)路搜索算法,先將原始數(shù)據(jù)抽象成Spark中GraphX圖數(shù)據(jù)結(jié)構(gòu),然后利用數(shù)據(jù)緩存、尾遞歸等方法并使用GraphX框架及Scala語言在本地模式下驗證了算法的正確性,但是在相同的數(shù)據(jù)集下該算法時間效率明顯低于最初提出的算法。為了提高該算法的執(zhí)行效率,通過優(yōu)化循環(huán)、建立索引等方法對其進行優(yōu)化,在本地模式下驗證后,使用邊數(shù)為10000條以上的圖數(shù)據(jù)集在Spark集群下實驗,結(jié)果表明,優(yōu)化后的算法不僅能夠解決具有多重邊的大規(guī)模有向圖環(huán)路搜索問題,具有良好的擴展性,而且執(zhí)行效率得到明顯提高。最后,本文設(shè)計并實現(xiàn)了界面友好且可操作性強的虛開增值稅發(fā)票行為檢測系統(tǒng)。經(jīng)測試,該系統(tǒng)能夠從資金交易流中搜索出資金環(huán)路并能夠查詢出環(huán)路關(guān)聯(lián)賬戶的詳細(xì)信息,為稽查部門檢測虛開增值稅發(fā)票行為提供了重要的依據(jù),節(jié)約了稽查成本。
[Abstract]:In the practice of solving the case of false VAT invoice, it is the key link to detect the false VAT invoice behavior to find the capital loop from the fund transaction flow. The flow of funds can be abstracted into a directed graph composed of vertex and edge, so it is necessary to study the method of detecting the behavior of false VAT invoice based on digraph. In this paper, we first study the behavior representation and detection method of Value-added tax (VAT) invoice Loop in the behavior of false VAT invoicing, and abstract the problem of searching the Loop of Capital from the flow of funds into a pair of directed Graph Loop search problem with multiple edges. Secondly, the storage of directed graph and the loop search algorithm of graph are studied, and the applicability of the algorithm is compared. It is found that the commonly used loop search algorithm can not solve the loop search problem of directed graph with multiple edges. An algorithm for searching the loop of directed graph based on depth first is proposed. First of all, preprocess the raw data, associate the fund flow and account information with account number, find out the edge set of each vertex and arrange it in ascending order according to the transaction time, avoid traversing all sides many times in the course of operation. The weights of the constrained edges are used to avoid traversing the invalid edges. The search process adopts the method of layer by layer regression to ensure that all loops in the directed graph can be traversed effectively and all the loops in the directed graph can be found, and the correctness of the algorithm is verified on a single machine. However, when the number of edges of directed graph increases to more than 1 million, memory overflow will occur in the execution of the algorithm, so the result can not be obtained. In order to solve this problem, a new algorithm of directed graph loop search based on Spark is proposed. The original data is abstracted into GraphX graph data structure in Spark, and then the data cache is used. The algorithm is proved to be correct in local mode by using GraphX framework and Scala language, but the time efficiency of the algorithm is obviously lower than that of the original algorithm under the same data set. In order to improve the efficiency of the algorithm, the algorithm is optimized by optimizing the loop and building the index. After being verified in the local mode, the experiment is carried out in Spark cluster by using the graph data set with more than 10000 edges. The optimized algorithm can not only solve the large scale directed graph loop search problem with multiple edges, but also improve the efficiency of execution. Finally, this paper designs and implements a friendly and operable VAT invoice detection system. The test shows that the system can search out the capital loop from the fund transaction flow and inquire the detailed information of the related account of the loop, which provides an important basis for the audit department to detect the false issuance of VAT invoices and saves the cost of audit.
【學(xué)位授予單位】：西安科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：F812.42;O157.5

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