42results about How to "Realize automatic division" patented technology

The present invention provides a historical wind power output data processing and fluctuation identification method, comprising the following steps: collecting historical wind power output data, and analyzing and sorting it; performing normalization processing and wavelet filtering processing on the analyzed and sorting historical wind power output data , and divide the fluctuations; use the visualization method to test the clustering effect of historical wind power output data and wind fluctuations. The invention provides a historical wind power output data processing and fluctuation identification method, which can be used as the early basis for wind power mid- and long-term output time series modeling, and can also be applied to power system planning and operation analysis including wind power.

An automatic division method of urban drainage pipe network catchment area solves the problem of low efficiency of existing catchment area division, and belongs to the cross-application fields of environmental engineering, visible light remote sensing image semantic segmentation and computer vision. The present invention includes: S1, obtaining remote sensing images of urban target areas, and constructing a training data set; S2, using a convolutional neural network to couple a variant residual network to construct a road network extraction convolutional neural network model, and the variant residual network as a convolution The coding structure of the neural network; S3. Use the training data set to train the road network to extract the convolutional neural network model, and determine the parameters of the road network to extract the convolutional neural network model; S4. Input the remote sensing image of the city to be divided into the road network to extract the convolution In the neural network model, road network information is extracted; S5, the extracted road network information is divided into catchment areas, combined with the prior information on the distribution of rainwater well points, the inverse distance weighted Thiessen polygon method is used to further divide sub-catchment areas .

The invention discloses a bayonet precise positioning capturing method and device based on a multi-target radar, and relates to the technical field of video monitoring. The method comprises the stepsthat a plurality of lane boundary lines of a multiple lane are projected into a radar coordinate system of the radar, lanes are automatically divided after lane boundary line information in the radarcoordinate system is acquired, radar triggering positions of the lanes in the radar coordinate system are acquired by mapping video triggering lines of the lanes into the radar coordinate system, accordingly the lane information and whether a bayonet capturing unit is triggered to capture or not can be rapidly judged according to detected target information output by the radar and transformed to be the information in the radar coordinate system, and if capturing occurs, captured information is output. The method and device provided by the invention avoid the defects of traditional video triggering capturing, and achieve precise capturing. Meanwhile, the defect that a traditional radar cannot differentiate and detect the target lane information is overcome.

The embodiment of the invention discloses a data source division method and device, equipment and a storage medium. The method comprises the steps of acquiring database information corresponding to multiple data sources; performing word segmentation processing on the database information corresponding to each data source, and determining a first feature set corresponding to each data source according to a word segmentation result; determining the similarity between every two data sources according to each first feature word in each first feature set, clustering each data source according to each similarity and a preset clustering algorithm, and determining each data source set; and when the number of the data source sets is equal to the number of the preset service directories, dividing each data source set to the corresponding preset service directory. Through the technical scheme of the embodiment of the invention, automatic and reasonable division of the data source can be realized,and the division accuracy is improved.

A signal processing method of a spectrum analyzer and the spectrum analyzer, the spectrum analyzer includes a radio frequency scanning module, a data acquisition module, a detection module, a display module and a control processing module, wherein the control processing module obtains the endpoints of a plurality of predefined scanning frequency bands Frequency and receive the scanning parameters input by the user, and determine the endpoint frequencies of multiple detection frequency bands according to the endpoint frequencies and scanning parameters of multiple scanning frequency bands. When it is detected that the endpoint frequency of the scanning frequency band does not coincide with the endpoint frequency of any detection frequency The endpoint frequency of the scanning frequency band sent to the radio frequency scanning module is adjusted, the endpoint frequency of the scanning frequency band is sent to the radio frequency scanning module, and the endpoint frequency of the detection frequency band is sent to the detection module, so that the radio frequency scanning module treats it according to the scanning frequency band determined by the control processing module The test signal is scanned so that the actual scanning frequency band matches the frequency range of the entire RF scanning and the data processing requirements configured by the user.

The invention discloses a message processing method and apparatus. The method comprises the following steps: performing grade division on received messages according to a preset grade division strategy, and determining a grade to which each message belongs; and responding to a first message processing operation of a user, performing first processing on the message of the corresponding grade of thefirst message processing operation. In the message processing method and apparatus disclosed by the invention, automatic grade division of the received messages is achieved, the time consumption is short, a user can conveniently select the message of a certain grade for processing according to the importance of the message, thereby being convenient to process the important messages and avoiding delaying the processing of the important messages.

The invention discloses an automatic classification method for layered rock side slopes. The method comprises the following steps of (1), preprocessing a ridge line, and dividing a mountain boundary based on the ridge line for forming a side slope unit; (2), calculating side slope attitude information and bed attitude information; and (3), according to a layered rock side slope classification standard, classifying the side slopes. The automatic classification method can realize automatic classification of the layered rock side slopes and furthermore has advantages of high automation degree, high objectivity, and effective satisfaction for classifying large-range layered rock side slopes.

The present invention relates to the technical field of data mining; a user level automatic segmentation method and system. Said method comprises: selecting original sample data; selecting at least one user feature to act as a dimension for calculating distance; determining a number K of classifications; randomly picking K number of users from the original sample data to act as initial class centers; measuring the distance of each remaining user in the original sample data to each current class center, and sorting each remaining user to the nearest class, thereby completing segmentation of K number of classes; recalculating the class centers of each class; repeating the iteration of S5 and S6 until the new class centers are equivalent to the original class centers or stopping iterative operations when the degree of variation is less than a specified threshold, and the currently segmented K number of classifications are considered the user level classifications which need to be segmented. The method may achieve user level automatic segmentation which is accurate, efficient, and which saves on labor costs.