33results about How to "Classification is flexible" patented technology

According to a middle-season rice information decision tree classification method based on multi-temporal data feature extraction of the invention, selected GF-1 image data has the advantages of high spatial resolution and high temporal resolution. On the basis, a variety of characteristic parameters for rice distribution extraction based on a single-temporal image are used, the advantages of timing analysis based on a multi-temporal image are utilized, multiple parameters and multiple temporal phases are combined organically, and the distribution of middle-season rice is extracted by means of knowledge decision tree classification. Through use of a variety of characteristic parameters, non-target surface features can be eliminated better. Multi-temporal analysis is conducive to the elimination of wrongly-classified surface features caused by 'different surface features, same spectrum' and the extraction of target surface features. Decision tree classification has the characteristics of being flexible, visual, efficient, and the like. Therefore, by integrating all the advantages, the precision of middle-season rice extraction is further improved. The method is of positive significance both to the food security system of a country and to the commercial application of remote sensing in agriculture.

The invention provides a goods sorting system based on RFID technology, which is mainly characterized in that a goods timing dispenser is arranged at one end of a conveyor belt of a conveying mechanism, and a plurality of goods taking-down devices are arranged under the conveyor belt; a system control center is connected with a programming port of a PLC controller of the conveyor belt of the conveying mechanism through an RS232 serial port and connected with a programming port of a PLC controller of the goods taking-down devices through the RS232 serial port, goods testing devices are fixed corresponding to both ends of the conveyor belt of the goods taking-down devices and a recycling bin at the end of the conveyor belt, and the signal wires of all goods testing devices are connected witha liquid crystal display having an alarming function; the whole system in the invention only needs one RFID identification system, and has low cost and simple structure; after information is set by aworker, the work needing to do is only to wait for a message sent from a recycling testing device and to change the recycling bin, and the working efficiency is improved; the invention is suitable for technical fields needing to sort goods, such as retail sales, warehouse management, library management and the like.

The present invention provides an abnormality detection optimization method oriented to power grid spatio-temporal data. The method comprises the following steps: (1) performing mesh division on a power distribution device according to spatial positions, then carrying out uniform division on power distribution power curves of acquisition devices in all meshes according to time, and defining a Gaussian distribution for power-distribution average power in each division; (2) establishing a null hypothesis and an alternative hypothesis; (3) estimating parameters, i.e. estimating values of testing parameters TP in the null hypothesis and the alternative hypothesis according to a maximum likelihood estimation method; (4) carrying out pruning optimization; (5) calculating a likelihood ratio of three-dimensional spacial data, wherein the higher the ratio is, the more obvious the abnormality of an area is; and (6) outputting first K abnormal areas by adopting a heap sort algorithm, and according to chi square distribution and in combination with a confidence level, acquiring an abnormality threshold. According to the abnormality detection optimization method provided by the present invention, power distribution network monitored data is classified so as to improve a fault detection technology aiming at a power distribution network and efficiently process interference of outside factors to power scheduling.

A 3 fiber line switched ring (3FLSR) provides protection for (optical) transmission networking wherein N nodes are connected via 3 lines (or optical fibers) in a ring topology. Two of the three fibers form a main transmission line and may transmit in one direction in the ring whereas the third might transmit in the opposite direction. This architecture of the 3FLSR provides a dual protection scheme, including a bi-directional line switching coupled with a unidirectional line switching. Traffic is categorized based on the level of protection available for the particular traffic type. The first two transmitting fibers form a bi-directional ring, carrying primary and secondary traffic which can survive 2 and 1 failures on the ring respectively. The third fiber may form a unidirectional ring, carrying additional traffic that can be pre-empted in case of multiple failures in the bi-directional ring. The 3FLSR enables reconfiguration of existing 2 / 4 fiber rings and conforms to applicable standards.

The invention discloses an allocation method and device of Internet protocol version 6 (IPv6) address prefixes. The allocation method comprises the following steps: carrying out CLASS-MAP classification on virtual private network (VPN) users belonging to the same CIP user access group or different CIP user access groups; and allocating the same IPv6 address prefixes to the VPN users of the same class. By adopting the CLASS-MAP mode, the invention allocates the V6 prefixes to the VPN users so that the allocation of the V6 prefixes can be independent of domains or CIP user access groups, thereby realizing the flexible allocation of the V6 prefixes.

