76results about How to "Realize quantitative analysis" patented technology

The invention discloses an extra-high voltage direct current transmission system sending end transient overvoltage calculation and suppression method considering the influence of multiple control links, and the method specifically comprises the steps: analyzing the operation characteristics and transient voltage influence factors of an LCC-HVDC system, and revealing that direct current is a key factor affecting the transient voltage change of a bus; the method comprises the following steps: decomposing the whole process of transient direct current under commutation failure according to direct current change characteristics in an operation curve of a direct current control system, and deducing an approximate analytical expression of the direct current after the fault occurs; respectively calculating voltage drops on equivalent resistance and reactance on the line, substituting the voltage drops into a direct current analytic expression, and deducing a quantitative calculation expression of transient overvoltage of the converter bus at the sending end; according to the transient overvoltage upper limit value, the allowable direct current minimum value is obtained, and the transient overvoltage suppression method under the commutation failure for improving the VDCOL link minimum current instruction value is provided. According to the invention, the quantitative analysis of the transient voltage is realized, and the transient overvoltage level of the converter bus at the sending end is effectively reduced.

The invention discloses a centralized management method and management system for enterprise-level work orders of a power supply system, and relates to the technical field of operation and maintenance management of the power supply system, and the method comprises the steps: collecting and preprocessing work order source data in the power supply system; constructing a work order association graph based on the work order source data, calculating a work order association degree, and forming a work order group; performing time sequence characteristic analysis on the work order group, identifying a periodic fault mode in the work order group by using a sequence mode mining algorithm, and generating a characteristic mark chain; training a dual-channel convolutional recurrent neural network by using the feature mark chain, establishing a fault prediction engine, and outputting a work order priority score table; and allocating a maintenance task instruction based on the work order priority score table, executing a maintenance task, and returning maintenance completion information to the work order association graph to complete work order whole process tracking. According to the method, the quantitative analysis of the association relationship between the work orders is realized by constructing the work order association map and combining the physical distance coefficient and the power supply path overlap ratio.

The invention relates to the technical field of neutron dose and internal pollution diagnosis, and provides a neutron dose and internal pollution diagnosis method and diagnostic agent.The method comprises the following steps that gamma ray signals are obtained at the head top and the lung of a human body through a detection device, and gamma rays are converted into electric pulse signals through the detection device; a digital multi-channel signal processing device is used for conducting signal processing on the electric pulse signals, signal processing comprises digital filtering and peak value sampling, and energy spectrum data are obtained; analyzing the energy spectrum data, and respectively obtaining a Na-24 characteristic gamma photon peak value at the top of the head of the human body and a characteristic gamma photon peak value at the lung of the human body; and according to the Na-24 characteristic gamma photon peak value obtained at the top of the head, calculating the neutron exposure dose according to a neutron dose algorithm, and according to the characteristic gamma photon peak value obtained at the lung, determining the type and activity of the internal pollution nuclide. According to the invention, accurate calculation of neutron dose and identification and activity determination of internal pollution nuclide are realized, and dual functions of neutron exposure dose and internal pollution diagnosis can be provided at the same time.

The invention relates to the technical field of intelligent sensing detection, in particular to an underground water detection system for hydraulic ring geological engineering based on data acquisition. The specific implementation process comprises the following steps: receiving a water quality sensing signal, and inhibiting a background interference domain and calculating a water quality physicochemical characteristic vector by utilizing water multiphase flow interference separation logic and comparing a physical scattering spectrum with a polarization drift spectrum; inputting the water quality physicochemical characteristic vector into a water quality physicochemical dynamic response model, executing concentration gradient variation modulus analysis, inverting a performance kinetic energy index, comparing the performance kinetic energy index with a water chemical equilibrium critical threshold, and regulating and controlling the sampling frequency; when the sudden change event is judged, generating a transient capture signal to execute locking sampling, and when the threshold is not broken through, generating a baseline water quality inspection signal to execute steady state monitoring. According to the method, the detection frequency is automatically adjusted by calculating the evolution kinetic energy index, the physical background interference is inhibited by utilizing the cross-correlation analysis between spectrums, the deviation degree of chemical equilibrium of the water body is quantified, and the fidelity of underground water monitoring data is improved.

