24results about How to "Accurate data analysis" patented technology

The invention relates to the technical field of Internet of Vehicles, in particular to an Internet of Vehicles federal semi-supervised learning method and system, and the method comprises the steps: in each iteration, a vehicle client firstly generates a pseudo label of unlabeled sample data, then carries out the training of a local model, and uploads the trained model to a server; and after the server side aggregates the local models of all the vehicle clients, the local models and the supervision model trained by using the labeled sample data are aggregated again to obtain a global model of the current iteration, and the global model continues to be used for training the local model in the next iteration. According to the invention, the model training efficiency is improved, the real-time performance and adaptability of the system are further improved, and the coping ability of the vehicle in a complex and changeable traffic environment is enhanced.

The invention discloses an ABS control strategy optimization method and system based on indirect tire pressure monitoring. The ABS control strategy optimization method comprises the following steps that S1, vehicle driving state information is collected in real time; s2, the driving state information is processed, and the dynamic behavior of the tire is recognized; s3, estimating the tire pressure state of the wheel; s4, the braking risk in the current driving state is evaluated; s5, ABS control parameters are generated; s6, generating a control instruction and transmitting the control instruction to an ABS actuator; s7, adjusting the pressure of the hydraulic system; s8, evaluating the validity of the ABS control parameters, and adjusting the ABS control parameters based on a feedback result; and S9, outputting and displaying the working state information and the tire pressure information of the ABS. According to the ABS control strategy optimization method and system based on indirect tire pressure monitoring, the control strategy can be dynamically adjusted according to the actual operation state, and the braking performance and safety are improved.

The present invention discloses a data security analysis system based on data mining, which specifically relates to the technical field of data mining, and includes a log file acquisition module, a preprocessing module, a data analysis module, and a human-computer interaction module. The present invention obtains the first safety range and the second safety range of the target log file detection through the log file acquisition module; the preprocessing module performs preprocessing operations through the first safety range and the second safety range to obtain the first safety keyword group and the second safety keyword group respectively; the data analysis module obtains the first safety degree text corresponding to the first safety range through the first safety keyword group according to the data mining intelligent model, and constructs the third safety keyword group through the preferred keywords; according to the data mining intelligent model, the second safety degree text corresponding to the second safety range is obtained through the third safety keyword group, and is fed back to the management personnel; when the same safety problem is deeply detected, the analysis data is made more accurate and fast.

The invention provides a live ammunition shooting visual instrument which comprises a mounting shell provided with a connecting structure used for being connected with a gun. The camera shooting assembly is arranged on the mounting shell and can collect target position image information; the wireless transmission module is arranged in the installation shell and used for receiving and transmitting the target position image information, the target position image information is collected in real time through the camera shooting assembly, the information is rapidly transmitted to a receiving end through the wireless transmission module, the automatic target scoring function is achieved, compared with manual target scoring, the time for going back and forth to the target position is saved, and the target scoring efficiency is improved. The shooting assembly can record the shooting result of each time in detail, the shooting result comprises the position, distribution and other information of bullet holes, accurate data analysis and feedback are provided for a trainee, and a shooter and a coach can know the aiming condition and the shooting result in real time through the device during training; and soldiers can be quickly and efficiently assisted in improving and mastering the aiming and shooting essentials, and a large amount of manpower and bullets are saved.

The utility model discloses a micro-melting and sputtering pressure sensor integrated bonding wire plate which comprises three interface holes, the three interface holes are arranged on a circuit board, a pressure sensor bonding pad is attached to the circuit board, the pressure sensor bonding pad is provided with a pressure sensor bonding wire area, and the pressure sensor bonding wire area is provided with a pressure sensor bonding wire. The pressure sensor bonding wire area comprises a sputtering film pressure sensor bonding wire area, a glass micro-melting pressure sensor bonding wire area and a middle lead hole; the middle lead hole is arranged between the sputtering film pressure sensor bonding wire area and the glass micro-melting pressure sensor bonding wire area, and a lead bonding point is arranged in the pressure sensor bonding wire area. According to the utility model, the bonding wire plates of two types of sensors are combined and designed to one universal platform, so that the complexity of product design is remarkably simplified, the material cost is reduced, the production cost is also reduced because only one type of bonding wire plate needs to be manufactured and stored, and the same production line can be used for the two types of sensors, so that the production efficiency is improved. And the time for replacing tools and adjusting equipment is shortened, so that the overall production efficiency is improved.

