92 results about "Scientific analysis" patented technology

The invention relates to the technical field of electrical performance testing, and particularly discloses an LED vehicle lamp operation monitoring system and method based on data analysis, and the system can accurately obtain the illumination parameters of the environment where an LED vehicle lamp is located, further scientifically analyzes and determines the reference illumination intensity of the LED vehicle lamp, and on this basis, comprehensively monitors and carefully collects the circuit information of the LED vehicle lamp, thereby improving the reliability of the LED vehicle lamp. Through a data analysis technology, each abnormal lamp bead existing in the LED vehicle lamp is accurately positioned, the abnormal lamp beads are specifically adjusted according to predetermined reference illumination intensity, after adjustment is completed, the running state parameters of the LED vehicle lamp are further monitored, the adjustment adaptation index of the LED vehicle lamp is evaluated accordingly, and the adjustment adaptation index of the LED vehicle lamp is evaluated according to the running state parameters of the LED vehicle lamp. Therefore, whether further performance adjustment needs to be carried out or not is intelligently judged, the adjustment effect is fed back in time, and therefore it is ensured that the made adjustment can fully meet set performance indexes.

The invention relates to the technical field of ocean data interpolation filling, in particular to a space-time deficiency filling method and system based on context association and physical guidance. The method comprises the following steps: acquiring seawater dissolved oxygen data and context data; multivariable space-time dependence extraction is carried out based on the obtained seawater dissolved oxygen data and context data; gaussian noise diffusion is carried out based on the obtained seawater dissolved oxygen data; noise prediction is carried out based on double-view space-time correlation; and the prediction error is constrained based on the joint loss function. According to the method, a physical consistency constraint mechanism based on a partial differential equation is introduced in a model training process, so that model output better conforms to a physical coupling rule among variables in a marine environment. The constraint effectively inhibits non-physical fluctuation possibly occurring in the interpolation result, enhances the physical credibility and interpretability of the result, and provides a more reliable data basis for subsequent scientific analysis and process modeling.

The invention relates to the technical field of communication base station monitoring, and discloses a power environment monitoring system and method applied to an outdoor communication base station, and the system comprises a data collection module, a data processing module, and a monitoring control module. Data such as a power state and battery parameters are fully covered, and a detailed basis is provided for monitoring; denoising is carried out through a moving average filtering algorithm, a scientific analysis method is combined, the conditions of power supply switching, battery capacity attenuation, equipment energy consumption and the like are accurately analyzed, and data quality and analysis reliability are ensured. During storage, archiving is carried out according to classes, and management and query are facilitated; real-time early warning is carried out according to an analysis result, and when power supply switching is frequent, electric quantity of commercial power and a battery is abnormal, the battery is aged or equipment energy consumption exceeds a limit, early warning information is sent to operation and maintenance personnel in time, so that quick response and disposal are facilitated; the operation stability and reliability of the base station are improved, the equipment failure risk is effectively reduced, meanwhile, energy consumption optimization is assisted, the operation cost is reduced, and the method has great significance in guaranteeing stable operation of a communication network.

The invention relates to the technical field of data management, in particular to a curvature radius monitoring system for a large-diameter shield tunneling machine in the stratum settlement process, and the system can accurately judge whether the operation process of the shield tunneling machine needs to be adjusted or not by monitoring and analyzing the operation data of the shield tunneling machine in a tunneling operation section and the corresponding curvature radius data in real time. The method comprises the steps of effectively avoiding stratum disturbance caused by tunneling deviation, reducing the stratum settlement risk, further judging whether to optimize shield tunneling machine communication, guarantee stability and accuracy of information transmission and improve the collaboration and safety of tunneling operation or not based on the adjusted operation condition, marking an operated section as a formed section after tunneling is completed, and improving the working efficiency of the shield tunneling machine. The system continuously obtains and evaluates stratum settlement data, whether an early warning adjustment instruction is sent out or not is judged through scientific analysis, and the series of processes can find stratum settlement abnormity in advance and take countermeasures in time, so that the overall benefits of engineering are improved, and all-directional intelligent monitoring support is provided for shield construction.