The invention belongs to the technical field of industrial automation and intelligent manufacturing, and particularly discloses a steel analysis laboratory intelligent monitoring management system based on multi-source data fusion, which comprises a parameter monitoring module, a process judgment module, a path decision module, a deviation analysis module, a deviation propagation judgment module and a health assessment module. According to the method, the equipment operation state parameters and the material quality parameters of the steel sample in each process are collected in real time, and the preset steel quality detection standard is combined to judge whether the current process is qualified or not, so that the problem that equipment monitoring and quality detection are mutually disjointed is solved; meanwhile, the state deviation degree of the previous procedure and the real-time monitoring parameters of the subsequent procedure are subjected to fusion analysis, cross-procedure quality influence evaluation is established, then the propagation path of the quality deviation between the procedures is dynamically tracked, the process set value of the subsequent procedure is accurately adjusted based on the deviation of the previous procedure, and the quality of the subsequent procedure is improved. And beforehand intervention on the quality risk is realized.

The utility model relates to the technical field of rice processing, in particular to an internal pressure measuring and controlling device of a rice polishing machine, which comprises a polishing roll, a roll screen is arranged outside the polishing roll, a plurality of groups of support ribs are distributed on the outer wall of the roll screen, and the support ribs are fixedly welded with the surface of the roll screen. A supporting frame is arranged between every two adjacent supporting rib pieces, the two ends of each supporting frame are fixed to the corresponding supporting rib pieces through screws, a plurality of cushion blocks are distributed on the inner side of each supporting frame, strain gauge carriers are arranged on the sides, close to the roller screen, of the cushion blocks, and the supporting frames, the cushion blocks and the strain gauge carriers are fixed through screws. The construction of the internal pressure detection system of the polishing machine is completed by designing a multi-point strain gauge measurement sensor and a multi-path acquisition module; based on measurement data of an internal pressure detection system, quantitative analysis on the influence of factors such as the position of a pressing weight, the rotating speed and feeding control on the polishing pressure is achieved.

The invention provides a detection method and application of amphoteric and cationic perfluorinated and polyfluoroalkyl compounds, the method optimizes an extraction agent, can more comprehensively detect, qualitatively and quantitatively analyze amphoteric and cationic PFAS in solid samples such as biological solids, soil and the like, has high accuracy and detection precision, and can be widely applied to detection of amphoteric and cationic perfluorinated and polyfluoroalkyl compounds. The amphoteric and cationic PFAS with more unknown structures can be identified and analyzed, the blank of the prior art in the aspect of extracting and detecting amphoteric and cationic perfluorinated and polyfluoroalkyl compounds is filled, the occurrence level and fate-to-transition behavior of the amphoteric and cationic PFAS in the environment can be accurately analyzed, traditional and novel amphoteric and cationic PFAS in the environment can be identified, and the detection accuracy of the amphoteric and cationic perfluorinated and polyfluoroalkyl compounds is improved. And a scientific basis is provided for new pollutant treatment in China.

This invention relates to the field of semiconductor material testing technology, specifically a single-crystal silicon wafer slip line detection system and method, comprising: a light source module emitting light signals of different wavelengths and polarization angles to scan the silicon wafer; a silicon wafer scanning module mounting the silicon wafer under test, adjusting the position of the silicon wafer under test, and executing a scanning trajectory to scan the silicon wafer with light signals; a signal acquisition and processing module receiving the light signals transmitted through the silicon wafer under test, performing preprocessing to obtain DU values ​​at different wavelengths and polarization angles, and sending them to an industrial control computer; the industrial control computer reconstructing the strain field based on the DU values ​​using a strain field reconstruction algorithm to generate a strain field distribution map; and identifying slip lines based on the strain field distribution map using a convolutional neural network model. This solution enables non-contact, non-destructive, and high-resolution slip line detection, thereby improving detection accuracy and efficiency.