The utility model provides a wave recording isolation sampling circuit which comprises a sampling assembly, an isolation module, a signal conditioning module and a micro-control unit. An ADC module is arranged in the micro-control unit, the sampling assembly is connected to a DC power supply of the feeder terminal and is electrically connected with the isolation module, the signal conditioning module is electrically connected with the isolation module, and the signal conditioning module is electrically connected with the ADC module in the micro-control unit; the isolation efficiency of the system is improved, the improvement is favorable for improving the safety of the system, the sampling accuracy is also effectively improved, and the recording data of the generated recording file can be ensured to be more reliable, so that more accurate data analysis and fault diagnosis are facilitated.

The invention relates to a monitoring point optimization method and device fusing a GIS technology and face recognition, and a terminal. According to the method, the GIS technology and the face recognition technology are adopted to realize grid management of a monitoring area; data is provided for abnormal track line identification through equipment parameter information and monitoring data of monitoring equipment; according to the monitoring data and the snapshot data, a track speed and an abnormal track line are analyzed, a monitoring blind area in a monitoring area is identified, virtual point location construction is carried out on the abnormal track line, a construction recommendation numerical value is obtained, a monitoring range map after accurate monitoring point location construction optimization is obtained, the coverage rate and monitoring efficiency of a monitoring network are remarkably improved, and the monitoring efficiency of the monitoring network is improved. The monitoring blind area is effectively reduced, and the construction and operation cost of the monitoring system is reduced; the technical problems that traditional monitoring point location layout depends on artificial experience and on-site investigation, the efficiency is low, and it is difficult to ensure that a monitoring network can comprehensively cover a key area, and consequently resources are wasted are solved.

The present invention relates to the field of image processing technology, and in particular to a gastric mucosa image analysis method and system for Helicobacter pylori detection. The method comprises the following steps: acquiring gastric mucosa image data; performing image segmentation on the gastric mucosa image data to obtain gastric mucosa image segmentation data, and performing regional characteristic processing based on the gastric mucosa image segmentation data to obtain regional characteristic data; performing image enhancement on the gastric mucosa image data based on the regional characteristic data to obtain gastric mucosa image enhancement data; acquiring region of interest data, and simulating the gastric mucosa image enhancement data based on the region of interest data to obtain region of interest simulation data, so as to perform gastric mucosa image analysis operations. The present invention provides more accurate image analysis data by performing more detailed processing operations on gastric mucosa images.

The invention discloses a method for counting the arcing position and time of a low-clutter antenna by using machine learning, relates to the field of magnetic confinement fusion, and realizes continuous recording of the change process of the arcing state of the low-clutter antenna by observing bright spots generated by arcing through a visible camera when a magnetic confinement fusion device runs. A large number of different arc states are recognized and classified, a corresponding database is established, the database serves as input in a deep convolutional neural network analysis program, different arc starting states are counted, learned and classified, the results of manual recognition and program recognition of the arc starting states are compared, and the accuracy of program calculation is verified while calibration is conducted. And based on a program identification result, a machine learning-DBSCAN algorithm is further adopted to carry out normalized clustering processing on the classified images for different arcing states, and statistics is carried out on the duration time of different arcing positions on the low-clutter antenna. According to the invention, real-time identification of the arcing state of the low-clutter antenna can be realized, and the arcing position and duration of the low-clutter antenna can be counted at the same time.

The invention discloses a repetitive peak isolation voltage formulating method and system for an optical isolation device, and the method comprises the steps: carrying out the statistics and distribution parameter estimation of the end-of-life time data of the optical isolation device through Weibull distribution, and obtaining a fitting probability graph; based on the fitting probability graph, obtaining failure time of specified failure rates under different test voltages; obtaining a life time prediction map of the optoisolator under different specific voltages based on the failure time of the specified failure rate under different test voltages; and based on the life time prediction map of the optical isolator under different specific voltages, analyzing the life of the device under the specific repeated peak isolation voltage. The invention provides a data analysis technology to obtain an accurate VIORM value and predicted life, so that life prediction of the optical isolator in different scenes is more accurate.

