WSN connectivity maximization supplementary node optimization deployment method based on improved teaching and learning algorithm

The invention discloses a WSN connectivity maximization supplementary node optimization deployment method based on an improved teaching and learning algorithm. The method comprises the following steps: dividing a monitored three-dimensional area into 1 * w * h pixel points to form a point set Ra; according to the method, and deploying |S| sensor nodes in a network in total, thus satisfying the coverage and communication requirements of the network, wherein S is a total sensor node set and is a set of a preset sensor node set Sp and a supplementary sensor node set Sa, S = Sp + Sa. According to the method, the network connectivity is measured by adopting methods such as cut-point quantization and the like from the whole network, so that an adaptive value calculation process in the algorithm is formed. According to the method, in a teaching and learning algorithm, in consideration of score fluctuation caused by self-forgetting and autonomous learning of each member, a self-disturbance strategy is introduced to e