This invention discloses a method and system for identifying urban decline spaces, belonging to the field of urban planning technology. The method includes: S1. Acquiring population grid data and building area grid data of a target area for multiple consecutive years within a time interval; S2. Performing spatial alignment and standardization processing on the population grid data and building area grid data to form a standardized annual spatial database; S3. Removing grid units in the annual spatial database that do not possess effective urban activity characteristics to obtain a set of effective urban spatial grids; S4. Performing time series analysis on the effective urban spatial grid set to determine urban decline space grids; S5. Using a spatial clustering algorithm to cluster the determined urban decline space grids, dividing the urban decline space into continuous urban decline space and scattered urban decline space. This invention achieves automatic identification and classification of continuous and scattered urban decline spaces by analyzing the population and building area change trends over multiple consecutive years.

The present invention discloses a phenacetin content sampling detection method, and relates to the technical field of drug analysis and detection, the method comprises the following steps: 1, preparing a test sample and an internal standard substance into a phenacetin solution, carrying out chromatographic separation through a high performance liquid chromatograph, and using solvents: 50% methanol, the test sample solution and a proper amount of the product; 2, sample preparation: precisely measuring a test sample, precisely weighing a reference substance preparation solution, and preparing an internal standard solution, wherein an impurity positioning solution is prepared by taking a proper amount of p-aminophenetole and a proper amount of p-chlorophenylacetamide reference substances; and 3, precisely measuring 1ml of the test solution, placing the test solution in a 50ml measuring flask, diluting the test solution to a scale by using a solvent, taking 1ml of the test solution and 1ml of the impurity positioning solution, diluting the test solution and the impurity positioning solution to 20ml by using a mobile phase, and the like. The method has high precision, accuracy and linear range, the concentration of phenacetin can be detected, and quantitative analysis and monitoring of phenacetin can be realized through proper sample preparation, chromatographic conditions and standard curve preparation.

The invention belongs to a sweet orange essential oil peculiar smell identification technology, and particularly relates to an identification and identification technology for sweet orange essential oil peculiar smell substance generation caused by hot processing treatment. The invention discloses a method for determining peculiar smell of sweet orange essential oil by combining a modern molecular sensory technology with molecular docking. The method comprises the steps of sensory evaluation of the sweet orange essential oil, pretreatment of the sweet orange essential oil, GC-O-MS, smelling sensory, preliminary screening of peculiar smell related compounds, further identification of peculiar smell compounds, pretreatment of molecular docking, molecular docking and the like. The method can solve the problem of limitation of identification of the peculiar smell compound of the sweet orange essential oil in the food field and the aroma field at present.

The invention belongs to the field of petroleum geological exploration, particularly relates to a method for determining the reservoir forming time of a deep concave area of a continental facies fault lake basin, and aims to solve the problems that the reservoir forming time of the deep concave area of the continental facies fault lake basin can only be obtained in a semi-quantitative manner and the reservoir forming time of the deep concave area of the continental facies fault lake basin is easily misjudged in the prior art. The method comprises the following steps: determining an oil-containing well section, selecting sandstone with developed calcite cement as a sample, and making the sandstone into slices; determining the type of a fluid inclusion, and further determining the type of an oil inclusion; obtaining the rare earth element partition mode similarity of the slices, and confirming the cementation period of the slices; selecting slices which contain the native inclusion and are in the same cementation period, and making the slices into a circular target sample; and performing U and Pb element scanning on the circular target sample, and performing U-Pb age calculation through a graphical method to obtain the reservoir forming age of the deep concave area of the continental disruption lake basin. According to the method, quantitative analysis of the reservoir forming time of the deep concave area of the continental fault lake basin is realized, and the correctness of reservoir forming time judgment is improved.