The utility model discloses a 3D detection device for height detection of mobile phone shell side, including base and install two longitudinal guide rails on the upside of base, the upside of two longitudinal guide rails all is provided with the stage to lift the product, the upside of base is provided with the transverse guide rail, the front side of transverse guide rail is provided with electric cylinder, the downside of electric cylinder is provided with line sweep head, the upside between two longitudinal guide rails is provided with the limit board, the downside of two limit boards and respectively close to left and right sides all are provided with the supporting plate, the upside of two supporting plates all is provided with triangular prism, the inside of two stages all is provided with the lift cylinder to lift the product and move up and down, through the rubber sleeve of triangular prism left and right sides, reduce the vibration amplitude of transmission to triangular prism, when the reflection of triangular prism to mobile phone shell, the picture reflected is more stable, clear.

The invention discloses a fault location method and system for sodium ion battery energy storage based on photovoltaic power supply, and relates to the technical field of fault location of sodium ion battery energy storage, comprising the following steps: obtaining impedance measurement accuracy data and impedance measurement stability data of EIS fault location analysis under prepared samples with different electrode surface roughnesses; constructing a sample preparation evaluation model based on a convolutional neural network; constructing an electrode surface roughness-EIS fault location performance display model; according to the experimental preparation restrictions and preset demand restrictions of EIS fault location, constraining the electrode surface roughness-EIS fault location performance display model; analyzing to obtain the balanced roughness of the electrode surface; the application is used to solve the problem of unbalanced electrode surface roughness, which will lead to an increase in contact resistance, thereby affecting the accuracy of electrochemical impedance measurement, and failing to truly reflect the interface state and performance of the battery.

The present invention discloses a financial data analysis and prediction system based on artificial intelligence, including a financial data collection module, a financial data outlier detection and modification module, a financial data analysis module, a financial data prediction module, and a user interaction module. Also disclosed is a financial data analysis method based on artificial intelligence, which uses a financial data analysis model to collect and clean financial data from a financial data source to obtain a data set; uses an optimized lonely forest algorithm to process data points in the data set, marks and modifies outliers, and integrates to obtain an updated data set; the updated data set is subjected to standardization processing, and then analyzed using an enhanced autoregressive difference moving average model to output a comprehensive feature vector; the financial data prediction model predicts the comprehensive feature vector to obtain a predicted value, and dynamically adjusts the prediction error threshold. The technical solution of the present invention can improve the accuracy of the analysis results, the prediction accuracy, and can ensure long-term use effects.

This invention discloses a dynamic user profile update method based on multimodal data, relating to the field of user modeling technology. The method includes: acquiring the collaborative analysis software of each software in the user's device; obtaining the association weight based on the association filtering value of the collaborative analysis software; acquiring status update words and updating the user's profile based on the collaborative analysis software of the updated reference software and the association weight of the collaborative analysis software. This invention addresses the problem in existing dynamic user profile update methods that lack analysis of multimodal data generated by users based on user software usage data. This results in the inability to effectively acquire dynamic profile data related to the user's immediate interests and needs, leading to inaccurate user profiles and a loss of dynamism after data processing.

The invention provides an augmented reality data labeling tool, and relates to the field of data analysis and computation.According to the augmented reality data labeling tool, the urban three-dimensional model road environment color needing to be labeled is converted from RGB to HSV through a computing module, then the computing module computes the hue most obviously compared with the hue value of Ha in a color circle through Hb = (Ha + 180 degrees) mod360 degrees, and the hue is compared with the hue value of Ha through the Hb = (Ha + 180 degrees) mod360 degrees; the method comprises the following steps: acquiring a hue value with the strongest contrast with the environment color of a road needing to be marked in a city three-dimensional model through a GUI (Graphical User Interface) module, calculating E = Hb / Ha by a calculation module, judging that E is more than 1.5 and less than or equal to 3, judging that the color difference is obvious if the judgment is passed, then converting the hue value with the strongest contrast into RGB (Red, Green, Blue) from HSV (Hue, Saturation and Value) by the calculation module, and transmitting the RGB value with the strongest contrast to the GUI module by a control center, the GUI module modifies the corresponding marking line color object, the color of the marking line is automatically adjusted through the algorithm so as to improve the visibility and the identification degree, and meanwhile it can be ensured that the calculated line color is obviously different from the environment color of the road needing to be marked in the urban three-dimensional model.

