Sensor dynamic modelling based on NGO-LSSVM

Dynamic modeling of sensors is an important means to study their dynamic characteristics, laws of motion, and performance indicators. Aiming at the problem of high nonlinearity in sensor dynamic modeling, which makes it difficult to establish an accurate dynamic model, a sensor dynamic modeling method is proposed. The ideal parameters for the sensor dynamic model are chosen using the Northern Goshawk Optimization Algorithm, which is based on the regression prediction analysis method of the least squares support vector machine. Simulation shows that the NGO-LSSVM model is an economical, high-precision, and reliable sensor dynamic modeling tool.