28results about How to "Improve selection accuracy" patented technology

The embodiment of the invention provides a vehicle autonomous lane changing method and system, electronic equipment and a storage medium, and belongs to the technical field of vehicle intelligent control. According to the method, driving styles of a vehicle and surrounding environment vehicles are considered, driving styles of a target vehicle owner and surrounding vehicle owners are implicitly represented by historical track data of a target vehicle and the environment vehicles through a hidden layer of a lane changing decision model, and lane changing decision index characteristics influencing lane changing behaviors are considered at the same time, so that the driving styles of the target vehicle owner and the surrounding vehicle owners are represented. The driving style features and the lane changing decision index features are input into the full connection layer of the lane changing decision model, the full connection layer combines input data to carry out lane changing decision, the lane selection accuracy can be remarkably improved, and meanwhile compared with a driving style explicit definition lane selection mode, the mode of embedding the driving style hidden features has the advantage that the lane selection efficiency is improved. Personalized driving styles can be reflected, the flexibility of autonomous lane changing decision making is improved, and the intelligent level of automatic driving is improved.

The present invention discloses a method and device for optimizing the K value of a distribution network conductor, which comprises the following steps: obtaining the tension resistance property of each pole position in the distribution network, generating a pole position set with an open tension resistance property; assigning an initial K value to each pole position in the pole position set; selecting a first K value and a second K value from a plurality of initial K values; assigning a first K value or a second K value to each pole position in the pole position set; assigning a K value to a pole position with a non-open tension resistance property in the distribution network; and determining the K value of a conductor between two adjacent pole positions according to the K values ​​of the two adjacent pole positions. The present invention assigns an initial K value to each pole position, selects a first K value and a second K value from a plurality of initial K values, and determines the K value of the conductor by using the first K value and the second K value, thereby improving the selection accuracy of the K value of the conductor, providing a data basis for a subsequent distribution network design process, and reducing the potential safety hazards of the distribution network.

The present application belongs to the field of aquatic genetic breeding, and relates to a SNP molecular marker related to the number of intermuscular bones of yellow river carp, primer groups and application in breeding yellow river carp with less intermuscular spines; the present application provides a group of SNP molecular markers significantly related to the number of intermuscular bones of yellow river carp, and the yellow river carp with less number of intermuscular spines can be quickly screened by using the group of SNP molecular markers. Based on the phenotype determination of the number of intermuscular bones of 917 yellow river carps and the whole genome resequencing data of 445 individuals, through GWAS analysis, the present application first identifies the SNP site on chromosome A24 which is significantly related to the number of intermuscular bones, and provides a reliable molecular marker for the breeding of low intermuscular bone strain of yellow river carp.

The present application relates to the field of Internet of Things security access technology, and specifically to a distributed IoT security authentication method, system and smart terminal device, which specifically includes: obtaining the attributes common to the current node and the target node to construct a common attribute set, and constructing the credibility of each known node based on the frequency of the node receiving information and the most recent communication time of the known node; constructing other attribute distribution vectors in combination with the appearance of the attributes of the known nodes in the common attribute set; constructing a reference attribute distribution vector based on the similarity between the data that the current node needs to transmit and the data transmitted by the known node to the current node, and combining the credibility; obtaining the attributes used for encryption based on other reference attribute distribution vectors and the security level of the target node, and performing security authentication through attribute encryption. While improving the reliability of security authentication, compared with traditional attribute encryption, the attributes used in encryption are reduced, and communication efficiency is improved.

The invention discloses a file information identification method, system and device and a computer program product. The method relates to the field of financial science and technology, and comprises the steps that a to-be-identified file sent by a block chain platform is received, and the to-be-identified file is sent to the block chain platform by a management platform; a model comparison rule is obtained, a target model is determined from the model comparison rule according to the file type of the to-be-recognized file, the model comparison rule comprises a corresponding relation between multiple file types and a preset model, and the preset model is used for recognizing document information of the to-be-recognized file; and identifying the to-be-identified file by using the target model to obtain file identification information. According to the method and the device, the problems of low accuracy of selecting the identification model and low accuracy and low efficiency of identifying the character information when the identification model is used for identifying the file in the related technology are solved.

