17results about How to "Easy mapping" patented technology

The invention provides a secondary network thermal load prediction method based on a CEEMDAN-KPCA-LSTM algorithm. The method comprises the following steps: dividing a complemented data set into a training set and a test set according to a proportion; key factors influencing the dynamic change of the thermal load of the secondary network in the training set data are used as input variables, and the thermal load data are used as output variables; performing local encryption and standardization processing on the thermal load data; building an improved neural network model for predicting the dynamic thermal load of the building; training the improved neural network model, and when the improved neural network model meets a convergence condition, obtaining a trained improved neural network model; performing standardization processing on the test set data, and setting test set input data according to an input variable selected from the test set data after standardization processing of the training set data; and inputting test set input data into the trained improved neural network model to realize prediction of the dynamic thermal load of a certain building in the future 24 hours.

The invention relates to a rapid conversion method and system from explicit geometry to implicit geometry, and the method comprises the steps: constructing a linear boundary body hierarchical structure for an input triangular grid, and constructing an octree structure; nodes of the octree structure are used as sampling points, and an adaptive grid unsigned distance field is calculated in parallel for each sampling point; calculating a pseudo normal of the triangular mesh by using an angle weight pseudo normal algorithm, and calculating a symbol of the unsigned distance field of the adaptive mesh by using the pseudo normal of the triangular mesh; and determining data of the sign distance field according to the adaptive grid unsigned distance field and the sign of the adaptive grid unsigned distance field, and completing conversion from implicit geometry to explicit geometry. According to the method, the conversion from implicit geometry to explicit geometry can be quickly realized, the conversion efficiency is greatly improved while high precision is kept, and the performance of graphic processing, physical simulation and application scenes can be improved.

The invention provides a distributed energy information modeling method for on-site coordination control of an active power distribution network, and belongs to the technical field of power grid control. Comprising the following steps: based on intelligent electronic equipment and a distributed energy system, establishing an equipment side information model according to an IEC61850 standard; according to an IECCIM expansion principle, distributed energy CIM expansion is carried out on the power system information model at a master station side; performing static topology model fusion and measurement model fusion on the equipment side information model and the electric power system information model after CIM expansion; and constructing a fusion model by utilizing a protocol mapping mode, and mapping data of the equipment side information model and the power system information model by utilizing the fusion model. According to the invention, the problem of model fusion between the terminal equipment and the distributed energy and the master station system is solved, a unified lightweight object-oriented information model for distributed energy cooperative control is established, and reliable and real-time exchange of equipment-equipment and equipment-master station information is realized.

The invention relates to the technical field of ship segmented site visual Kanban, and discloses a ship segmented site visual Kanban system, and a system operation method comprises the following steps: S1, collecting site information, and obtaining the maximum length Larea and the maximum width Warea of an actual segmented site of a shipyard; according to the method, the real-time conditions of all sites can be comprehensively mastered, the optimal segment placement position can be accurately found, reasonable site layout planning can be realized, the segment storage efficiency and accuracy of ship enterprises can be effectively improved, the site space utilization rate is optimized, the storage cost is reduced, the overall efficiency of ship manufacturing is further improved, and the economic benefit is increased. And accurate correspondence between the data site model and the actual site can be ensured, so that the real contour of the actual site can be mapped conveniently, and accurate proportion correspondence between the site model, the segmentation model and the global segmentation site total model is ensured.

The present invention discloses an antibody targeting human Nectin4 protein and its application; the antibody comprises five groups of heavy chain variable regions and five groups of light chain variable regions, and the five groups of heavy chain variable region amino acid sequences can be combined with five groups of light chain variable region amino acid sequences for double chain use. The antibody can specifically recognize human Nectin4 antigen, and has good specificity in normal human tissues, only binds to Nectin4 positive tissues, does not recognize other tissues and organs, and has no off-target risk; at the same time, the antibody has good targeting for both natural configuration state and recombinant configuration state, and has good application prospects for antibody drugs, multi-antibody drugs and recombinant antibody proteins.

