43results about How to "Realize multi-objective optimization" patented technology

The invention relates to a method for carrying out face three-dimensional reconstruction at any viewing angle on the basis of a self-adaptive deformable model. The method includes the steps of (1) obtaining face image data and screening a face image with high definition as original data, (2) positioning feature points, (3) coarsely estimating the angle of a face according to the positioning result of the feature points, (4) building a face three-dimensional deformable model, adjusting the feature points of the face to be at the same dimension as the face three-dimensional deformable model through translation and scaling and extracting coordinate information of the points corresponding to the feature points of the face to form a sparse face three-dimensional deformable model, (5) iterating face three-dimensional reconstruction by means of the particle swarm optimization algorithm according to the coarsely estimation value of the angle of the face and the sparse face three-dimensional deformable model to obtain a face three-dimensional geometric model, (6)mapping input face texture information in a two-dimensional image to the face three-dimensional geometric model in a texture pasting method after the face three-dimensional geometric model is obtained, so that a complete face three-dimensional model is obtained. The method can be widely used in the field of identity identification.

The invention relates to an adaptive vehicle following algorithm based on improved model prediction control. The algorithm comprises the steps that 1, a vehicle following model is established, whereina controller of an adaptive cruise control system is divided into an upper-layer controller and a lower-layer controller for control, the upper-layer controller calculates expected acceleration according to received information of a relative distance and a relative velocity and transmits the acceleration to the lower-layer controller, and the lower-layer controller controls throttle opening and brake pressure according to a vehicle inverse longitudinal dynamic model through the acceleration; and 2, an algorithm based on model prediction control is established, wherein an estimator is constructed, a least square method is adopted to fit out a most approximate straight line by use of values of previous moments, values of future moments are estimated, and finally a model prediction algorithmis utilized to calculate optimal expected acceleration. Under an existing model prediction framework, front vehicle acceleration information is collected, the least square method is utilized to fit out the front vehicle acceleration change law, prediction is made, a disturbed value of acceleration is provided for model prediction control, and therefore the effect of improving an optimal solutionis achieved.