20results about How to "Precise definition" patented technology

The invention discloses a drainage basin ecological safety monitoring method and system based on big data. The method comprises the steps of data acquisition, data preprocessing, drainage basin ecological environment monitoring, drainage basin ecological system monitoring, hyper-parameter optimization and drainage basin ecological comprehensive monitoring. The invention belongs to the technical field of ecological safety information processing, and particularly relates to a drainage basin ecological safety monitoring method and system based on big data, according to the scheme, ecological environment monitoring and ecological system monitoring are creatively and deeply fused, and the comprehensiveness and accuracy of drainage basin ecological safety monitoring are improved; adjacent domain similarity, a standard deviation adjustment distance and a distribution coefficient are introduced, a selection process of a clustering center is optimized, and the technical problem that a watershed ecosystem monitoring result is not accurate enough is solved. The algorithm for obtaining the optimal parameters of the monitoring model is improved by adopting the dynamic adaptation factors, the opposite individuals and the individual symbiotic update, the optimal parameter combination is obtained, the accuracy of the model output result is improved, and the drainage basin ecological environment monitoring result is more accurate.

The invention discloses a photovoltaic module I-V feature extraction method based on linear regression, and the method comprises the steps: carrying out the preprocessing of the current and voltage data of a photovoltaic module, and generating an equivalent I-V curve with a plurality of voltage data points at equal intervals through a smooth spline method; establishing a judgment criterion of change points according to noise parameters of the I-V curve, identifying the change points generating steps, and decomposing the equivalent I-V curve into a plurality of single-step I-V curves based on the searched change points; linear regression processing is carried out on each single-step curve, only continuous data points with small slope change are adopted in the process, then the selected linear data points are used for correcting a nonlinear area, a complete linear model is obtained, and corresponding I-V feature values are calculated; and finally, carrying out repeatability test on the extracted I-V features by adopting a resampling method. According to the method, the features are extracted from the I-V curve through the methods of smooth spline, linear regression and the like, the repeatability of extraction of each I-V feature is detected, and the method has high reliability and accuracy.

The invention discloses a connectable multi-configuration lattice structure topological optimization method, system and device based on transition unit cells and a storage medium. The method comprises the steps that interpolation is conducted on rod diameters of M kinds of basic unit cells to obtain the transition unit cells; respectively calculating equivalent elastic matrixes of the M basic unit cells and the transition unit cells by adopting a homogenization method; according to the relative densities and the equivalent elastic matrixes of the basic unit cells and the transition unit cells, respectively calculating the relative densities and the elastic matrixes of the units by utilizing a multi-material interpolation formula; constructing a topological optimization model of the connectable multi-configuration lattice structure based on the transition unit cell, and optimizing the sensitivity of the target function and the volume constraint to the design variables in the design domain based on the topological optimization model until the topological optimization model converges; in the optimization process, a moving asymptote method is adopted to update design variables; and obtaining an optimized structure according to a design variable corresponding to the converged topological optimization model. According to the invention, the problem of connectivity between microstructures is solved by using the transition unit cells, the geometric configuration of the basic unit cells does not need to be limited, and the mechanical potential of the structure is improved.

The invention discloses a reactor cabin structure internal pressure-bending combined load test device and a test method thereof.The device comprises a test module, the test module comprises a test section, a first transition section and a second transition section, and the test section is provided with a first pressure cabin and a second pressure cabin; the internal pressure loading module comprises a water tank and a pressure pump; the bending loading module comprises a first vertical loading mechanism and a second vertical loading mechanism; the bottom supporting module comprises a first supporting mechanism and a second supporting mechanism; and the measuring module comprises a first pressure sensor, a second pressure sensor and a pressure gauge. According to the invention, the internal pressure loading module and the bending loading module are used for simulating the load of the pressure chamber structure under dual accident conditions, the structural response under the condition of superposition of different internal pressure loads and different bending loads is known, and the safety and reliability of a chamber section model of the pressure chamber structure under the accident conditions are analyzed.

