43results about How to "Reduce the number of combinations" patented technology

The invention relates to a multi-input multi-output wireless communication system, in particular to a beam forming algorithm of a multi-user pairing virtual multi-input multi-output (MIMO) system. Directing at the problems in the prior art, the beam forming algorithm of the multi-user pairing virtual MIMO system is provided. Based on a maximized signal to interference plus noise power ratio standard, beam forming vectors of paired users are determined one by one and are enabled to approach an optimal condition, the problems that when a single-user terminal is provided with a plurality of antennas, the virtual MIMO system cannot utilize terminal multi-antenna resources so that transmission efficiency is not high are resolved. Due to the fact that the user terminal is provided with the plurality of antennas, base station receiving signal to interference plus noise power ratio is improved under the scene of an uplink virtual MIMO system transmission, and accordingly transmission quality is improved. The beam forming algorithm is applied to the field of virtual MIMO system uplink data transmission.

The invention provides a multi-label image classification method, a device and an electronic device. On the one hand, a first characteristic image is classified by using a pooling layer and a full connection layer to obtain a first label classification prediction result. On the other hand, according to the parameters of the whole connecting layer and the first characteristic image, the first characteristic image is filtered to obtain the second characteristic image. The parameters of the full connection layer and the convolution layer are optimized based on the metric learning algorithm. Then,the second feature image is pooled to obtain a second tag classification prediction result. At last, the prediction result of the target label classification is obtained by synthetically consideringthe prediction result of the first label classification and the prediction result of the second label classification. The method performs label classification from two aspects, corrects the first label classification prediction result based on the second label classification prediction result obtained from the second feature map, reduces the number of label combinations, and assists in improving the multi-label image recognition accuracy.

The invention relates to a self-positioning vacuum brazing technique for a multi-cavity electrical bridge waveguide. The self-positioning vacuum brazing technique comprises the following steps of preparing materials and finishing the machining of an upper part and a lower part of the waveguide; respectively carrying out surface treatment on the machined upper and lower parts of the waveguide; producing brazing filler metals according to overall dimensions of the upper part and the lower part of the waveguide and assembling the upper part and the lower part of the waveguide and the brazing filler metals; matching the assembled electrical bridge waveguide with a work fixture and placing the assembled electrical bridge waveguide and the work fixture into a vacuum aluminum brazing furnace; carrying out vacuum brazing on the multi-cavity electrical bridge waveguide according to a vacuum brazing temperature process curve; carrying out numerical control machining on the shape of the waveguide and a ring flange; drilling and carrying out electrochemical treatment. According to the self-positioning vacuum brazing technique disclosed by the invention, the ring flange and a waveguide tube are integrally formed at one time, so that the processing work procedures are simplified, and the production period is short; a groove and a shoulder are arranged, so that self positioning is realized, combined times are reduced, and the assembly precision is high; one-time welding forming is realized by adopting vacuum brazing, and thus the deformation of cavities caused by multiple times of welding is avoided; in addition, no brazing flux is needed, and thus the corrosion of the brazing flux to the cavities is avoided, and the service life of the multi-cavity electrical bridge waveguide is prolonged.

The invention provides a lease data processing method and a device for cloud computing resources, and electronic equipment, relates to the technical field of data processing, and solves the technicalproblem that the maintenance cost of pricing reference factors of cloud computing products is too high. The method comprises the steps of determining user ordering information, wherein the ordering information comprises information of at least one product ordered by a user; matching at least one target charging item and at least one target influence factor corresponding to each charging item according to the information of each product; for each target charging item of each product, determining pricing information of the product corresponding to the target charging item according to the targetcharging item and at least one target influence factor corresponding to the target charging item; and thus, determining the price of each product according to the pricing information of each productfor all the target charging items.

The invention discloses a transient stability out-of-limit probability calculation method and device considering new energy power generation uncertainty, and the method comprises the steps: calculating a comprehensive impact factor of a new energy field station for the transient stability of a power grid according to the transient stability margin of a transient stability key mode and a new energyfield station participation factor, and determining a leading new energy field station; according to the new energy station active probability distribution density function, the active real-time planning value and the comprehensive influence factor of the active real-time planning value on the transient stability of the power grid, determining an active sampling interval of the leading new energystation, and generating an active grading interval combination of each leading new energy station; calculating the transient stability margin of the anticipated fault in the power grid operation state corresponding to each combination to obtain a transient stability margin out-of-limit combination; and calculating the transient stability out-of-limit probability of the new energy power generationuncertainty according to the probability of the combination of the anticipated fault occurrence probability and the transient stability margin out-of-limit. Quantitative evaluation of the transient stability out-of-limit risk of the power grid is realized.

A design support apparatus comprises: an experiment plan section 11 that selects a combination of design parameter values by allocating the design parameter values to an orthogonal table; a simulation input creating section 12 that creates an input into the simulation by allocating outside factors such as an error factor and a signal factor as inside factors to an orthogonal table to thereby reduce the number of combinations of the design parameter values: a simulation instructing section 21 that issues an instruction to execute the simulation by using the input into the simulation; and an analyzing section 30 that calculates a set of design parameter values and a characteristic value based on results of the simulation and performs analysis.