The application provides a method for determining residual guanidium gel content in guanidium gel breaking fluid. The method comprises the following steps: sample pretreatment; preparation of guanidium gel breaking fluid series samples with different guanidium gel contents; taking the content of guanidium gel standard in the guanidium gel breaking fluid series samples with different guanidium gel contents as a response value, taking the characteristic fluorescence peak intensity and viscosity of the guanidium gel breaking fluid series samples with different guanidium gel contents after blank deduction as variables, performing regression analysis to obtain a standard curve equation of residual guanidium gel; and substituting the characteristic fluorescence peak intensity and viscosity of the pretreated guanidium gel breaking fluid sample after blank deduction into the standard curve equation of residual guanidium gel to obtain the content of residual guanidium gel in the guanidium gel breaking fluid sample to be determined. The determination method is scientific and reasonable, has high repeatability and accuracy, realizes qualitative and quantitative analysis of residual guanidium gel in guanidium gel breaking fluid, and can support efficient resource treatment of oil and gas field fracturing flowback fluid.

The present application provides a method, device, equipment and medium for detecting the dispersion degree of battery slurry components, which belongs to the field of battery technology, and particularly relates to the field of battery detection technology, wherein the battery slurry is pre-treated to retain the original microstructure, and the method comprises: obtaining an element distribution map, which is obtained by scanning the original microstructure in the battery slurry; inputting the element distribution map into a preset image processing software to perform image processing to obtain a quantitative dispersion index of each element; and determining the uniform dispersion degree detection result of each component in the battery slurry according to the quantitative dispersion index of all elements. The present application can quantitatively analyze the dispersion degree of each component in the battery slurry, so as to efficiently and accurately control the slurry quality during the battery manufacturing process, thereby improving the quality of battery products.

A method for determining the association and continuity combination of top-side-rock structural surfaces based on unsupervised learning is proposed. This method involves investigating the structural surfaces of the roof and side-rock masses in underground engineering projects to obtain geometric and statistical information. A unified encoding is performed to construct a joint feature set of roof-side-rock structural surfaces. An unsupervised density-based clustering algorithm is used for initial cluster analysis of the joint feature set. A swarm intelligence-based Lüperfox optimization algorithm is introduced to optimize key parameters of the DBSCAN clustering algorithm. A Latin hypercube sampling method is used to improve the population initialization process of the Lüperfox optimization algorithm, resulting in better DBSCAN hyperparameters and optimized structural surface clustering results. The method determines the structural surface system affiliation of structural surfaces in different locations, quantitatively calculates the spatial continuity and combination relationship of structural surfaces, and outputs the spatial association determination results and continuity levels of the roof-side-rock structural surfaces. This method enables intelligent identification and quantitative analysis of the spatial relationship between roof and side-rock rock structural surfaces.

The invention belongs to the field of sample analysis, and provides a mass spectrum system and method integrating online pretreatment and dynamic biological evaluation. The system comprises a sample on-line pretreatment part which is used for obtaining a sample mother solution to be analyzed and separating and preparing concerned components in the sample mother solution; the dynamic biological evaluation part is used for performing multi-channel cell culture and real-time microscopic observation on concerned components in the sample; the dynamic biological evaluation part outputs at least two paths, and one path is connected with the multi-source chromatography-mass spectrometry analysis part so as to finish dynamic biological evaluation for analyzing related components at a cellular level; the other path is synchronously connected to a functional target plate site, and matrix-assisted laser desorption mass spectrometry and surface desorption mass spectrometry are carried out; the system control and data processing part is used for carrying out qualitative and / or quantitative analysis on the components of the metabolite of the dynamic biological evaluation part, and detecting sample injection mass spectrograms, sample difference metabolites and protein molecules in all treatment links of the sample.

The invention provides an operation capability analysis method and device for a virtual marshalling train, equipment and a medium. The whole virtual marshalling train is composed of a plurality of marshalling trains. Wherein one marshalling train is a leading train, and the other marshalling trains are following trains; the method comprises the following steps: determining the vehicle length of a leading vehicle and the vehicle length of each following vehicle; the safety distance between each following vehicle and the front vehicle is determined; according to the distance function, the train length and the safety distance of the speed change of each following train, the whole train length of the virtual marshalling train is analyzed; and analyzing the operation capability of the virtual marshalling train according to the length of the whole train. According to the method, the whole train length of the virtual marshalling train is analyzed according to the distance function of the speed change of each following train, the train length of the leading train, the train length of each following train and the safety distance between each following train and the front train, and then the operation capacity of the virtual marshalling train is analyzed according to the whole train length. Quantitative analysis of the operation capability of the train control system based on the virtual marshalling principle is realized.

