BP neural network WSN forest fire prevention system based on ant colony optimization

A BP neural network and forest fire technology, applied in the field of wireless sensor networks, can solve the problems of scattered data collection, time-consuming and labor-intensive, and inaccurate, and achieve high prediction accuracy, improved convergence speed, and high accuracy

Inactive Publication Date: 2017-07-07
YANGZHOU UNIV
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Problems solved by technology

[0006] The purpose of the present invention is to propose a BP neural network WSN forest fire prevention system based on ant colony optimization, which overcomes the shortcomings of time-consuming, laborious, high cost, scattered data collection, and inaccurateness in traditional forest fire monitoring, and can effectively and accurately predict The scale of the fire prompted the relevant departments to take preventive measures in advance

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  • BP neural network WSN forest fire prevention system based on ant colony optimization
  • BP neural network WSN forest fire prevention system based on ant colony optimization
  • BP neural network WSN forest fire prevention system based on ant colony optimization

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Embodiment Construction

[0019] It is easy to understand that, according to the technical scheme of the present invention, under the situation of not changing the essential spirit of the present invention, those skilled in the art can imagine the various implementations of the BP neural network WSN forest fire prevention system based on ant colony optimization of the present invention Way. Therefore, the following specific embodiments and drawings are only exemplary descriptions of the technical solution of the present invention, and should not be regarded as the entirety of the present invention or as a limitation or limitation on the technical solution of the present invention.

[0020] The core of the BP neural network WSN forest fire prevention system based on ant colony optimization in the present invention is to include a wireless sensor network and a forest fire prediction model. Specifically, the forest area uses sensors to collect the data of environmental factors that affect the occurrence o...

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Abstract

The invention provides a BP neural network WSN forest fire prevention system based on ant colony optimization, which comprises a wireless sensor network and a forest fire prediction model, wherein the wireless sensor network is used for acquiring environmental impact factor data in the forest and providing the acquired data for the forest fire prediction model; the forest fire prediction model judges the fire happening possibility according to the environmental impact factor data; the wireless sensor network is formed by a plurality of wireless sensors deployed in the forest in a ZigBee wireless networking mode; all wireless sensors transmit the acquired environmental impact factor data to a network coordination node, the network coordination node forwards the acquired data to a monitoring host in a monitoring center through wireless remote data transmission network GPRS, and the forest fire prediction model is arranged on the monitoring host. The fire scale can be predicted effectively and accurately.

Description

technical field [0001] The invention belongs to the technical field of wireless sensor networks, in particular to a BP neural network WSN forest fire prevention system based on ant colony optimization. Background technique [0002] Wireless sensor network (WSN) is composed of a large number of randomly distributed tiny sensor nodes integrated with sensor data processing units and communication modules. The sensor nodes form a network through self-organization. In the restricted distribution system, the surrounding environmental parameters where the sensor nodes are located, such as temperature, humidity, PH value, noise, light intensity, pressure, soil composition, size, speed and direction of moving objects, etc., collect data through the network, and in the between networks and through upper-layer networks. The communication and networking methods of the network adopt multi-hop and peer-to-peer methods, and the network topology is similar to that of the wireless Ad hoc ne...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06N3/00G06N3/06H04L29/08H04W84/18
Inventor 王进曹溢泉曹佳溢周峰李斌
Owner YANGZHOU UNIV
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