The present invention belongs to the technical field of molecular genetics, and specifically relates to a SNP site related to the fine wool rate of fine wool sheep and its application. The SNP molecular marker described in the present invention is located at the A / T mutation of the 236304249th nucleotide site on chromosome 1 of the international sheep reference genome Oar_v4.0 version. The present invention also provides the use of a reagent for detecting the above-mentioned SNP site in detecting the fine wool rate trait of fine wool sheep or in molecular marker-assisted breeding of fine wool sheep, which has great application value in fine wool sheep variety screening, variety identification or molecular marker-assisted breeding; it is used for early breeding selection, shortening the generation interval, accelerating the breeding process, saving a lot of breeding costs, and has broad market prospects.

The application discloses a product optimal viewpoint fast selection method and device based on multi-view and cross-modal distillation, belongs to the multi-view deep learning and cross-modal distillation technical field, and comprises the following steps: obtaining viewpoint label data, multi-view data and 3D point cloud data from product 3D data; constructing an optimal viewpoint selection model comprising a point cloud optimal viewpoint regression network and a multi-view optimal viewpoint regression network; inputting the product 3D data into the optimal viewpoint selection model to obtain an optimal viewpoint; training the point cloud optimal viewpoint regression network by using the viewpoint label data and the 3D point cloud data to obtain 3D structure information; training the multi-view optimal viewpoint regression network by using the viewpoint label data and the multi-view data to obtain 2D feature description; using cross-modal distillation to enable the 2D feature description to learn the 3D structure information, then regression optimization is performed on the optimal viewpoint, and finally, the optimal viewpoint selection model is obtained through reverse propagation. The application can keep high-precision viewpoint selection under a small amount of input views.

The invention discloses an on-line monitoring method, system, equipment and medium for industrial wastewater treatment, and the method comprises the following steps: determining key sampling areas for monitoring each treatment stage of industrial wastewater, and sequentially communicating according to the sequence of the treatment stages to generate candidate monitoring paths; performing correlation analysis on the reference monitoring path and the candidate monitoring path to determine a current target monitoring path; constructing an optimization model, solving by using 0-1 integer programming to determine the position and the number of target sampling points of each key sampling area, and determining a first monitoring scheme in combination with a sampling period; and predicting a water quality change trend of each key sampling area according to historical monitoring data and a current monitoring result, constructing a correction model according to the water quality change trend, and dynamically adjusting the first monitoring scheme for monitoring of a next period. According to the invention, the monitoring path can be flexibly planned, the position and number of the monitoring points can be scientifically selected, the monitoring scheme is dynamically adjusted in combination with historical data, the monitoring efficiency and quality are improved, and the monitoring cost is reduced.

The present invention relates to the field of environmental data processing technology, and in particular to an intelligent monitoring and early warning system for emergencies, comprising an adjustment box and a camera device, wherein the inner cavity of the adjustment box is provided with an adjustment component; the adjustment component comprises an adjustment block, the surface of the adjustment block is provided with an adjustment groove, the inner cavity of the adjustment groove is slidably connected with a running block, and one side of the running block is fixedly connected with a connecting rod; the inner cavity of the adjustment box is provided with a front and rear adjustment component; the front and rear adjustment component comprises a first motor fixedly connected to the adjustment box. The present invention has the function of automatically circling the area to be released on the map to replace the manual circling process, which can greatly improve the efficiency of map circling, and the ultimate goal is to improve the efficiency of early warning information release.

The application discloses a SNP molecular marker related to the body weight of Harpadon microchir, which is characterized by being located at the 4593166th base of the 23rd chromosome of the Harpadon microchir, and the sequence of the SNP molecular marker is shown as SEQ ID NO. 1, and the 301st base from the 5' end is A or G; wherein the body weight of an AA genotype individual is significantly higher than that of an AG or GG genotype individual. The application further discloses primers and a kit for detecting the SNP molecular marker, and application of the primers and the kit in breeding of a fine strain of the Harpadon microchir. The application can be used for early screening of breeding materials of the Harpadon microchir, shortening of a breeding cycle, improvement of selection accuracy and overcoming of the limitation of phenotype dependence in traditional breeding.