The invention discloses an anti-collision azimuth angle measurement method based on a student psychology optimization algorithm, and the method comprises the steps: obtaining signal data transmitted by a radio frequency end, processing the signal data through employing a convolutional neural network, obtaining a sample label, defining a hardware link process from an antenna to a receiving and transmitting module, building an anti-collision angle measurement model through the combination of the sample label, and obtaining an anti-collision azimuth angle measurement model. A student teaching and learning optimization algorithm is adopted to carry out parameter configuration on an anti-collision angle measurement model, anti-collision azimuth angle measurement is carried out based on the anti-collision angle measurement model after parameter configuration, a set of reusable and high-precision anti-collision angle measurement model is formed by adopting an identification optimization thought, the multidimensionality of sample data is increased, and calculation errors are reduced.

The invention discloses an antibody targeting a human Nectin4 protein and an application of the antibody. The antibody comprises five groups of heavy chain variable regions and five groups of light chain variable regions, and amino acid sequences of the five groups of heavy chain variable regions can be respectively combined with amino acid sequences of the five groups of light chain variable regions for double-chain use. The antibody can specifically recognize a human Nectin4 antigen, has good specificity in human normal tissues, is only combined with Nectin4 positive tissues, does not recognize other tissues and organs, and has no off-target risk; meanwhile, the antibody has good targeting performance on a natural configuration state and a recombinant configuration state, and has good application prospects of antibody drugs, multi-resistance drugs and recombinant antibody proteins.

This invention relates to the field of spectroscopic detection technology, specifically disclosing a method and system for determining the composition of titanium alloys based on a spectrometer. The method includes: acquiring raw spectral data of a titanium alloy sample using a spectrometer, filtering high-frequency noise from the raw spectral data to obtain clean spectral data; detecting local minima in the clean spectral data to construct a baseline profile of the titanium alloy sample, and performing drift calibration on the baseline profile to obtain optimized spectral data; comparing the characteristic wavelength heights of adjacent elements and integrating the obtained peak data into characteristic spectral peaks; performing similarity matching between the characteristic spectral peaks and wavelengths in a preset element characteristic wavelength library to determine the intensity of the characteristic peaks; extracting element concentration data and correlating the element concentration data with the intensity of the characteristic peaks to construct a calibration curve; mapping the optimized spectral data to the calibration curve to generate composition ratio data. This invention can improve the efficiency of spectrometer-based titanium alloy composition determination.

The invention discloses a prediction time coding method based on large language model prior, and belongs to the technical field of marine meteorology. According to the method, periodic and nonlinear change rules of ocean state variables on different time scales are systematically coded into time embedding, and the expression ability of time features is improved. According to the method, the prior knowledge of a large language model is utilized, the extraction and mapping process of time features is optimized, the time embedding quality and efficiency are improved, time information is converted into context semantic embedding, and accurate expression and efficient utilization of the time features are achieved. The forecasting precision can be improved, and error accumulation is reduced; the model training and maintenance cost is reduced; the time feature expression ability is enhanced, and the model generalization ability is improved; the operation convenience and practicability of the forecasting system are improved; resource utilization is optimized, and energy consumption is reduced; and the reliability and stability of the forecasting system are improved.

The utility model provides a bidirectional solid state circuit breaker module comprising a first sub-module and a second sub-module, the first sub-module comprises a first part, and the second sub-module comprises a second part. At least the first part of the first sub-module and at least the second part of the second sub-module have the same configuration and are symmetrically arranged relative to each other. Each of the first part and the second part comprises a substrate and at least two power semiconductors and at least one energy absorption element which are arranged on the substrate, and the at least one energy absorption element is arranged in the middle of the substrate; the at least two power semiconductors are arranged around the at least one energy absorbing element.

The invention relates to a time sequence and convolution combined computing power weblog anomaly detection method and system. According to the method, template classification of massive network calculation logs is accelerated by utilizing a hash optimized log template analysis algorithm based on an analysis tree. And meanwhile, the log variables can effectively construct spatial features by utilizing Hash-based spatial coordinate mapping. In addition, the log sequence features based on semantic information and the original sequence features of the logs are considered by combining the sequential network and the convolutional network, and the variable space features on the time sequence are also fully considered, so that the neural network model in the method has higher detection accuracy and robustness.

