{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T08:24:50Z","timestamp":1758270290671},"reference-count":19,"publisher":"World Scientific Pub Co Pte Lt","issue":"01","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2019,1]]},"abstract":"<jats:p> The weakness of supervision and management measures in railway emergency rescue led to difficulties of whole of monitoring and disposal on the completion time and effect. In order to solve this problem, the GERTS stochastic network schedule is introduced to the process supervision of railway emergency rescue based on the analysis of process of railway emergency rescue. With critical procedures serving as the nodes and execution process as the edges of the network, the random network model is thus formed. In case of emergency, the simulation of GERTS random network can be used to predict necessary rescue time and disposal efficiency, with previous rescue time and effect for reference. The analysis of the case shows that the simulation obtained by this method is consistent with the practical situation of the rescue. Measure standards from this method can be acquired to evaluate the work schedule and efficiency, efficiently supervising the delay of different divisions during the rescue. The proposed measure improves the efficiency and handling capacity of railway emergency rescue, having certain theoretical guidance significance and application value on railway emergency rescue. <\/jats:p>","DOI":"10.1142\/s0218001419590031","type":"journal-article","created":{"date-parts":[[2018,6,26]],"date-time":"2018-06-26T02:36:31Z","timestamp":1529980591000},"page":"1959003","source":"Crossref","is-referenced-by-count":3,"title":["Research on the Process Supervision and Forecasting Model of Railway Emergency Based on GERTS"],"prefix":"10.1142","volume":"33","author":[{"given":"Jing","family":"Zuo","sequence":"first","affiliation":[{"name":"School of Automation &amp; Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, P. R. China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Min","family":"Lyv","sequence":"additional","affiliation":[{"name":"School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, P. R. 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