This disclosure provides a filtered air outlet device and an air handling unit. Multiple temperature sensors are distributed on the filter of the filtered air outlet device, enabling real-time capture of the outlet air temperature in different areas, forming multi-point temperature monitoring. The air guide assembly is divided into multiple sub-air guide zones, each equipped with an independent air guide vane group and a corresponding temperature sensor. The control device can adjust the air guide direction of the corresponding air guide vane group based on the real-time temperature differences in each sub-air guide zone. Through dynamic regulation of local airflow, the outlet air temperature in different areas is balanced, effectively eliminating local temperature differences and improving overall airflow uniformity. Uniform outlet air temperature avoids local overheating or undercooling, improving the user comfort of the air handling unit equipped with this filtered air outlet device. This disclosure fundamentally solves the problem of uneven outlet air temperature in traditional units, providing a reliable guarantee for the efficient and stable operation of air handling units.

The present invention relates to the field of environmental monitoring technology, specifically a real-time monitoring system for ecological restoration process, the system comprising: based on remote sensing technology and ground monitoring, collecting normalized vegetation index, soil chemical composition, water quality index data, calibrating remote sensing data and ground data, adjusting sampling frequency and data resolution, and generating basic environmental data sets. In the present invention, the integration of normalized vegetation index, soil chemical composition and water quality index data improves comprehensiveness and comparability, makes data analysis more accurate, adjusts sampling frequency and data resolution to meet the needs of large-scale or complex environmental monitoring projects, and provides a high degree of flexibility. The application of time window analysis and local time series strengthens the ability to identify environmental change trends and provides a basis for decision-making. By integrating multiple model outputs, parameter settings are optimized, and the consistency and application value of predictions are improved, thereby enhancing the efficiency of project management and the practicality of scientific research data.

The invention relates to the technical field of microscopic imaging, and particularly provides a limited visual angle correction photoacoustic microscopic imaging system based on three-beam interference excitation. The limited visual angle correction photoacoustic microscopic imaging system based on three-beam interference excitation comprises a control circuit, a fixing assembly, a pulse laser, a light field modulation assembly, a light path lens assembly, an ultrasonic probe and a three-dimensional scanning platform. The exciting light field in the photoacoustic microscopic imaging system is modulated by using the light field modulation assembly, the photoacoustic signals are excited by using the stripe-shaped light field formed by three-beam interference, and the stripe-shaped light field can effectively destroy the photoacoustic effect to excite the spatial coherence between ultrasonic wave sources. Therefore, the limited visual angle defect caused by coherent cancellation in the three-dimensional reconstructed image is eliminated, and system performance indexes such as the imaging speed and the imaging depth are not affected.

The invention relates to a system for monitoring the position of a dairy cow in a milking machine. The method comprises the following steps: acquiring image data of any dairy cow channel; determining a target dairy cow entering the dairy cow channel according to the image data of any dairy cow channel; acquiring a mark on the body of the target dairy cow; after the target dairy cows enter the critical positions of the milking positions of the milking machine in sequence, identity tags of the targets are obtained according to the sequence; after it is determined that the current milking position of the milking machine completely enters the target according to the sequence, the identity tag of the target dairy cow is consistent with the position tag entering the milking position, and information of the target dairy cow at the milking position is determined; after the critical position of the milking position is determined to enter the target dairy cows in parallel or in advance, the identity tag of each target dairy cow is obtained at the same time; after it is determined that the current milking position completely enters the target dairy cow in advance, the identity label of the target dairy cow is inconsistent with the position label entering the current milking position, and the target dairy cow at the current milking position is updated to be the target dairy cow entering in advance.