This application relates to a method, system, and computer device for selecting the number of pulses for blind vias. The method includes: obtaining the adaptive power of a test board; machining multiple first blind vias on the test board using the adaptive power and different pulse test counts; observing the hole quality characteristics of the multiple first blind vias; and selecting an appropriate number of pulses from the different pulse test counts. This method improves the accuracy of selecting the number of pulses for blind vias, thereby improving the machining quality of blind vias.

The present invention provides a multi-sequence seabed intelligent water sampling system and method based on deep learning. The system includes a multi-sequence water sampler, an underwater camera, a sonar, an environmental parameter sensor unit and a power unit arranged on the multi-sequence water sampler; and a central processing unit; the central processing unit is used to receive data collected by the underwater camera, the environmental parameter sensor unit and the sonar in real time, and use a pre-trained deep learning model to perform image recognition on the data collected by the underwater camera, and control the multi-sequence water sampler to perform seawater sampling according to the recognition result and the data collected by the environmental parameter sensor unit and the sonar, and control the power unit to drive the multi-sequence water sampler to achieve adaptive movement; the present invention can realize tasks such as accurate selection of seabed sampling points, construction of three-dimensional seabed terrain, adaptive selection of water sampler sampling timing, and adaptive sample detection around seabed sampling points.

The invention provides an improved deployment method and system for a multi-feature fusion entity co-reference resolution model. The method comprises the following steps: S1, constructing a multi-feature fusion entity co-reference resolution model; the multi-feature fusion entity co-reference resolution model comprises a word embedding layer, a feature extraction layer, a to-be-resolved item trimming layer and an output layer; and S2, processing an input text by using different layers of the multi-feature fusion entity co-reference resolution model, and deploying the multi-feature fusion entity co-reference resolution model. According to the end-to-end-based multi-feature fusion entity co-reference resolution model provided by the invention, by effectively capturing semantic information and contexts of words, potential co-reference relationships in documents are deeply mined, and a machine is helped to more efficiently and accurately understand and analyze complex texts.

The invention provides a 2.5 K liquid phase chip for local chicken egg yield character breeding and application of the 2.5 K liquid phase chip, and belongs to the technical field of genome breeding. The 2.5 K liquid phase chip for local chicken egg yield character breeding comprises a probe combination, the probe combination is used for identifying the genotype of each SNP site in the SNP site combination; the SNP locus combination is composed of 2499 SNP loci which are shown in a table 1 and are positioned on a chicken reference genome GRCg6a. The 2.5 K liquid phase chip is mainly designed according to breeding selection of local chicken egg yield characters, has the advantages of high genotyping detection rate, flexibility in customization, high universality of different local chicken varieties and the like, can effectively reduce the cost of whole genome genotyping while ensuring the accuracy of genetic evaluation through a filling technology, and has a wide application prospect. And core technical support is provided for popularization and application of a local chicken genome breeding technology in small and medium-sized breeding enterprises and accelerated improvement of complex egg yield characters.

The present invention belongs to the field of genetic engineering technology, and more particularly to a distal enhancer of the ADAMTS1 gene related to the tail type of sheep and its application in the early screening of fat or thin tails of sheep. The distal enhancer of the ADAMTS1 gene of the present invention is located at chromosome 1, 128464792-128465192 of the sheep reference genome ARS‑UI_Ramb_v2.0. By detecting the influence of the distal enhancer on the expression of the ADAMTS1 gene, different tail type traits of sheep can be detected, which can be used for the early selection of sheep with different tail types, improve the accuracy of seed selection, shorten the breeding cycle, speed up the breeding process, and provide a scientific basis for the molecular marker-assisted selection of sheep.

This invention discloses a SNP molecular marker of the AFF3 gene associated with broiler meat quality traits and its applications, belonging to the field of molecular biology. The nucleotide sequence of this SNP molecular marker is shown in SEQ ID NO.3, with an A / G mutation at base position 601, and genotypes including AA, AG, and GG. This invention also provides primer pairs for amplifying this molecular marker and a detection method. This SNP site is significantly correlated with leg muscle pH, breast muscle pH, breast muscle conductivity, and breast muscle shear force. Genotype detection can identify broiler meat quality traits, which can be applied to marker-assisted breeding to improve selection accuracy.