This invention belongs to the field of intelligent manufacturing technology and discloses a real-time data-driven intelligent digital twin system for the docking of aerospace components. First, a standardized communication interface is established between multi-source sensors and various modules of the system to collect and transmit sensor data in real time. Second, based on the real-time multi-axis displacement data of the positioner, the real-time motion trajectory of the component is derived through kinematic modeling, completing the spatial pose parameter calculation of the component. Finally, the component pose parameters and multi-dimensional force sensing data are fused to construct a dynamic and interactive three-dimensional digital twin interface, realizing twin monitoring of the component's motion state and internal forces during the docking process. This system, based on the Unity3D engine, achieves real-time synchronous mapping of multi-dimensional force information and motion attitude parameters. Through a closed-loop processing flow of data acquisition, analysis, and visualization, it realizes quality assessment and quantitative analysis of the aerospace component assembly process, significantly improving the controllability of the docking process.

The embodiment of the application provides a kind of soft package battery's multiple field in-situ strain characterization method and device, with shear thickening electrolyte, soft package battery speckle mark surface is upwards, it is placed in the recess of in-situ observation platform, and positive and negative lug is connected to hard plate;Using intelligent temperature control device, the ambient temperature is adjusted to experimental temperature, infrared thermal imager is opened, and it is aligned with soft package battery;Fixed mechanical loading device is below the impact window of in-situ observation platform, and the adjustable power supply outside explosion-proof cover is connected with point device;Soft package battery is connected with battery test system and carries out charge-discharge test;CCD camera is connected with computer and is aligned with in-situ observation platform observation window, and starts shooting;Adjust the adjustable power supply parameter outside explosion-proof cover, and start mechanical loading device;Output the first mechanical behavior information and the second mechanical behavior information corresponding to the first time and the second time of soft package battery;According to the first mechanical behavior information and the second mechanical behavior information, the surface strain of soft package battery is obtained.

The invention discloses a Ni / Co (HHTP) MOF electrode material, a preparation method of the Ni / Co (HHTP) MOF electrode material and application of the Ni / Co (HHTP) MOF electrode material in preparation of an electrochemical aptamer sensor for detecting escherichia coli O157: H7, and belongs to the technical field of harmful microorganism detection. The electrochemical aptamer sensor is prepared by modifying a rod-like Ni / Co (HHTP) MOF material onto a glassy carbon electrode. The electrochemical aptamer sensor disclosed by the invention can efficiently and specifically capture escherichia coli O157: H7, and can be used for rapidly and sensitively detecting escherichia coli O157: H7 in food; compared with a traditional bacterium detection method, the method has good selectivity, storage stability and reproducibility, the detection limit is low, the detection time is short, a new thought is provided for detection of food-borne pathogenic bacteria, and the method has good application prospects.

This invention discloses a method for evaluating the bus voltage stability domain of a cascaded system under small current disturbances, relating to the field of power supply and distribution system technology. The method includes the following steps: constructing an impedance ratio test circuit; introducing a non-intrusive current signal disturbance into the bus voltage of the cascaded system using an impedance analyzer to excite the operation of the cascaded system feedback loop; simplifying the Middlebrook stability criterion to obtain an improved stability criterion; integrating the amplitude-frequency Bode plot data corresponding to each load operating point obtained from the impedance ratio test circuit and fitting the amplitude-frequency Bode plot data of each load operating point using Matlab to obtain a fitted surface based on the test results; comparing the fitted surface with the judgment region determined based on the stability criterion to determine the stable operating boundary of the cascaded system over a wide load range. This invention solves the bus voltage stability problem of black-box cascaded converter systems under a wide load range and proposes a test method that does not require intrusion into the bus line.

