Multilayer BP neural network is a one-way transmission of feed forward network and it has three or more than three layers of neural network, including input layer, hidden layer and output layer. Wireless sensor network is composed in certain region has a plurality of wireless communication, sensing, data processing capabilities of network nodes. The paper presents design and development of detection node in wireless sensor network based on neural network. The simulation results prove the validity of the adopted BP neural network to build wireless sensor network node.

Wireless sensor networks with node calculation ability is weak, node power (battery provides) Limited, routing algorithm of wireless sensor networks should be the energy saving and simple algorithm. Ant colony algorithm shows good search results in the discrete solution space. This paper improves the ant colony optimization algorithm. The paper presents analysis of routing protocols for wireless sensor networks based on improved ant colony optimization algorithm, and the simulation results verify the effectiveness of the improved algorithm.

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A two-dimensional electromechanical analysis is performed on a transversely isotropic piezoelectric material containing a crack based on the impermeable electric boundary condition. By introducing stress function, a general solution is provided in terms of triangle series. It is shown that the stress and electric displacement are all of 1/2 order singularity in front of the crack tip. In addition, the electromechanical fields in the vicinity of the crack when subjected to uniform tensile mechanical load are obtained using boundary collocation method.

Particle swarm optimization objective is spatial neighborhood directly in the search space according to the distance between particles. This paper analyses method of detection and node management in wireless sensor networks. Sensor nodes are randomly placed in the particle swarm optimization method, data acquisition, processing and transmission of the work. The paper presents using particle swarm optimization algorithm to construction detection and node management system in wireless sensor network. Simulation experiments show the validity of this method.