Message optimization method based on wireless sensor network for coal mine face positioning
A technology for positioning wireless and sensor networks, which is applied in the field of message optimization based on coal mine positioning wireless sensor networks, and can solve the problem of not being able to take into account network effectiveness and reliability at the same time
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Embodiment 1
[0078] A specific embodiment of the present invention discloses a message optimization method based on a coal mine face positioning wireless sensor network, such as figure 1 shown, including the following steps:
[0079] S1. Initialize the message population to be transmitted based on the coal mine face positioning wireless sensor network, so that each message is sequentially arranged on the current channel;
[0080] S2. Identify the size and damage degree of each message on the current channel, and arrange all the messages in order according to their size and damage degree;
[0081] S3. For messages with a similar degree of damage and close priorities, perform local order adjustment through a multi-level iterative greedy algorithm until the algorithm converges, and end the local order adjustment;
[0082] S4. Identify whether the above-mentioned adjusted message population is unstable or out of order. If it exists, perform local order adjustment on the unstable or out of ord...
Embodiment 2
[0085] Optimizing on the basis of Embodiment 1, in step S1, the initialization processing of the message population to be transmitted based on the coal mine face positioning wireless sensor network further includes the following steps:
[0086] S11. Obtain the transmission constraints of the message on the channel;
[0087] S12. Obtain the transmission time of each message on each channel according to the transmission constraint;
[0088] S13. By minimizing the maximum transmission time and complying with the message propagation blocking relationship, optimizing the order of the messages in the message population, and realizing the initialization processing of the message population.
[0089] Preferably, in the above step S11, the constraints include: 1) each channel can only send one message at a certain moment; 2) the message can only be transmitted before the next channel is released after the message is transmitted on the current channel is blocked on the current channel....
Embodiment 3
[0136] In order to demonstrate the technical effects of the present invention more clearly, an example is given below for detailed description.
[0137] Select the data of different scales in the public data set Taillard as the initial message population, and then use the method (algorithm) described in Embodiment 2 of the present invention, cultural gene algorithm, and differential evolution artificial bee colony algorithm to process in sequence.
[0138] figure 2 The arrangement of the initial message populations on the two channels X and Y of the method described in Embodiment 2 of the present invention is given, and after being processed by the method described in Embodiment 2 of the present invention, the messages in a stable and orderly arrangement are obtained populations, such as image 3 shown.
[0139] Set the key parameters: particle swarm size is 100, the number of iterations of the multi-level iterative greedy algorithm is set to G=2000 when the number of chann...
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