ANFIS (Adaptive Neural Fuzzy Inference System) indoor positioning method based on improved GA(Genetic Algorithm) optimization in WLAN (Wireless Local Area Network) environment

The invention discloses an ANFIS (Adaptive Neural Fuzzy Inference System) indoor positioning method based on improved GA(Genetic Algorithm) optimization in a WLAN (Wireless Local Area Network) environment, relating to an indoor positioning method in the fields of pattern recognition and artificial intelligence, particularly relating to a WLAN indoor ANFIS positioning method based on the improved GA optimization. The method solves the problems that the BP (Back Propagation) algorithm is slow in convergence rate and easy to trap into the local minimum and the genetic algorithm is premature and slow in evolution speed. The method comprises the steps of: 1, ensuring that anyone point in the environment is covered by signals emitted by two or more access points (AP); 2, building a corresponding relationship between actual coordinates of a reference point and the strength of the received signals of the AP; 3, building an ANFIS positioning sub-system in X direction and Y direction; 4, obtaining a network structure parameter by utilizing the improved ANFIS positioning sub-system; and 5, implementing the positioning of a test point. The ANFIS indoor positioning method based on the improved GA optimization in the WLAN environment is applied to indoor ANFIS positioning in the WLAN.