30results about How to "Realize optimal selection" patented technology

The present disclosure provides a method and a system for controlling the midpoint balance of a three-level inverter under low voltage ride-through conditions. The first vector selection is performed according to the relationship between the midpoint potential, the three-phase current direction and the set midpoint potential threshold; According to the relationship between the reference voltage and the first, second, third and zero vectors, the volt-second balance equation is established, and the mid-point potential balance equation is established according to the relationship between the mid-point potential deviation and the small vector. By solving the volt-second balance and the mid-point potential balance equation to obtain the duty ratio of each vector; rearrange the switching action sequence of each vector according to the principle of minimum switching loss to form a switching sequence; construct a value function, select a switching sequence that minimizes the value function, and drive the action of the switching tube; the present disclosure The obtained common-mode voltage of the three-level inverter is one-sixth of the DC side voltage, which reduces the leakage current and electromagnetic interference of the system, reduces the switching loss, and ensures that the mid-point potential is fast when the voltage shifts and oscillates. Recover, maintain balance.

The invention provides an integrated intelligent gas flow meter with double flow measuring heads. The integrated intelligent gas flow meter comprises a measuring tube, wherein flanges are respectively arranged at two ends of the measuring tube, an ultrasonic vortex flow measuring head and a V-shaped tapered flow measuring head are arranged in the measuring tube, a flow control and display unit isalso arranged at the outer side of the measuring tube, and is composed of a measurement switching unit and a flow measuring and controlling unit, the measurement switching unit is connected with the flow measuring and controlling unit to form a closed loop, detecting signals of the ultrasonic vortex flow measuring head and the V-shaped tapered flow measuring head are input to the flow measuring and controlling unit after being switched and controlled by the measurement switching unit, and the flow measuring and controlling unit is used for sending a switching control signal to the measurementswitching unit according to the detecting signals. The flow meter provided by the invention has the advantages of a wide flow detecting range between 0.3m / s and 30m / s, smaller interference for the signals and obviously increased measurement accuracy.

The invention discloses a quick self-adaptive layout method for a map legend. The method comprises the following steps: in a thematic map manufacturing process which uses an administrative area as a range, dividing a space area between an administrative area geographic range and a map printing geographic range into four positions comprising a top left corner, a top right corner, a bottom left corner and a bottom right corner, and endowing one weighting coefficient to each position; using an evaluation rectangle with assigned initial size and length-width ratio to circularly judge, evaluate and grade the spatial relation of the divided positions; and after the grading of all the divided positions is finished, ordering the scores and taking the position with maximum score as a best position, later converting an evaluation rectangle coordinate system where the position with the maximum score is positioned, and finally putting the map legend in the converted rectangle. The method makes full use of the efficient processing performance of a computer, reduces man-machine interaction during the manufacture of the thematic map of the administrative area, and greatly improves the manufacturing efficiency of the thematic map of the administrative area. The method has large application prospect in the manufacture of the thematic map by using the administrative area as a base map.

The invention belongs to the technical field of image processing, in particular to a method for extracting features of a light-weight three-dimensional ultrasonic image of an incisional hernia patch. The present invention first uses the texture feature extraction algorithm to automatically quantify and extract the relevant texture feature parameters of the area to be classified in the three-dimensional volume of interest (VOI) of the automated three-dimensional breast ultrasound (ABUS) image, so as to distinguish the patch from the fascia; and then Aiming at the problem that the two-dimensional texture parameters are sensitive to spatial transformations such as curling and shrinkage of the incisional hernia mesh, three-dimensional texture parameters and three-dimensional position parameters are introduced to improve the robustness of the light-weight patch classification and recognition algorithm; finally, the class The distance algorithm and the sequential forward search method are used for feature selection. The method of the invention has good feature selection effect and high efficiency, can effectively improve the classification accuracy of the light-weight incision hernia patch three-dimensional ultrasonic image, and is convenient for automatic classification and identification.