The invention provides a rotary pencil holder facilitating the selection. The pencil holder comprises a supporting plate and an inner cylinder; the surface of the supporting plate is joggled with a supporting column; a first bearing is arranged at the bottom of the inner cylinder; the surface of the supporting column is connected with an inner ring of the first bearing in a sleeving mode, the surface of the supporting column is in threaded connection with a lifting plate, and the surface of the lifting plate is in joggle joint with a plurality of limiting rods; the inner wall of the inner cylinder is provided with a plurality of limiting grooves, the surfaces of the limiting rods are in sliding connection with the inner walls of the limiting grooves, and the surface of the lifting plate isin joggle joint with a supporting rod. The invention relates to the stationery field. When the pencil holder is in use, the pencils can be respectively taken out according to different lengths of the pencils, and the operation is simple, thereby avoiding the pollution and inconvenience. Meanwhile, the classification can be flexibly adjusted according to the length change of pencils, and therefore, the problem that pencils of different lengths are inconvenient to take out of a common pen container according to the length and the length change of the pencils in the using process is effectivelysolved.

According to the middle rice information decision tree classification method based on feature extraction in multi-temporal data in the present invention, the Gaofen-1 image data selected by it has the advantages of high spatial resolution and high temporal resolution. On this basis, the present invention It not only uses a variety of characteristic parameters used in the extraction of rice distribution from single-temporal images, but also combines the advantages of time-series analysis of multi-temporal images to organically combine multi-parameters and multi-temporal phases, and extract The distribution of middle rice. A variety of characteristic parameters can better eliminate non-target features. Multi-temporal analysis can help to eliminate misclassified features caused by foreign objects with the same spectrum, and can further extract target features. Decision tree classification is flexible, intuitive, and Features such as high efficiency. Therefore, combining these advantages can further improve the accuracy of mid-season rice extraction, which is of positive significance to both the national food security system and the commercial application of remote sensing in agriculture.

The invention provides a method for evaluating the health state of main power distribution equipment, which includes establishing an index layered space model that characterizes the state of main power distribution equipment; performing normalization processing on the indicators, assigning index weight values, and determining the objects to be evaluated Element; establish classical domain and node domain models and calculate the correlation value between indicators and equipment status. The technical solution provided by the present invention adopts the matter-element extension comprehensive evaluation method of the improved correlation function for information fusion, the evaluation system grade division is flexible, the evaluation result of a single index is more refined, the overall evaluation result of the equipment is accurate and specific, and the calculation process is simple and applicable. It is suitable for the status assessment of power distribution equipment with a large number of installations and a wide installation area.

The invention discloses a data packet classification method, which includes CPU preprocessing rule set and GPU execution data packet classification. run. Preprocessing operations are done on the CPU. The packet classification operation is the core part of the algorithm, which classifies the input data packets and outputs the rule number with the highest priority matched by the data packets. Packet classification operations are done on the GPU. The invention makes full use of the hardware characteristics and advantages of the GPU, and has greater performance advantages than conventional data packet classification algorithms.

The invention discloses a multifunctional toolbox for animal husbandry and veterinary use, which mainly comprises a bottom plate, a side plate, an upper cover, a bottom shell, a blocking rod, a fourth shell, a first shell, a second shell and a third shell. A bottom casing is fixedly installed in the middle of the top of the bottom plate, and the left and right symmetrical dry waste grooves and wet waste grooves are divided inside the bottom casing. The present invention is reasonably designed in structure, and the tool box adopts a layered flexible structure. After opening, the upper and lower shells are opened at the same time without blocking each other, and it is very convenient to pick and place tools of different layers; the structure distribution is reasonable, and the internal classification is convenient. , The waste is recycled and stored at the bottom, which is convenient for later cleaning, and it is not easy to cross infection with tools; when the device carries things for a long time, the structure is flexible, making it convenient to carry and take.

