Alarm condition rehearsal system and rehearsal method based on BP neural network

Abstract

The invention discloses an alarm condition rehearsal system and rehearsal method based on a BP neural network. The system comprises an alarm condition simulation background server and a plurality of portable rehearsal terminals; the portable rehearsal terminal comprises a first microprocessor, a display, a GPS module and a second wireless transceiver module, and the alarm condition simulation background server comprises a second microprocessor, a script generation module, a first wireless transceiver module, an alarm event simulation module, an environment state simulation module and an instruction generation module; the first wireless transceiver module is in communication connection with a second wireless transceiver module; the script generation module, the alarm event simulation module, the environment state simulation module and the instruction generation module are electrically connected with the communication end of the second microprocessor. The invention can effectively simulate the complex and rapid change process of emergencies, and has the advantages of reducing the drilling cost, improving the drilling efficiency and the like.

Description

Technical field [0001] The invention relates to the field of police situation handling drills, in particular to a police situation rehearsal system and a rehearsal method based on a BP neural network. Background technique [0002] BP (Back Propagation) neural network was proposed by a team of scientists led by Rumelhart and McCelland in 1986. It is a multi-layer feedforward network trained by error back propagation algorithm and is currently one of the most widely used neural network models. The BP network can learn and store a large number of input-output pattern mapping relationships without revealing the mathematical equations describing this mapping relationship in advance. Its learning rule is to use the steepest descent method to continuously adjust the weights and thresholds of the network through backpropagation to minimize the sum of squared errors of the network. Reference figure 1 , BP neural network model topology structure includes input layer, hidden layer and outp...

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Problems solved by technology

[0005] In view of the above-mentioned deficiencies in the prior art, the purpose of the present invention is to: disclose a police situation rehearsal system and rehearsal method based on BP neural network, which solves the problem that it is difficult to truly simulate the rapid change process of emergencies and the rehearsal of mass emergencies. The problem of large space and many drill facilities can effectively simulate the complex and rapid change process of emergencies, and has the advantages of reducing drill costs and improving drill efficiency.

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