The invention discloses a method for constructing a human marrow paraffin tissue space transcriptome sequencing map, which comprises the following steps of: obtaining high-quality space transcriptome data from a marrow paraffin section of an AML (acute myeloid leukemia) patient, and then integrating the space transcriptome with scRNA-seq and histopathology. Relatively complete transcriptome information is still preserved after the bone marrow specimen is subjected to better decalcification treatment, and meanwhile, higher-quality slicing treatment can be performed on the embedded paraffin tissue, so that very complete bone marrow space transcriptome sequencing data is obtained. Then, the cell type of each detection site in the bone marrow space transcriptome map can be accurately defined by integrating bone marrow single cell sequencing data and pathological morphology annotations, and subsequent analysis is carried out.

The invention discloses a preparation method of a thin-wall pipe. The preparation method comprises the following steps: establishing a pipe model of a pipe mold for preparing the thin-wall pipe; simulating the flowing condition of the polymer in the pipe model by using the pipe model, and optimizing the parameters of the pipe model according to the flowing condition of the polymer in the pipe model; extruding the polymer into the pipe model by using the initial extrusion parameter for simulation, and pulling the polymer out of the pipe model by using the initial traction parameter for simulation to obtain a test pipe; optimizing the initial extrusion parameter and the initial traction parameter according to the test pipe to obtain a target extrusion parameter and a target traction parameter; and preparing the thin-wall pipe according to the target extrusion parameter, the target traction parameter and the pipe model. The parameters of the pipe model are optimized through the simulation technology, it can be ensured that the polymer flows more evenly and stably in the pipe model, and the product reliability of the prepared thin-wall pipe is improved.

The invention discloses a river regulation data analysis management system and method based on artificial intelligence, and relates to the field of intelligent management, and the system comprises a main control module which is used for the general control of the data stream editing and instruction transmission of each function module; the water layer division module is used for defining and dividing a water layer of a target water area, dividing the water area into a plurality of independent water layers according to hydrological characteristics, and distributing a unique identifier for each water layer; the silt collection module is used for acquiring obstruction accumulation data in a specified water layer through a sensor network; the floating acquisition module is used for acquiring floating object coverage data in a specified water layer; fusion analysis is carried out on multi-dimensional and real-time collected data by using an artificial intelligence deep learning algorithm, and the deterioration risk probability of a specific period in the future can be output, so that a management department can identify a high-risk area and intervene in advance before a water quality or sedimentation problem actually occurs or deteriorates, and then the logic of river regulation is assisted to be changed.

The invention aims to provide a log data standardization method. Firstly filtering all the collected data; obtaining the direct information as basic original information according to an analysis rule; then, the direct information is classified and marked according to preset dimensions, so that the direct information is divided into a plurality of types, an information set composed of the dimensions serves as a tuple, and an event can be abstracted on the whole; further performing association marking on each tuple information according to a preset association rule, and associating events with internal or potential association with a preset knowledge base, so as to obtain indirect information without response in the events; finally, the event information is divided into direct information, tuple information and indirect information, and various information sources are provided for subsequent data analysis. Useful event information can be extracted from mass data, and events can be defined more accurately while data standardization is achieved.

This application provides an ion implantation method for a semiconductor structure, relating to the field of semiconductor technology. The semiconductor structure ion implantation method includes: providing a substrate having a deep trench; forming a first positive photoresist layer on the surface of the substrate; performing a first exposure using a first exposure dose to expose the first positive photoresist layer at the bottom of the deep trench; forming a second positive photoresist layer on the surface of the first positive photoresist layer; performing a second exposure using a second exposure dose less than the first exposure dose; performing a first development on the first and second positive photoresist layers to form an implantation window; and performing ion implantation on the substrate through the implantation window. This semiconductor structure ion implantation method addresses the problem of achieving precise ion implantation at the bottom of deep trenches in semiconductor devices.

The invention discloses a method and a terminal for locating a variable reference position in a PLC programming software, which obtains variable information in a ladder diagram instruction, wherein the variable information includes a variable name; stores the logical position of the ladder diagram instruction in a position set corresponding to the variable name; sets a corresponding position set for each variable name, and if the ladder diagram instruction includes a corresponding variable name, stores the logical position of the ladder diagram instruction in the position set corresponding to the variable name, so that finally all logical addresses corresponding to the variable name and using the variable can be counted; centrally manages the logical positions of the variables and the ladder diagram instructions that reference the variables, so that all ladder diagram instruction code segments related to specific variables can be quickly and accurately located, thereby improving the maintenance efficiency of the code.

