Novel Learning Algorithm for System Model of Traditional Chinese Drug Fumigation

Abstract

Using control method to explain medical phenomenon is currently a hot subject of research. The traditional Chinese drug fumigation steaming treat protrusion of protrusion of protrusion of lumbar intervertebral disc with steam generated by boiling medicinal herbs, and this process is a typical non-linear, multivariable, and strong coupling. Experienced nurse and doctor cure patient by their experience. So establish a model of this process can discover more factor of the disease, better treat to protrusion of protrusion of protrusion of lumbar intervertebral disc and reduce of energy consumption. The novel learning algorithm which is combined Ying learning algorithm with fuzzy neural network is proposed in this paper of traditional Chinese drug fumigation fume to cure protrusion of protrusion of protrusion of lumbar intervertebral disc. Proper data pretreatment can improve the accuracy of model. The new way handle of date pretreatment and create a new local space by K-Vector Nearest Neighbors to remove extraneous matter from learning set. This method automatically adjusts fuzzy rules and networks weights based on local space to fit sampling data. The identification model can reveals pathological mechanism of protrusion of protrusion of protrusion of lumbar intervertebral disc. The controller can adjust heater output power based on this model at the state of energy conservation. The simulation results show that the identification model is true and result is feasible. Compared with other methods, the new controller has better dynamics performance and anti-interference capability.