The invention discloses a partial maximum likelihood detection method based on energy ordering. Firstly, the minimum mean square error (MMSE) equalization is used to equalize the number of subcarriers, then the energy value of each subcarrier is calculated and sorted to set the number of candidate subcarriers p, and then the maximum likelihood detection is used to detect the number of partial subcarriers, antenna number and constellation symbol. Sub-carrier blocking can make up for the error retransmission defect of receiver demodulation, By comparing the power of equalized symbols on the subcarriers, the subcarrier sequence number can be demodulated, and the number of combinations traversed can be reduced by adding a partial maximum likelihood detection algorithm, which reduces the complexity to a certain extent, and the setting of P value can achieve a good tradeoff between the system bit error rate and complexity.

The invention relates to an object data processing method and device, computer equipment and a storage medium. The method relates to a decision tree model in the field of machine learning, and comprises the following steps: converting object behavior data corresponding to each portrait dimension into a strategy effect corresponding to a target strategy according to the proportion of a first hit category belonging to the implementation of the target strategy on a sample object in the object behavior data corresponding to each portrait dimension of the object portrait data; inputting the strategy effect corresponding to each portrait dimension into a decision tree model, and training the decision tree model by taking strategy effect optimization corresponding to portrait dimension combinations represented by nodes in the decision tree model as a target to obtain a group division decision tree; and determining an optimal subdivision group corresponding to the target strategy based on thestrategy effect corresponding to each subdivision group represented from the root node to the leaf node of the group division decision tree. By adopting the method, the efficiency of mining the subdivided group strategy result from the test result can be improved.

The invention discloses a rapid automatic detection method for counting a row number of corn ears. The method mainly comprises the three steps of firstly, building a row gap theoretical model according to characteristics that the row number of the ears is an even number and the cross sections of the ears have a rotation symmetry theory; secondly, collecting positive side images of the corn ears, displaying a kernel row gap in a highlighted manner, and obtaining an actual measurement mode of the row gap; and finally, performing matching check on the actual measurement mode and the theoretical model, thereby obtaining the theoretical model corresponding to a minimum distance between the actual measurement mode and the theoretical model, wherein the ear row number of the theoretical model isnamely the calculated ear row number. The method is simple in step, small in calculation amount and high in detection accuracy.

The invention provides a parameter configuration method and a communication device. The method comprises the following steps: the terminal device receives an indication of a first mapping relationshipfrom the network device, wherein the first mapping relationship is one mapping relationship in a pre-configured first mapping relationship group, and the first mapping relationship group comprises atleast one mapping relationship used for indicating at least one corresponding relationship between the reported number of spatial domain vectors and the reported number of frequency domain vectors; and the terminal equipment determines the reporting number of the spatial domain vectors and the reporting number of the frequency domain vectors according to the first mapping relationship. Therefore,by pre-defining various possible corresponding relations between the L value and the M value, the selection range of the reporting number can be reduced, the selection range of the reporting number can be reduced, and the calculation amount and the indication overhead for determining the reporting number by the network equipment can be reduced.

The invention discloses a production process of jacquard fabric with a petit point effect and belongs to the technical field of jacquard weaving. The production process comprises specification design,fabric weave design and looming weaving, wherein a warp combination comprises a larger number of surface warp and a smaller number of lining warp, a weft combination is formed by weft A, weft B and weft C, the looming warp density and the looming weft density are 112.8 pieces/cm and 114 pieces/cm separately, the proportion of the weft A, the weft B and the weft C is 1:1:1, a single loom beam is adopted for weaving, ground weave is double-layer weave, surface-layer weave is through hole weave, lining-layer weave is plain weave, a surface layer is formed by interweaving the weft A and the weftB both in the opening state with the surface warp, a lining layer is formed by interweaving the weft C at the other opening with the lining-layer warp, and the weft C is partially connected with the surface-layer warp. The jacquard fabric having high warp and high weft density and prepared with the process has remarkable petit-point texture and a good weaving yarn hole effect.

The invention provides a combined limiting condition data preprocessing method in truck path planning, and relates to the field of data preprocessing methods. The combined limiting condition data preprocessing method in truck path planning comprises the following steps: S1, setting an initial combined condition value: S2, establishing a binary tree result to store an optimal path calculation result, and taking a current condition as a root node; S3, recursively executing the following calculation steps to obtain path planning results under all combination conditions: S3-1, according to the current node parameters, calculating an optimal path for truck passing under the conditions that the truck height is h_min and the truck weight is w_min; S3-2, according to the optimal path calculation result, obtaining the optimal path planning result. According to the invention, a binary tree mode is used to represent all combination conditions of truck height and weight limitation. According to the method, the preprocessing calculation efficiency is greatly improved, the space occupied by the preprocessing data is reduced, the application range of the preprocessing planning method in truck navigation is widened, and the method can also be applied to offline navigation equipment with limited storage space to improve the route planning efficiency.

The invention discloses a container anomaly detection method and system, and belongs to the technical field of cloud computing security. The method comprises the steps: firstly collecting log data, filtering, simplifying and complementing the log data, and innovatively proposing to obtain new log data according to column numbering; then, respectively calculating the support degree of each column of elements in the new log data, removing the elements with the support degree smaller than the minimum support degree in each column, independently storing the remaining elements in each column, and adding zero elements to the ends of the remaining elements; sequentially and randomly selecting one element according to columns, combining the elements, and judging the support degree of the combination to find out all element combinations of which the support degree is greater than or equal to the minimum support degree and the length is equal to the log entry field number; and finally, feeding back the selected part of element combinations with the maximum weights to a system administrator so as to carry out container anomaly detection. Therefore, the method can help a system administrator to quickly and accurately position the abnormity, and reduces the burden of system maintenance personnel.