The invention discloses a Tibetan speech corpus tagging method and system based on cooperative batch active learning, wherein the system includes: a sample selection module, a manual tagging module, a tagging decision module, a tagger evaluation module, and a training set generation module. The invention solves the construction of the sample evaluation function and the proof of the nature of the submodular function through the approach to the optimal batch sample selection method, and solves the construction of the labeling decision function, the construction of the labeler evaluation model and the labeler-assisted learning model through the labeling committee collaborative labeling method mold. In addition, the system of the present invention can realize functions such as optimal selection of samples, annotation evaluation of users, sharing of annotation information and Tibetan phonetic knowledge, assisted learning by annotators, and is intended to improve the tagging quality of Tibetan speech data and speed up the construction of audio corpus.

The invention relates to a structural design optimization method for a deepwater catenary mooring rope. The method aims at an 'anchor chain-steel rope-anchor chain' three-section combined deepwater catenary mooring rope, structural parameters of length of each section of the rope, top pretension, mooring horizontal radiation distance and the like are determined through iterative computation by giving consideration to specific requirements of design specifications on various indicators under the condition of given rope specifications, operating water depth and allowable limit horizontal offset of a floating body, and accordingly horizontal restoration characteristics of the rope reaches optimum under the condition of controlling total steel consumption and mooring load, and then structure types and stress situations of the rope under different states are computed to bring convenience to type selection of mooring equipment. Compared with existing commercial software such as mooring analysis software MOSES and SESAM, the method has the advantages of oriented design, high practicality, high convergence speed and the like, achieves optimal selection of various design parameters and can be used for preliminary scheme design and performance evaluation of deepwater floating type platform catenary mooring systems.

The invention discloses a multi-dimensional information-based monitoring method for abnormal oil temperature on the top layer of a transformer, comprising the following steps: step A, initializing the CS algorithm, establishing a fitness evaluation model of the bird's nest position, and initializing the fitness value; step B, calculating the global maximum The optimal solution and the local optimal solution of each bird's nest location; step C, constructing the Susa thermal circuit calculation model and the SVR regression compensation model respectively according to the identified parameters; step D, based on the Susa thermal circuit calculation model, obtain a preliminary top oil temperature prediction value; step E, based on the SVR regression compensation model, to obtain the final predicted value of the top oil temperature; step F, using the ARIMA method to predict the short-term trend of the residual after the moving average. This scheme fully considers the environmental conditions of the transformer, and identifies and corrects the key parameters in the temperature rise model, predicts the residual error of the top oil temperature, and improves the monitoring accuracy of the transformer top oil temperature.

A method for compressing wireless multi-media sensor network images based on space mapping is used in a wireless multi-media sensor network environment and solves the problems that power source energy, the communication capability and the capabilities of calculation and storage of the wireless multi-media sensor network nodes are limited by means of the technology of multi-node cooperative image collection and compression based on related space mapping. According to the method, a cooperative type processing method is applied, and an analysis framework which is based on entropy is established so as to evaluate the joint function of a plurality of related multi-media sensor nodes. Meanwhile, factors such as correlation among the multi-media sensor nodes, the node communication distance and node energy are comprehensively considered, and therefore the optimal selection of the nodes can be achieved. A new space correlation function is designed to describe the correlated characteristics of images which are observed form an overlapping view of the multi-media sensor nodes. A method of hierarchical clustering is adopted to calculate the combination entropy of the multi-media sensor nodes.

Disclosed are a carrier selection method and a communication device, the carrier selection method comprising: when selecting a carrier, selecting a sending carrier according to a service priority, a resource occupancy rate of an alternative carrier and remaining available resources. According to the scheme of the invention, carrier selection is carried out by combining the resource occupancy rate and the residual available resources, and support of carrier aggregation and optimal selection of carriers and resources are realized.

The invention discloses a carrier selection method and communication equipment, wherein the carrier selection method includes: when selecting a carrier, selecting a sending carrier according to service priority, resource occupancy rate of an alternative carrier and remaining available resources. The scheme of the present invention performs carrier selection in combination with resource occupancy rate and remaining available resources, and realizes support for carrier aggregation and optimal selection of carriers and resources.