The invention provides intelligent sports long jump measuring equipment, and relates to the field of long jump measuring equipment.The intelligent sports long jump measuring equipment comprises a bottom plate and a pedal, a frame plate is fixedly installed on the side face of the bottom plate, a ray trapper is arranged at the top end of the frame plate, a motor is fixedly installed on the surface of the frame plate, and a threaded rod is fixedly installed at the output end of the motor; the output end of the motor is fixedly provided with umbrella-shaped teeth A. The inner side of the bottom plate is rotationally connected with a transmission rod. According to the device, the ray trapper, the threaded rods, umbrella-shaped teeth A, a transmission rod, umbrella-shaped teeth B, a sliding groove, a moving plate, a limiting groove, a scraping plate and a spring A are arranged, when the motor works, the transmission mechanism is matched to drive the two sets of threaded rods to rotate at the same time, and then the moving plate and the scraping plate can be driven to slide in the direction of the sliding groove; and soil impurities on the surface of the pedal can be quickly scraped, so that the workload of cleaning and maintenance is reduced, and the occurrence of measurement errors can be reduced.

The invention provides a debris flow early warning and emergency processing system and method. The debris flow early warning and emergency processing system comprises a data acquisition module, a data analysis module, a mobile warning receiving module and an alarm and linkage module, the data acquisition module is used for acquiring real-time acquisition parameters of debris flow in real time and transmitting the real-time acquisition parameters to the data analysis module; the data analysis module processes the real-time acquired parameters to obtain real-time debris flow parameters, and compares the real-time debris flow parameters with a preset grade threshold to generate grade warning data; the grade warning data is transmitted to the warning and linkage module; the alarm and linkage module is used for sending debris flow first alarm information to the user terminal after receiving the first alarm signal; the grade warning data is received, and second warning information is sent to the user terminal and the mobile warning receiving module; and the mobile warning receiving module gives a warning based on the first warning information or the second warning information.

The invention relates to the field of water quality monitoring, and discloses a water quality evaluation comprehensive method and device based on a multi-source fusion sensing network and a medium, and the device comprises a floating detection node, a LoRa gateway and a cloud platform; the floating detection node communicates with the LoRa gateway through a wireless network; the LoRa gateway communicates with the cloud platform through a wireless network; the floating type detection node comprises a plurality of water quality detection sensors and is used for detecting water quality parameters and transmitting the water quality parameters to the LoRa gateway; the LoRa gateway transmits the water quality parameters to a cloud platform, and the cloud platform performs comprehensive analysis to obtain a water quality evaluation result; according to the invention, the automation degree and the data processing efficiency of water quality monitoring are greatly improved, the efficient data processing capability ensures that a user can rapidly obtain water quality information and make a decision, and the response speed of environment management is improved.

The utility model provides a self-adaptive temperature control system for mass concrete, which is novel in structural design. Comprising a water supply tank, a heating tank and a water storage tank, a return pipe is arranged between the heating tank and the water storage tank, a return water pump is arranged on the return pipe, an upper-layer cooling pipe and a lower-layer cooling pipe are arranged on the water supply tank, and an upper-layer heat preservation pipe and a lower-layer heat preservation pipe are arranged on the heating tank. The ends, away from the water supply tank and the heating tank, of the upper-layer cooling pipe, the lower-layer cooling pipe, the upper-layer heat preservation pipe and the lower-layer heat preservation pipe are all installed on the water storage tank. According to the utility model, the advanced temperature sensor, the cooling pipe and the thermal insulation pipe are laid in the concrete, the digital twin cloud platform is established to realize concrete hydration heat whole-process accurate monitoring and data analysis, the digital twin cloud platform is established to realize concrete internal and external temperature difference monitoring, and decision is made through an algorithm. Cooling and heat preservation inside and outside the concrete are achieved through intelligent water supply.

The invention provides a heterogeneous hardware accelerated supply chain enterprise carbon emission intelligent terminal. Comprising an acquisition module, a storage module, an analysis module and a network module. The acquisition module collects carbon emission data of each link on a power grid supply chain in production, storage, maintenance and scrapping processes in real time through a carbon emission gas sensor deployed on an end side; the storage module adopts an optimally designed time sequence database system, constructs a programmable network hardware read-write request processing sub-module, a query optimization sub-module based on a hardware increment materialized view and a time sequence data compression storage sub-module based on hardware, and realizes storage and management of a large amount of carbon emission time sequence data uploaded by the acquisition module; the analysis module cleans and preprocesses the data stored in the database; and the network module is responsible for safely and quickly transmitting the processed data to a cloud end or other terminal equipment. The effects of accurately and efficiently collecting carbon emission data and efficiently processing large-scale carbon emission data are achieved.