This invention relates to a method and system for monitoring the operating status of a transformer. The steps include: real-time monitoring and acquisition of key operating data of the transformer; preprocessing the key operating data; extracting key features from the preprocessed key operating data; constructing multivariate time series data; reconstructing the phase space using time delay embedding technology; constructing a chaotic attractor from the time series data; and conducting in-depth analysis of the morphology and dynamic evolution of the chaotic attractor through topological data analysis to identify abnormal states of the transformer. This invention, by introducing chaotic attractors and topological analysis, not only deepens the understanding of the complex behavior of transformers but also enables quantitative analysis of these behaviors to accurately identify abnormal states and provide early warnings before faults occur, thereby ensuring the safety and reliability of transformer operation.

The invention discloses a knee joint prosthesis evaluation method and system, and the method comprises the steps: carrying out the multi-modal data collection according to the biomechanical performance test data of a knee joint prosthesis, the medical image data and the postoperative motion capture data of a patient, and carrying out the data fusion through a multi-modal alignment network based on deep learning, a fused multi-modal data set is obtained; inputting the multi-modal data set into an adaptive convolutional neural network, and extracting mechanical characteristics of the knee joint prosthesis under a dynamic load to obtain a dynamic mechanical characteristic matrix; and inputting the dynamic mechanical characteristic matrix into a performance evaluation model based on a multi-scale attention mechanism, performing prosthesis performance quantitative analysis, and generating a performance evaluation report. By utilizing the embodiment of the invention, comprehensive quantitative analysis of the prosthesis performance can be realized, and scientificity and accuracy of prosthesis design are improved.

The invention relates to the technical field of online car hailing, and discloses a transport capacity management method and device and computer equipment, and the method comprises the steps: a server side receives an original position point reported by a user side in a preset range, updates the original transport capacity distribution information of a geographic grid corresponding to the preset range in a server map according to the original position point, and stores the original transport capacity distribution information; generating a corresponding transport capacity scheduling strategy; and the user side sends an original position point of the user side to the server side, receives a push data packet returned by the server side based on the original position point, analyzes the scheduling suggestion information and the transport capacity feedback information in the push data packet, executes an updating operation of a user side map according to the transport capacity feedback information, and executes a reminding operation of the scheduling suggestion information at the same time. Through interactive cooperation of the server side and the user side, dynamic updating and accurate scheduling of transport capacity distribution are realized, and the utilization efficiency of transport capacity resources is effectively improved. According to the invention, the problem of unbalanced supply and demand of transport capacity caused by asymmetry of driver and passenger information in the prior art is solved.

The embodiment of the application relates to the field of rock physical experiments, in particular to a method for identifying rock pore types, an electronic device and a storage medium, the method comprising the following steps: obtaining ultrasonic longitudinal wave speed and / or ultrasonic transverse wave speed of a target rock sample after ultrasonic longitudinal wave and transverse wave testing under different temperature and pressure conditions; establishing a temperature-pressure and speed covariant fitting equation based on the ultrasonic longitudinal wave speed and / or ultrasonic transverse wave speed under different temperature and pressure conditions; determining a pore type of the target rock sample according to a fitting coefficient in the temperature-pressure and speed covariant fitting equation based on a preset mapping relationship between pore types and fitting coefficients. The application establishes a temperature-pressure and speed covariant fitting equation, extracts a fitting coefficient, and realizes the differentiation of rocks with different pore types based on the fitting coefficient, thereby improving the identification efficiency of pore types.

The invention discloses an oil paper insulation time-frequency domain response synchronous testing device and an aging state evaluation method, belongs to the technical field of insulation material aging detection, and aims to solve the problem that time / frequency domain dielectric response synchronous measurement cannot be realized in the prior art. According to the scheme, an upper computer outputs a frequency domain excitation instruction to a signal generator, a generated alternating-current voltage signal is amplified by a power amplifier and applied to a to-be-tested product through an alternating-current side protection resistor, and a responded alternating-current signal is collected after passing through a blocking capacitor; the upper computer outputs a time domain excitation instruction to the high-voltage direct-current power supply and synchronously applies a generated direct-current voltage signal to a to-be-tested product through the direct-current side protection resistor, and a responded direct-current signal is collected after passing through the high-voltage silicon stack; and the upper computer calculates a change curve of an alternating current side impedance module value and frequency and a change curve of a direct current side impedance module value and time according to the synchronously acquired alternating current signal and direct current signal so as to obtain a DP value of the to-be-tested product to realize quantitative evaluation of the aging degree of the transformer.