The invention provides an ICD management method, system and device based on a model and a medium, and relates to the field of interface management, and the method comprises the steps: extracting and defining a function interface, a physical interface, a relation interface, an energy interface and a message interface based on a demand-driven RFLP architecture model; the method comprises the following steps: defining an airborne system modeling language ASML, integrating the ASML into a modeling tool, constructing a system architecture interface model, introducing meta-models into interfaces of different hierarchies as a core framework, and creating an interface definition template; based on the meta-model and a pre-constructed ICD data dictionary, defining an interface verification rule, and monitoring and verifying interface data; and performing version control on the model-based ICD management process, generating and updating a baseline version at a project milestone node, and outputting an ICD document in a standard format. According to the method, the standardization level, design efficiency and quality of airborne system ICD design are improved, and technical guarantee is provided for standardized design and management and control of complex system interfaces.

The application discloses a composite film material for a circuit board process, a preparation method of the composite film material, and a circuit board selective hole plugging method. The composite film material comprises a metal layer, a photosensitive layer arranged on a first surface of the metal layer, and a resin bonding layer arranged on a second surface of the metal layer. The resin bonding layer comprises an alkali-soluble resin and is used for bonding with the circuit board. The application uses the strong support of the metal layer and a specific formula design of the resin bonding layer to ensure that the film material can be cleaned and removed without residues by an alkaline solvent after experiencing an extreme heat process of 150 DEG C to 220 DEG C, and the yield and surface flatness of a selective hole plugging process of a high thickness-diameter ratio circuit board are significantly improved.

The invention relates to the technical field of generator set early warning, and discloses a generator set early warning method and system based on DCS data. The method comprises the steps that real-time data of DCS process variables of the generator set are collected, data subsets are divided according to operation conditions, and a dynamic self-adaptive reference contour is established for each subset; an instantaneous anomaly index is quantified by calculating a multi-dimensional distance between real-time data and a reference contour, and an accumulated situation index reflecting anomaly persistence is constructed. And identifying an early performance degradation mode by analyzing the growth slope and curvature change of the index, and accordingly, matching an early warning strategy and dynamically updating the reference contour. And finally, a comprehensive health degree score is generated, and self-adaptive early warning threshold adjustment is realized. According to the method, the problem of false alarm of a fixed threshold value under a variable working condition is effectively solved through the dynamic reference model, sensitive capture of early performance degradation symptoms is realized through deep analysis of an abnormal trend, and the accuracy and timeliness of early warning are improved.

This invention provides a reverse design method for wharf foundation piles based on multi-objective optimization, belonging to the field of civil engineering structural design technology. In the composite load space composed of vertical, horizontal loads, and bending moments, this invention uses a shape parameter vector containing dimensions and coupling coefficients to define and parameterize the target failure envelope. By performing numerical limit state analysis and fitting on design samples, the actual shape parameters are obtained. This is used to train a machine learning model that can quickly predict the shape of the corresponding envelope from the design parameters. Using the difference between the predicted shape and the target shape as the optimization objective, and combined with construction costs, the model is used to evaluate candidate designs. A multi-objective optimization algorithm is used iteratively to obtain a set of design parameters that optimally balance performance and cost. The selected design is verified through high-precision simulation. After confirming that its actual performance matches the target, the parameters and performance information are integrated into a standard digital file to directly drive automated construction.

The invention discloses a device for supporting complex system demand integrity modeling and evaluation, and relates to the technical field of system engineering, and the device comprises demand modeling, demand integrity evaluation, design process modeling, demand and design process ontology integration, and demand traceability expression and evaluation. The demand modeling module comprises demand entry model construction and demand content constraint definition; the main function of the demand modeling module is to create a demand model based on the proposed demand integrity expression rule and constraint, and ensure the integrity of demand content in the created demand model; in the demand modeling module, a demand content constraint definition sub-module provides constraints for a demand entry model construction sub-module, and in the demand modeling module, a demand engineer uses an entry model construction technology to decompose high-level demands into specific and operable entries, so that deep understanding of the demands is promoted, and the demand modeling efficiency is improved. And each demand is ensured to be accurately defined and recorded.

