Study On The Knowledge Reasoning Of Urban Rail System Operation Risk Based On Accident Analysis

Safety is the prerequisite and core competitiveness of the urban rail transit operation.With the deepening of high-density and strong coupling network of the urban rail transit,the operation safety problems have aroused great attention from all walks of life.The state and industry have issued a series of policies and management methods to standardize the operation risk management of the urban rail transit so as to the research about system risk management and control has become a hot topic problem.However,the work on system risk management and control are mostly based on empirical analysis of accident causes after the occurrence of which at present.This "passive safety" mode can’t meet the risk management and control needs of the urban rail transit operation status any more.Scientific prediction of the potential accident risk and taking corresponding measures can effectively reduce the frequency of accidents,so as to realize the "active safety" purpose of system operation safety.In view of this practical background,this paper proposes a method of the risk knowledge extraction based on the text research of urban rail operation accidents and combined with the ontology theory to complete the structured storage of the risk knowledge.Using Bayesian theory to complete the reasoning research on uncertain risk knowledge at last.The main research contents are as follows:(1)Constructed a systematic lexicon which is to represent the characteristics of urban rail transit operation accidentsBased on the deeply investigation inside the urban rail transit system,this paper summarizes the current situation about the safety accidents management and control in the actual operation process.And also analyzes the statistical characteristics,text characteristics and the causes of the urban rail transit system operation accidents.Based on these researches,we establish a systematic lexicon which considers the causative factors from the person,the machine,the environment and the management in four aspects.Meanwhile according to the different proportion of the accident data,the systematic lexicon is divided into personnel sub lexicon,physical component sub lexicon,environment sub lexicon and safety management sub lexicon with setting different weights.The division of sub lexicon can pave the way for the effective extraction of risk knowledge in the next step.(2)Formed the method of extracting operational risk knowledge of the urban rail transitCombined with the reality of unstructured storage about operation accident texts,the Chinese text segmentation technology is used to complete the word segmentation of the text firstly.And also using the hidden Markov and Viterbi algorithm to complete segmentation optimization.In order to further clarify the mechanism of operation accidents,the concept words of the risk are extracted with considering comprehensive weights by using the constructed professional lexicon and TF-IDF algorithm.To clarify the mechanism of the operation accidents furtherly,the confidence degree and improved K-means algorithm are used to develop the top-level risk concept words based on the risk concept words so as to complete the extraction of hierarchical and non-hierarchical relations among concepts.(3)Constructed an ontology model of urban rail transit operation riskAfter extracting the effective risk concepts and the connection relationship between the concepts from the urban rail transit operation accidents,the ontology concept model is introduced for the storage of risk knowledge,and a semi-structured urban rail operation risk ontology construction method is proposed.After clarifying the hierarchical and non-hierarchical relationship between the risk concepts and the description of the related attributes of the risk concepts,the construction of the urban rail transit operation risk ontology model is realized,and the editing software is used to complete the visual display of the risk ontology model.On this basis,the logical relationship existing in the risk knowledge is checked and evaluated,redundancy and wrong connection are eliminated,and the directed ring connection is avoided,which lays the foundation for the subsequent determination of the directed acyclic structure based on Bayesian inference.(4)Formed an uncertain risk knowledge reasoning method based on improved Bayesian structureThe constructed urban rail transit operation risk ontology model can realize the effective storage of deterministic risk knowledge,but there is still uncertain risk knowledge in the actual operation process.Combined with the assessed risk ontology structure,the probability extension is carried out to complete the determination of the Bayesian inference structure in this paper.The maximum likelihood estimation algorithm is also used to quantitatively analyze the relationship between the risk concept nodes,and infer the probability of related accidents in the case of uncertain risks.Under the results,we put forward the standardized accident text management ways to cater to the active safety requirements of urban rail transit operations,so as to more accurately extract risk knowledge from accidents.(5)An urban rail transit system operation risk management and control platform is developedBased on the above research,the paper develops an urban rail transit system operation risk management and control platform which is for active safety requirements.And demonstrate the logical architecture,main functions and core interfaces of the system.