Mining of Sequential Patterns using Directed Graphs

Sequential pattern mining is one of the important functionalities of data mining. It is used for analyzing sequential database and discovers sequential patterns. It is focused for extracting interesting subsequences from a set of sequences. Various factors such as rate of occurrence, length, and profit are used to define the interestingness of subsequence derived from the sequence database. Sequential pattern mining has abundant real-life applications since sequential data is logically programmed as sequences of cipher in many fields such as bioinformatics, e-learning, market basket analysis, texts, and webpage click-stream analysis. A large diversity of competent algorithms such as Prefixspan, GSP and Freespan have been proposed during the past few years. In this paper we propose a data model for organizing the sequential database, which consists of a directed graph DGS (cycles and several edges are allowed) and an organization of directed paths in DGS to represent a sequential data for discovering sequential pattern3 from a sequence database. Competent algorithms for constructing the digraph model (DGS) for extracting all sequential patterns and mining association rules are proposed. A number of theoretical parameters of digraph model are also introduced, which lead to more understanding of the problem.

Failure Evaluation and Analysis of Mechatronics-Based Production Systems during Design Stage Using Structural Modeling

A method based on structural modelling is developed for failure evaluation and analysis of mechatronics-based production systems. Majority of the elements in production systems are mechatronics-based, which includes various elements such as; electrical, electronic and mechanical. Each of these may have different failure types that may be interdependence/interactive. The reliability of the system mainly depends on how well the failures are taken care of during design stage. In general, individual failures are generalized into probable failure modes and early identification of these helps to reduce their probability. However, consideration of failures and their interdependence / interactions will help to evaluate and analyse the failures of complicated systems in an efficient and effective manner and increase the inherent system reliability. The system structure modeling helps in this regard. Digraph model, in conjunction with matrix method, is employed for failure evaluation and analysis of a mechatronics-based production system based on its structure.

Missile Assault to Surface Signed Digraph Model of Aviation Based on Information Support

By analyzing the space-based information support and basic process of aviation in missile assault to surface under the C4ISR system, the parameters for the operation model are set and aviation in missile assault to surface war model under space-based information support is proposed by using signed digraph method. Finally, this paper analyzes this signed digraph model by using the qualitative theory of nonlinear differential equation, which effectively shows the information support function of space-based information in aviation in missile assault to surface.

Study on Intelligence Fault Diagnosis Approach Based on Digraph Model and Application to Satellite Battery

This article presents a SSDG---based intelligent fault diagnosis method. This method uses five signed threshold value modes to define nodes for carrying quantified information. This method establishes the SDGs of the system and its components, uses the based on rules method to diagnosis, then expands the diagnosing rule bank with logical operators to construct the diagnosing rule bank of the system. Applying in satellite battery system, this method can diagnosis the multiple fault, and batter explain, reworked and faster diagnosis.

Precise signed digraph modelling based on causal dependence identification

The fault diagnosis approach based on signed digraph is promising, but signed digraph models built by existing methods often contain false causalities and make spurious diagnosis results. In this article, a signed digraph modelling method based on causal dependence identification is proposed. Many equations used to describe mechanism of process system can be used to analyse the cause–effect relation between state variables and build precise signed digraph models. The cause–effect relation hided in system equations is extracted through causal dependence identification of algebraic and differential equations. Signed digraph model is then constructed by merging the analysis results. The method of causal dependence identification and strongly connected components identification of process system is investigated in detail. Algorithm of causal dependence identification is summarized and results in a simple but effective signed digraph construction procedure. The validity of the proposed method was tested by the case study of signed digraph modelling for a series connected liquid storage system, and the efficiency of the algorithm was tested by another case study of a compressor unit system. The comparison result shows that the proposed method can extract precise causal dependence relation between state variables from system equations and build signed digraph model effectively with less resource consumption, which is very important for building signed digraph model of large scale process system.