The application discloses a kind of based on knowledge graph and big model fusion's fishery science and technology project innovativeness evaluation method, the method is as follows: S1: from English literature database and patent database automatically collects fishery science and technology related paper and patent data, constructs multi-source heterogeneous dataset;S2: to multi-source data is de-duplication, cleaning and standardization processing, through word segmentation, word class restoration and feature extraction form unified structured data representation;S3: based on structured data carries out entity, relationship and attribute extraction, combines cross-language alignment and expert knowledge verification constructs fishery science and technology field knowledge graph;S4: to project research content and existing technology carries out semantic correlation matching and difference analysis;S5: constructs and includes novelty and frontiers innovativeness evaluation model, carries out quantitative evaluation to project and exports evaluation result.The method not only improves the accuracy and systematization level of innovation point identification, but also guarantees the traceability and comparability of evaluation result.

The present application relates to remote sensing technology and ecological environment restoration evaluation technical field, especially in kind of based on multi-source remote sensing data's mine ecological restoration project achievement evaluation method.The method includes the following steps: to collect mine restoration area carries out multi-source remote sensing data cooperation collection and pretreatment, obtains the noise reduction data set;The multi-dimensional cooperative sensing processing is carried out to the noise reduction data set, and the multi-dimensional cooperative sensing data set is obtained;The soil spectrum feature separation extraction is carried out to the multi-dimensional cooperative sensing data set, and the soil spectrum feature data are obtained;The ground temperature distribution map is calculated according to the soil spectrum feature data;The surface soil moisture content inversion is carried out according to the soil spectrum feature data and the ground temperature distribution map, and the surface moisture content distribution map is obtained;The deep soil moisture content estimation is carried out according to the surface moisture content distribution map, and the soil moisture profile data are obtained.The present application improves the restoration input benefit by quantitative inversion of soil physical parameters and dynamic analysis of rainfall response process.

The invention relates to the technical field of artificial intelligence, can be applied to medical auxiliary diagnosis, financial risk analysis and other scenes, and provides a multi-agent cognitive strategy training and evaluation method, system and device and a medium, and the method comprises the steps: constructing a teacher agent and a plurality of learner agents with different learning behavior characteristics; running a simulation teaching cycle, controlling the teacher agent to publish learning stage information based on a preset scene problem, and controlling each learner agent to execute the information to generate an interaction response containing process behavior data and learning result data; recording process behavior data and learning result data of each agent, and generating a cognitive strategy evaluation report of each agent based on the process behavior data and the learning result data; and combining the plurality of learner agents into a multi-agent cluster capable of cooperatively solving the preset scene problem according to strategy features indicated by the evaluation report. According to the invention, dynamic simulation and evaluation of the agent cognitive strategy are realized, and a cooperative solution cluster oriented to an actual scene can be constructed according to the dynamic simulation and evaluation.

The present invention relates to the field of wireless communication technology, and in particular to a data transmission method and system suitable for 5G communication. The method comprises the following steps: acquiring and analyzing network communication data to obtain regional communication demand data; performing communication transmission resource allocation according to regional communication demand data to obtain communication transmission resource allocation data; performing network slice transmission resource allocation on the communication transmission resource allocation data to obtain network slice transmission resource allocation data; acquiring real-time network communication data and performing interference source impact node identification to obtain interference source impact node data; performing communication interference optimization on the network slice transmission resource allocation data according to the interference source impact node data, thereby obtaining network slice transmission optimization resource allocation data, and uploading it to the communication management platform to perform data transmission tasks. The present invention improves the management efficiency of network resources.