40results about How to "Little fluctuation" patented technology

The embodiment of the invention provides a carpooling discount determination method and apparatus, and relates to the technical field of traffic. According to the embodiment of the invention, an estimated carpooling success rate is determined according to the carpooling feature of a current order; and then, an expected value of a discount is determined according to the estimated carpooling successrate, a preset first discount value corresponding to carpooling success and a preset second discount value corresponding to carpooling failure to serve as the discount value of the current order. Byadoption of the technical scheme, a relatively stable and accurate discount value with little fluctuation can be automatically given without manual configuration, thereby saving labor, and when the estimated carpooling success rate has a certain deviation, the finally determine discount value is not greatly fluctuated, thereby achieving a win-win situation of passengers, drivers and the platform.

The invention relates to the field of pattern recognition, in particular to a pattern recognition method based on a self-adaptation correction neural network. The method comprises the steps of classifying input training samples through a probabilistic neural network model so as to obtain samples accurate in classification and samples inaccurate in classification; adding an input layer, a central layer and an excitation layer on the basis of the probabilistic neural network model structure so as to construct a self-adaptation correction neural network model structure; for the samples inaccurate in classification in the probabilistic neural network model, using themself as central points, calculating the allowance radius between the the samples and samples of other classifications, clustering error samples of same category so as to realize batch correction of classification patterns and replanning of a judging interface and build the self-adaptation correction neural network; finally, conducting pattern recognition on input testing samples based on the self-adaptation correction neural network model. The pattern recognition method has the advantages of being high in accuracy in mode classification, strong in mode generalization ability, good in classification real-time performance, wide in application prospect, and the like.

The invention relates to a self-adhesive reactive ethylene-octene copolymer composite waterproof coiled material and a production method thereof. The self-adhesive reactive ethylene-octene copolymer composite waterproof coiled material is formed by superimposing and compounding a base layer, a surface layer and an anti-adhesive isolating layer, wherein the base layer is an ethylene-octene copolymer waterproof layer, the surface layer is a self-adhesive reactive butyl rubber layer, and the isolating layer is a PE (polyethylene) anti-adhesive isolating film; on the basis of 100 parts of ethylene-octene copolymer, the base layer comprises 50-110 parts of carbon black, 30-70 parts of superfine talc powder, 5-10 parts of calcium carbonate, 20-60 parts of a plasticizer, 2-10 parts of polyethylene glycol, 1-6 parts of dicumyl peroxide, 0.5-2.75 parts of a crosslinking agent and 1-3 parts of an anti-aging agent; and the surface layer comprises the main raw materials namely butyl rubber, polyisobutylene, amorphous alpha-olefin copolymer and viscosity increasing resin, and the surface layer comprises auxiliary materials namely desulfurization gypsum, bentonite, calcium stearate, lithium chloride, calcium chloride, a swelling agent and a crosslinking agent. The invention can realize molecular chain complete crosslinking of the ethylene-octene copolymer waterproof coiled material to improve the thermal stability of the material and can achieve the aim of self-repairing by stopping water with water.