The invention provides a method and a system for extending garbage classification by an intelligent garbage can. The above-mentioned method and system for expanding garbage sorting by smart garbage cans detect whether the peripheral garbage can is connected through the main control chip; Prompt information to the user terminal; classify and configure the peripheral trash can through the user terminal; the main control chip generates a corresponding voice recognition control command to realize voice control of the opening and closing of the peripheral trash can, and the user It can flexibly expand the peripheral garbage cans without adding the main control chip, expand the number of similar garbage cans or flexibly add new garbage classifications to achieve personalized expansion effects and save expansion costs.

The invention provides a goods sorting system based on RFID technology, which is mainly characterized in that a goods timing dispenser is arranged at one end of a conveyor belt of a conveying mechanism, and a plurality of goods taking-down devices are arranged under the conveyor belt; a system control center is connected with a programming port of a PLC controller of the conveyor belt of the conveying mechanism through an RS232 serial port and connected with a programming port of a PLC controller of the goods taking-down devices through the RS232 serial port, goods testing devices are fixed corresponding to both ends of the conveyor belt of the goods taking-down devices and a recycling bin at the end of the conveyor belt, and the signal wires of all goods testing devices are connected with a liquid crystal display having an alarming function; the whole system in the invention only needs one RFID identification system, and has low cost and simple structure; after information is set by a worker, the work needing to do is only to wait for a message sent from a recycling testing device and to change the recycling bin, and the working efficiency is improved; the invention is suitable for technical fields needing to sort goods, such as retail sales, warehouse management, library management and the like.

The invention discloses a vehicle-mounted ad-hoc network intersection prediction routing method based on a CP (Counter Propagation) neural network, and mainly aims to solve the problems of frequent link fracture among nodes in a data packet forwarding section, large data packet transmission delay and low transmission success rate due to high-speed moving of vehicles, frequent change of network topology and a plurality of vehicle distribution densities in a traffic environment. According to the implementation scheme, a next section priority at which data packets are forwarded on an intersection is classified by use of the CP neural network; when a node arrives at the intersection, an average link communication probability of adjacent sections, average node densities of the adjacent sections and a distance ratio of a distance from a next intersection to a destination to a distance from the current intersection to the destination are taken as inputs of the CP neural network in one Hello message period; the priorities of adjacent data packet forwarding sections are taken as outputs; and a section with a highest priority is selected to be an optimal data packet forwarding section. Through adoption of the vehicle-mounted ad-hoc network intersection prediction routing method, the data packet forwarding success rate is increased, and the transmission delay of the data packets is shortened. The method can be applied to a vehicle-mounted ad-hoc network.

The invention discloses a method and device for classifying pictures. Wherein, the method includes: determining the classification basis of the target picture; extracting the picture features of the target picture from the target picture according to the determined classification basis, wherein the picture features include classification features of at least two dimensions belonging to the determined classification basis; The extracted image features classify the target image. The invention solves the technical problem that the classification results obtained by classifying the target pictures have large errors because the related technology adopts a fixed classification basis and a single classification feature is used to classify the target pictures during specific classification.

The invention relates to a soft component classification registration method based on field ontology, including the following steps: constructing a soft component attribute public ontology; establishing a field model of the specific field, and under the field model supporting, refining the soft component attribute public ontology, to obtain a specific field soft component attribute ontology; using the ontology tools to describe the specific field soft component attribute ontology, and output the ontology file in a standard format; constructing the specific field soft component registration unit model, and establishing the soft component database mapping unit model; constructing the specific field-oriented soft component registration model, and establishing the mapping relation between the specific field-oriented soft component registration model and other registration models; using open-source tools to analyze the ontology files, and generating the soft component registration template, and using the soft component registration template to process component registration. The soft component classification mechanism of the invention is flexible, easy to expand, and it can automatically achieve the generation of the registration template, and the soft component database constructed based on international standards (ISO / IEC 19763) has strong opening, universality and interoperability, and facilitate to the sharing and reuse of soft component resource.

A method for shape classification of an object is provided. Shape categories are provided which specify a plane and points therein relative to the object, and also specify at least one limit coordinate for each such point, the limit coordinate defining a boundary in a direction normal to the plane for the shape of the object considered in order for the object to be classified into a respective shape category. The shape categories can be provided by a user, making the method very flexible. The shape categories can in particular be derived from a set of samples of objects representing a shape category to be defined. For classification, the position of a surface of the object is measured at each of the points defined in the shape category, and the result is compared with the corresponding limit coordinate.