Scheduling parameter weight training model construction method and work area scheduling method
A technology for scheduling parameters and training models, applied in neural learning methods, biological neural network models, data processing applications, etc., can solve problems such as lack of experience in security dispatchers, inability to issue emergency command and dispatch orders, etc., to avoid poor dispatching effect, High degree of automation and high efficiency
Pending Publication Date: 2022-01-21
SHUOHUANG RAILWAY DEV
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[0004] However, the inventor found during the implementation process that in the traditional railway emergency command process, the most efficient emergency command and dispatch order may not be issued due to the lack of experience of the safety dispatcher
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[0046] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application, and are not intended to limit the present application.
[0047] The scheduling parameter weight training model construction method provided by this application can be applied to such as figure 1 shown in the application environment. Wherein, the terminal 102 communicates with the server 104 through the network. The user can send the sample data set to the server 104 through the mobile terminal 102 . The server 104 trains the preset neural network model according to the sample data set, and uses the trained neural network model as the scheduling parameter weight training model. Wherein, the terminal 102 can be, but not limited...
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The invention designs a scheduling parameter weight training model construction method and a work area scheduling method. The work area scheduling method comprises the following steps: obtaining scheduling parameters of each work area to be participated in rescue and weight parameters in a scheduling parameter weight training model; inputting the scheduling parameters and the weight parameters into a rescue scoring model; and outputting a result by the rescue scoring model, and determining a work area participating in emergency event rescue, wherein the scheduling parameter training model is constructed through a scheduling parameter training model construction method. In the construction method, a preset neural network model is trained by obtaining a sample data set, so that construction of the scheduling parameter weight training model is completed. Rescue work area confirmation is performed on the basis of each scheduling parameter weight capable of representing the influence degree of each scheduling parameter on whether each work area participates in rescue in the trained model, the problem of wrong and slow scheduling decision caused by insufficient personal experience can be avoided, and the method does not need to depend on manpower and is high in efficiency and reliability.
Description
technical field [0001] The present application relates to the technical field of railway emergency command, in particular to a method for constructing a dispatch parameter weight training model and a work area dispatch method. Background technique [0002] With the rapid development of railway transportation, railway emergencies occur from time to time. For railway emergencies, it is necessary to carry out rescue through reasonable dispatching of resources in various railway work areas. [0003] The realization of traditional railway emergency command work area dispatching still mainly relies on the safety dispatcher. The safety dispatcher will issue emergency command and dispatch orders based on factors such as distance, personnel, and materials combined with his own experience. [0004] However, the inventor found during the implementation process that in the traditional railway emergency command process, the most efficient emergency command and dispatch order may not be...
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Login to View More IPC IPC(8): G06F30/27G06Q10/04G06Q10/06G06Q50/30G06N3/08
CPCG06F30/27G06Q10/04G06Q10/0631G06Q10/06393G06N3/084G06Q50/40
Inventor 代斌李德方宋丽莉于国旺张志国李洪人王玉麟韩君龙
Owner SHUOHUANG RAILWAY DEV