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98 results about "Category Code" patented technology

A coded value specifying a classification. [NCI]

Customs declaration commodity intelligent classification method based on historical data mining

The invention provides a customs declaration commodity intelligent classification method based on historical data mining. The method comprises the steps: analyzing the relation between a customs declaration commodity category code and the name, specification and model of a commodity, and describing a customs declaration commodity classification problem; preprocessing the historical information ofcustoms declaration commodities to remove useless parts of speech; designing an inverted index and a search algorithm for judging the first four codes of the commodity; performing feature selection onthe preprocessed commodities based on word frequency, and constructing a feature matrix based on a one-hot method; and based on the characteristics of different types of commodities, constructing a commodity classification model by adopting a decision tree algorithm; utilizing the classification model to classify customs declaration commodities, and obtaining a classification result, namely commodity codes. According to the invention, the category of the commodity can be well judged. The commodity can be effectively classified, and the commodity code based on the HS classification directory can be obtained. The method has high generalization performance. The customs clearance efficiency of enterprises can be improved. Trade risks caused by wrong classification of commodities are reduced.
Owner:BEIJING JIAOTONG UNIV

Automatic detecting and driving loading method of user mode network card in Linux system

InactiveCN103150190APowerful debugging abilityEliminate high overheadProgram loading/initiatingGNU/LinuxNetwork packet
The invention provides an automatic detecting and driving loading method of a user mode network card in a Linux system. In the Linux inner core initialization phase, a PCI (peripheral component interconnect) bus registers each drive and scans equipment mounted on the PCI bus; each drive respectively traverses the equipment mounted on the PCI bus, whether the drive is matched with the equipment or not is judged, if the drive is matched with the equipment, whether the category code of the equipment is matched with the category code of network card equipment or not is continuously judged, and if not, the equipment is initialized; and if the category code of the equipment is matched with the category code of the network card equipment, the equipment is distinguished as a network card, the information of the network card is stored, the initialization of the network card is given up, in addition, the user mode obtains the information of the network card, and the corresponding network card driving is loaded according to the information of the network card. The automatic detecting and driving loading method has the advantages that the automatic loading and the driving loading of the network card are respectively placed in the user mode, and high overhead on the system invoking and the data packet copy due to the inner core mode driving is eliminated.
Owner:OPZOON TECH

K mean value cluster-based optical fiber inertial measurement unit temperature model coefficient determination method

The invention discloses a K mean value cluster-based optical fiber inertial measurement unit temperature model coefficient determination method. According to optical fiber inertial measurement unit temperature model coefficient first-order subsection cases, if the number of segments is determined, 1, according to a straight line determined through adjacent temperature points, a slope is calculated, 2, through a K mean value clustering algorithm, the slope is classified and a category code is determined, 3, according to the category code and the number of the segments, all segment point compositions are acquired, and 4, through a fitting residual error, the optimal segment point is determined, and if the number of segments is not determined, according to a sequence of 1 to the largest probable number of the segments, the optimal segment point under the condition of each one of the numbers of the segments is calculated through the above steps 1-4 until the residual error satisfies the requirements. Finally, according to the optimal segment points, the optical fiber inertial measurement unit temperature model coefficient is fitted. The method utilizes the K mean value clustering algorithm to automatically search the optimal segment point, overcomes random errors and repeated processes of manual subsection and effectively improves product temperature model coefficient calculating efficiency and reliability.
Owner:BEIJING AEROSPACE TIMES OPTICAL ELECTRONICS TECH
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