An embodiment of the present invention provides a method and device for collecting high-speed data packets, wherein the method includes: determining the target ring from the plurality of ring buffers according to the priority value corresponding to each ring buffer in the plurality of ring buffers Cache area: transfer the data packets in the network card cache area to the target ring cache area. The method provided by the embodiment of the present invention determines the target ring buffer by setting the priority value corresponding to each ring buffer in the plurality of ring buffers, so as to realize the optimal selection of the target ring buffer and reduce the packet loss rate of data packets.

The invention provides a performance evaluation method and an evaluation system for a flame retardant material for a secondary battery, the method comprising: determining the heat Q generated by the secondary battery without the flame retardant material under thermal runaway conditions; determining the generation of 1.1 ‑2.0 times the amount of combustion gas used for the amount of heat Q; the flame retardant material is burned with the amount of gas; an equation for evaluating the flame retardant performance is constructed; the system includes: a heat calculation module for determining that the flame retardant material is not installed The heat Q generated by the secondary battery under thermal runaway conditions; the spray gun, which is equipped with gas fuel, and the heat generated when the gas fuel is burned is Q; the memory is used to record the amount of gas fuel in the spray gun; evaluation The module is used to construct a flame retardant performance evaluation equation, so as to evaluate the performance of the flame retardant material; the technical solution provided by the present invention guides the selection of the flame retardant material for the secondary battery, and further reduces the thermal runaway of the secondary battery. risk factor.

The invention provides a rove vertical transmission feeding and spinning device and method. The spinning device comprises a rear drafting roller pair composed of a rear roller and a rear rubber roller, a middle drafting pair composed of a middle roller and a middle rubber roller and a front drafting pair composed of a front roller and a front rubber roller. The rear roller adopts a roller sleeve which is connected to a roller shaft through a separating bearing, the rear rubber roller adopts a rubber roller sleeve which is connected to a rubber roller shaft through a separating bearing, and retractable gears with retractable teeth on the surfaces are installed at head ends of the rubber roller shaft and roller shaft. Separate servo motors are connected with the retractable gears through gear groups, so that optional driving of the rubber roller shaft and the roller shaft is achieved, selection between active feeding of rove under driving of the roller sleeve and active feeding of the rove under driving of the rubber roller sleeve is achieved, selection of vertical transmission feeding of the rove according to different rove features is correspondingly achieved, and thus optimized selection of a spinning process is achieved.

The invention relates to a virtual network mapping method for realizing the topology awareness based on historical data. The method comprises the following operation steps: (1) according to a historical data set which is accumulated by a bottom layer physical network and is successfully mapped by a virtual network, calculating a dependency matrix M between nodes of the bottom layer physical network; (2) according to the size requirement of virtual nodes in the virtual network on central processing unit (CPU) resources, sorting all the virtual nodes of the virtual network from big to small; (3) according to the dependency matrix M, sequentially carrying out node mapping from the virtual nodes to the bottom layer physical nodes according to a certain sequence; and (4) after completing the node mapping, realizing mapping from a virtual link of the virtual network to a physical path of the bottom layer physical network according to a set link mapping method. The method disclosed by the invention realizes the scientific evaluation on the resource capacities of the bottom layer physical network and the optimization selection of the node mapping by sensing a topological structure of the virtual network, and improves the long-term average success rate of the virtual network mapping.

The invention discloses a method for constructing network layers of wireless sensor networks. The method includes grouping acquisition nodes of the wireless sensor networks; enabling sink nodes to periodically receive node information of the acquisition nodes, acquiring weather forecast index information and constructing characteristic vectors of the acquisition nodes; selecting backbone nodes according to the characteristic vectors; selecting non-backbone nodes from the acquisition nodes according to the backbone nodes, and grading the non-backbone nodes according to the availability of the backbone nodes in communication ranges of the non-backbone nodes; constructing the network layers according to the backbone nodes and grades of the non-backbone nodes. The method has the advantages that characteristic information of the acquisition nodes and the weather forecast index information are periodically received by the sink nodes, the characteristic vectors of the acquisition nodes are constructed, a neural network with a decorrelation layer, an input layer and a competition layer is established, accordingly, sample learning can be carried out, the backbone nodes can be optimally selected, and energy consumption between the nodes can be reasonably distributed.