Using Improved BP Neural Network and Concept Lattice to Construction Smart Sensors System

Abstract

Smart sensor is information detection, information processing, information memory, logical thinking and judging function of sensor. It not only has the various functions of the traditional sensor, but also has the data processing, fault diagnosis, non linear processing, self correction and man-machine communication. BP (Back Propagation) neural network is a kind of error back propagation training algorithm for the multilayer feed forward network. As the central data structure in formal concept analysis, concept lattice can sign formal description the concept from the denotation and connotation to realize understanding semantic information by computer. This paper uses the implicit structure of three layers of BP neural network to build intelligent sensor network model is improved to complete the prediction of sensor information. The paper presents using improved BP neural network and concept lattice model to construction of smart sensors system. Experimental comparison shows that the method proposed in this paper is very effective to forecast information smart sensing.

Keywords

• Smart sensors
• Back Propagation neural network
• Concept lattice.