This invention discloses a three-dimensional visualization display method, system, and related equipment for health evaluation of concrete structure contact joints. This solution is based on the spatial positioning information of the detection equipment and simultaneously displays the detection results with labels. Furthermore, it is integrated with the engineering model to achieve three-dimensional visualization for health evaluation of concrete structure contact joints, thereby effectively overcoming the problems existing in the prior art.

The embodiment of the present application provides a data processing method, a data processing model, a system and a computing device. The method includes the following steps: obtaining data generated in a data processing event; converting the data into patterned information corresponding to a preset mode in a preset data processing model; supplementing dimension information for the patterned information according to the event record of the data processing event; wherein the dimension information is the basis for determining whether the patterned information belongs to the processing object of a processing task. The technical solution provided by the embodiment of the present application has a higher versatility in the data processing process; even if the business changes, the previously generated patterned information will not be affected. In addition, supplementing the patterned information with dimensional information is, firstly, to facilitate subsequent data processing, such as data accounting, auditing, etc.; secondly, it is easy to map to specific accounting subjects to access the existing data accounting system.

The invention discloses an antibody targeting a human Nectin4 protein and an application of the antibody. The antibody comprises five groups of heavy chain variable regions and five groups of light chain variable regions, and amino acid sequences of the five groups of heavy chain variable regions can be respectively combined with amino acid sequences of the five groups of light chain variable regions for double-chain use. The antibody can specifically recognize a human Nectin4 antigen, has good specificity in human normal tissues, is only combined with Nectin4 positive tissues, does not recognize other tissues and organs, and has no off-target risk; meanwhile, the antibody has good targeting performance on a natural configuration state and a recombinant configuration state, and has good application prospects of antibody drugs, multi-resistance drugs and recombinant antibody proteins.

A process for the methacrylation of dECM comprises placing a carbonate buffer at a concentration of 1 M into a reaction vessel and heating to a temperature of 50 DEG C, adding dECM to the carbonate buffer to obtain a dECM solution at a concentration of 4% (w / v), sterilizing the solution by irradiation with radiant ultraviolet rays for 15 minutes, adding methacrylic anhydride in an amount of 0.5 mL / 1 g of dECM and reacting at 50 DEG C for 1 hour, and then removing the dECM from the reaction vessel. Then adding a phosphate buffer salt solution to obtain a diluent which is 5 times of the mixture, putting the obtained solution into a dialysis tube, then putting the dialysis tube into deionized water, carrying out the stage at 40 DEG C for not more than 4 days, after the stage is completed, transferring the solution in the dialysis tube into an aluminum plate, and then standing at-80 DEG C for at least 3 hours, and then freeze-drying the frozen solution under the following conditions: the shelf temperature is 10 DEG C, the pressure is 0.1 mba, and the freeze-drying time is 48 hours. The invention also relates to the methacrylated dECM obtained by the above process, and to the use of the methacrylated dECM obtained by the above process in a bioprinting process.

The invention discloses a carriage loading rate determination method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring reference image data, wherein the reference image data is a carriage image of a target vehicle shot by a shooting device facing the tail of the target vehicle; determining first image information according to the reference image data, wherein the first image information is used for describing contour information of a target object in the reference image data; the target object comprises an object related to the carriage; determining second image information corresponding to the first image information, wherein the second image information is used for describing depth information associated with the contour information of the target object in the carriage of the target vehicle; compartment grid information of the target vehicle is determined according to the first image information and the second image information; and mapping the first image information and the second image information corresponding to the target package into the compartment grid information, and determining the compartment loading rate according to the grid proportion. The problem of high hardware cost is solved, and the accuracy of determining the loading rate is improved.

The embodiment of the invention belongs to the field of artificial intelligence, and relates to a poster generation method, which comprises the following steps: acquiring an initial poster image; inputting the initial poster image into an image model in a poster generation model to obtain poster image features and multi-modal information of layout elements in the initial poster image; inputting the multi-modal information into a layout model in the poster generation model to obtain layout information; inputting the poster image features and the layout information into a cross attention network in a poster generation model for feature interaction to obtain improved layout information; and mapping the improved layout information back to the image space to obtain a target poster image. The invention further provides a poster generation device, computer equipment and a storage medium. According to the invention, the accurate layout of each element in the poster is automatically realized.