The present invention relates to the field of molecular marker technology, and specifically provides a pig whole genome low-density 3K SNP chip and its application. The pig whole genome low-density 3K SNP chip provided by the present invention contains a SNP molecular marker combination for pig genotyping, and the SNP molecular marker combination consists of 3627 SNP molecular markers, and the position and polymorphism information of the SNP molecular markers are shown in Table 1 No. 1-3627. The pig whole genome low-density 3K SNP chip or molecular marker combination of the present invention can be applied to multiple fields such as pig whole genome breeding value evaluation, cluster analysis, molecular marker assisted breeding, etc., greatly reducing breeding costs.

The invention provides a dual-cavity tracheal catheter selection method and system based on multi-modal data fusion. The method comprises the steps that basic information, neck ultrasonic images and chest CT data of audiences are collected; performing data fusion and preprocessing on the basic information, the neck ultrasonic image and the chest CT data to obtain multi-modal fusion data; a double-cavity tracheal catheter analysis result is obtained through deep learning; integrating the multi-modal fusion data and the double-lumen tracheal catheter analysis result to obtain a double-lumen tracheal catheter recommendation result; new tracheal intubation data are collected, and the new tracheal intubation data are used for continuously correcting and optimizing the double-cavity tracheal catheter recommendation result. According to the method, the double-cavity tracheal catheter is selected by adopting artificial intelligence and multi-modal fusion data, so that the purpose of correctly selecting a proper double-cavity tracheal catheter is achieved, and the selection accuracy of the double-cavity tracheal catheter can be effectively improved.

This application discloses an intelligent selection method for manufacturing process templates based on field matching and directed graph judgment, comprising: acquiring key attribute information of the task to be produced; traversing the process template library, comparing the types and quantities of input fields provided by the task with the predefined required fields of each template, and filtering out a set of candidate templates with matching fields; when the number of candidate templates is greater than one, acquiring a preset directed graph corresponding to each candidate template, wherein the directed graph contains judgment nodes and directed paths terminating at template nodes; solving for the output values ​​of each judgment node in the directed graph based on the key attribute information, and determining the template activation status based on the output values ​​of all judgment nodes on the directed path; and finally determining and outputting a unique process template from the set of candidate templates. This invention achieves automatic and accurate selection of process templates through a dual filtering mechanism of field matching and directed graph logical judgment, improving the efficiency of process preparation and the flexibility of rule configuration.

The invention provides a transformer core multipoint grounding equivalent circuit and a fault processing method, and relates to the technical field of power transformers. The equivalent circuit comprises a primary side equivalent branch, a secondary side equivalent branch, a fault equivalent branch, a current-limiting resistor and an insulation resistor, one ends of the primary side equivalent branch and the secondary side equivalent branch are connected with the ground, and the other ends are connected with the ground through insulation resistors; one end of the fault equivalent branch is connected with the ground through a current-limiting resistor, and the other end is connected with the ground through an insulation resistor; and the fault equivalent branch is equivalent to a secondary winding and is used for equivalent induction electromotive force generated by multi-point grounding of the iron core. The multi-point grounding condition of the transformer core can be simulated, and the selection accuracy of the resistance value of the current-limiting resistor is improved.

This utility model discloses a machine vision-based intelligent sorting and quality inspection device for jujubes, including an electric conveyor belt for feeding, with a machine vision-based sorting platform installed at one end of the conveyor belt. When the device is in operation, after the feeding mechanism feeds the jujubes into the inspection port, the pressure sensor inside senses the pressure value. This allows for both weighing the jujubes and triggering the inspection mechanism. Specifically, the servo motor inside the machine vision-based sorting platform starts, and with the encoder's angle control feedback function, it controls the drive turntable to rotate 90 degrees each time, sequentially passing the jujubes through a color CCD camera, a near-infrared camera, and a 3D structured light camera. This enables the detection of surface color and defects, analysis of internal sugar and moisture content, and acquisition of three-dimensional size and shape data, thereby improving the subsequent sorting accuracy.

This invention belongs to the field of biotechnology-assisted breeding and discloses a SNP marker for identifying resistance to bacterial soft rot in cucumber and its application. The SNP molecular marker of this invention is located at physical positions 13,925,944 bp on cucumber chromosome 2. Cucumber materials with a base of G at this site are resistant to bacterial soft rot, while cucumber materials with a base of A at this site are susceptible to bacterial soft rot. Using the SNP marker provided by this invention, the resistance of cucumber plants to bacterial soft rot can be rapidly and accurately identified during the seedling stage, enabling high-throughput screening of a large number of breeding materials. This method has advantages such as high detection efficiency and no limitation by environmental conditions, significantly improving the selection efficiency in disease-resistant breeding, shortening the breeding cycle, and providing an effective tool for marker-assisted selection breeding of cucumbers resistant to bacterial soft rot.