The invention provides a knee joint MRI image classification method based on artificial intelligence, and relates to the technical field of image processing, and the method comprises the steps: carrying out the preprocessing of a knee joint MRI image; performing affine registration on the preprocessed knee joint MRI image and a reference image to obtain a registration MRI image aligned with the reference image; performing region boundary extraction on the registered MRI image, determining boundary feature points on a region boundary, and performing region segmentation on the MRI image according to the boundary feature points; inputting a plurality of regional images obtained by segmentation into a multi-target distinguishing model, and performing category marking on the regional images; and comparing each area image marked with the category with the standard area images of different grades of the corresponding category, constructing a pixel difference matrix, calculating the similar focusing degree of each pixel difference matrix, and judging the grade of the area image based on the similar focusing degree.

The invention discloses a cluster task generation method and device based on unmanned aerial vehicle command and control software, and the method comprises the steps: generating a task type layout file according to the data of a cluster task and a task type rule; and constructing a task model containing all task types, and adjusting a task execution sequence through the task execution numbers. Generating a set of initial task data according to the task type, and creating an internal protocol data subset; and updating the multi-dimensional array of the internal protocol data subset according to the task type and sequence number of the task model, integrating the multi-dimensional array into the initial cluster task data set, and cleaning empty elements to form a final cluster task data set. And generating a task list according to the task execution purpose, and executing in sequence. The problem that in the task execution process, when the unmanned aerial vehicle encounters the environment change, the task cannot be re-planned in time, and the task fails is solved.

The invention provides a visual and inertial odometer integrated navigation method, device and equipment and a medium. The method comprises the following steps: determining a state vector of visual / inertial odometer integrated navigation; constructing a visual / inertial odometer integrated navigation system model; constructing an observation model of a vision / inertial odometer integrated navigation system based on pure pose constraint; kalman filtering is completed according to the system model and the observation model of the visual / inertial odometer integrated navigation system, attitude, speed and position information of a filtered carrier is output, and the visual / inertial odometer integrated navigation filtering observation model is deduced again through a pure pose constraint theory. The new observation model does not contain three-dimensional feature information any more, so that null-space mapping and three-dimensional reconstruction processes are not needed any more, the problem of model inconsistency existing in multi-state constraint Kalman filtering and the influence of errors introduced by inaccurate three-dimensional reconstruction are avoided, and the integrated navigation precision is improved.

The invention discloses a non-uniform data clustering method based on convex hull optimization, and the method comprises the steps: S1, randomly selecting a clustering center in a data set, and carrying out the initial clustering of the data set based on Euclidean distance; wherein one clustering center corresponds to one cluster; s2, discarding data points, namely discarded points, far away from the centroids of the clusters according to a discarding probability formula, and re-updating the centroid position of each cluster; s3, calculating a convex hull for unabandoned data points of each cluster, and defining the convex hull as a cluster boundary; s4, recalculating the distance from the abandoned point to each clustering boundary, and dividing the abandoned point to a cluster corresponding to the nearest clustering boundary; and S5, repeating the steps S2 to S5 until all clusters tend to be stable. According to the method, high-dimensional data and complex data distribution can be effectively processed, and the clustering boundary can be accurately divided by calculating the convex hulls of the data points, so that the clustering accuracy and efficiency are improved.

This invention discloses a method and system for monitoring watershed ecological security based on big data. The method includes data acquisition, data preprocessing, watershed ecological environment monitoring, watershed ecosystem monitoring, hyperparameter optimization, and comprehensive watershed ecological monitoring. This invention belongs to the field of ecological security information processing technology, specifically a method and system for monitoring watershed ecological security based on big data. This solution creatively integrates ecological environment monitoring and ecosystem monitoring, improving the comprehensiveness and accuracy of watershed ecological security monitoring. It introduces adjacency domain similarity, standard deviation adjustment distance, and allocation coefficients to optimize the selection process of cluster centers, solving the technical problem of inaccurate watershed ecosystem monitoring results. It employs dynamic adaptation factors, opposing individuals, and individual symbiotic updates to improve the algorithm for obtaining optimal parameters of the monitoring model, obtaining the optimal parameter combination, improving the accuracy of the model output results, and making the watershed ecological environment monitoring results more precise.