An Forecasting Model For Coal And Gas Gushing Based On Self-learning SVM

The aim of the subject is to provide safety alarm system for coal enterprise in order to improve our country coal safty produce ability.making use of the new Technology-SVM and data from monitor-Control system.On the base of SVM arithmetic , The author introduce the GA and use it to Choose Character, and deal with all kinds of Data from Sensors by Amalgamation, and distinguish danger zone from normal zone by SVM, and regard change coefficient as critical flag, all of these is to improve veracity of forecasting,at last offer the design of Uml under Rup;Due to the aim of the subject is to apply ,so the author provide detailed theoretics and material resolvent in data collection, data pretreatment, Character Choose, Data Amalgamation, SVM-sorting , change coefficient as critical flag,Soft design truss under Rup.The article discuss summary firstly,theory secondly, practice at last. The author sum up the content has been discussed and integrate it into the application in chapter 8. and only offer some main maps of uml,because of too big truss.The idea of design is aim at practice, all of data used to test is from KJ110 gas detection-control system of xi'an xike detection-control co,Ld ,so the arithmetic idea to do with questions is generic and could be used in other malfunction diagnosis system.