The present invention belongs to the technical field of molecular genetics, and specifically relates to a SNP site related to the fine wool rate of fine wool sheep and its application. The SNP molecular marker described in the present invention is located at the A / G mutation of the 60455332nd nucleotide site on chromosome 5 of the international sheep reference genome Oar_v4.0 version. The present invention also provides the use of a reagent for detecting the above-mentioned SNP site in detecting the fine wool rate trait of fine wool sheep or in molecular marker-assisted breeding of fine wool sheep, which has great application value in fine wool sheep variety screening, variety identification or molecular marker-assisted breeding; it is used for early breeding selection, shortening the generation interval, accelerating the breeding process, saving a lot of breeding costs, and has broad market prospects.

The present invention relates to the field of molecular marker technology, and specifically discloses a pig whole genome low-density 5K SNP chip and its application. The pig whole genome low-density 5K SNP chip provided by the present invention includes a SNP molecular marker combination for pig genotyping, and the SNP molecular marker combination consists of 5603 SNP molecular markers, and the SNP molecular markers are shown in Table 1. The SNP chip or molecular marker combination provided by the present invention can be applied to multiple fields such as pig whole genome breeding value evaluation, cluster analysis, molecular marker assisted breeding, etc., greatly reducing breeding costs.

The application provides a drilling bit optimization method and device based on data analysis, and relates to the technical field of well drilling analysis. The method comprises the following steps: obtaining the use parameters of a drilling bit in a target stratum; calculating the average rate of penetration and the average footage of each drilling bit according to the rate of penetration and the footage in the use parameters; taking the average rate of penetration and the average footage as the horizontal coordinate and the vertical coordinate of a Cartesian coordinate system respectively, and marking the average rate of penetration and the average footage of each drilling bit in the coordinate system; selecting different reference indexes according to the well depth data of the target stratum, and partitioning the coordinate system; and selecting the drilling bit model in the coordinate system as the optimized drilling bit model according to the partitioning condition. The application has sufficient theoretical basis, is simple and easy to use, can greatly improve the scientificity and rationality of drilling bit selection in the drilling industry, has high drilling bit selection accuracy, can greatly improve the drilling efficiency, and reduces the drilling investment cost.

The invention discloses an alternative MRI (Magnetic Resonance Imaging) construction method based on three-dimensional head scanning and a related device, and the method comprises the steps: carrying out the preprocessing of an image of an MRI database, obtaining head MRI data, and constructing an MRI head three-dimensional model; acquiring three-dimensional head scanning data, and performing point cloud registration and shape similarity matching by using the three-dimensional head scanning data and the MRI head three-dimensional model; and selecting the MRI head three-dimensional model with the highest matching degree with the three-dimensional head scanning data as a substitution model according to the point cloud registration and shape similarity matching result. The method has the advantages of being convenient to operate, low in cost, low in requirement for subjects and the like, a set of automatic retrieval and substitution generation process from three-dimensional scanning to MRI is constructed, the method can be directly used for TI electrode layout, simulation and stimulation navigation, and therefore the application range of the TI technology in clinical and scientific research environments is remarkably widened.

The present application relates to the technical field of plant molecular breeding, and particularly relates to a Kasp marker PH-03-KASP-106 closely linked to corn plant height and application thereof, the marker comprises a single nucleotide polymorphism SNP site located at the position 163964821 of the 3rd chromosome of corn Chr3 and a KASP molecular marker primer set, PCR amplification of corn genomic DNA is carried out through the specific primer set, and the TT dwarf, CC high rod genotypes are distinguished according to fluorescence signal differences. The present application can be used for early identification, screening and molecular marker assisted breeding of corn plant height traits, can improve the efficiency of dwarf corn germplasm breeding, enhance the selection accuracy, clarify the breeding direction, and is simple in operation, high in cost-effectiveness, and suitable for corn breeding research and production practice of different scales.