The invention relates to the technical field of vehicle-mounted control platform testing, and discloses a joint debugging test system and method for a vehicle-mounted control platform, and the method comprises the steps: firstly obtaining historical joint debugging test record data of a user, determining a test period, constructing a data set, and then determining a periodic user characteristic data set according to a personalized rule; then scene features are extracted, a path is constructed, and optimal data are determined through analysis and scoring; taking scene feature path nodes of the optimal data as reference groups, analyzing adaptive scene features, and determining a recommendation scoring range; and then screening and pushing test data according to the scoring range, and realizing periodic automatic updating. The system comprises a test record acquisition module, a scene feature processing module, a test adaptation recommendation analysis module and a feedback updating module. According to the method and the system, historical data are effectively utilized, scientific analysis, personalized recommendation and flexible periodic updating of a test scene are realized, and the joint debugging test efficiency and accuracy are improved.

The invention relates to the technical field of obstacle target recognition, and discloses a laser obstacle clearance instrument obstacle intelligent recognition system and method based on big data, and the system comprises a laser obstacle clearance target recognition module, a laser obstacle clearance point and obstacle clearance parameter analysis module, and a laser obstacle clearance operation control module. Target obstacle type intelligent identification is carried out according to target obstacle live-action image parameters in combination with an intelligent identification algorithm and different types of obstacle image information stored based on big data, and laser obstacle clearance obstacle type information is efficiently and intelligently identified; scientific analysis is carried out on the position of a target obstacle clearance point based on target obstacle type identification information in combination with an intelligent search algorithm and standard set obstacle clearance point image information of different types of obstacles, and accurate identification of an optimal obstacle clearance point target of a laser obstacle clearance obstacle is realized.

The invention discloses an advertisement directional pushing method based on video content, relates to the technical field of advertisement pushing, and solves the technical problem that target audiences really having demands cannot be effectively reached by fully considering personalized characteristics and demand differences of each user. According to the method, information such as browsing history records, search records and use time of the push users is obtained in detail, and scientific analysis methods such as time period division, classification of advertisements of the same type and frequency calculation are applied, so that a user portrait which is more accurate than that of a traditional mode can be constructed; therefore, advertisements meeting user requirements are pushed in a targeted mode, the matching degree of the advertisements and the users is improved, invalid advertisement putting is reduced, and by analyzing software use behaviors and advertisement browsing conditions of the users in different time segments, for example, the browsing ratio of different advertisement types and the software use frequency in the target time period are calculated, so that the user experience is improved. And the advertisement pushing times and types are reasonably adjusted.

The invention discloses a simple measuring method for the air volume of a dome square-bottom tunnel, and relates to the technical field of crossing and fusion of tunnel engineering and an environment monitoring technology. The ventilation quantity single-point test method suitable for the dome square bottom tunnel is an important technology. The method focuses on utilizing precise measurement equipment and scientific analysis means to accurately evaluate the performance and efficiency of the ventilation system in the tunnel with the dome and the square bottom. The method comprises the following steps: firstly, selecting a measuring point which is convenient to measure and has a certain distance from the top wall and the side wall in a dome area in the dome square-bottom tunnel, measuring the wind speed at the position, calculating the wind speed at the center of the tunnel according to the wind speed distribution rule in the cross section of the dome square-bottom tunnel by taking the wind speed as a reference, and further calculating the wind volume of the cross section in the dome square-bottom tunnel. By means of the method, the air volume of the dome square-bottom tunnel can be determined only by measuring the air speed of one point position, and therefore the problems that multi-point measurement in the tall and large dome square-bottom tunnel is not easy and time and labor are wasted in measurement are solved.

The invention provides a content marketing semantic analysis method and system based on natural language processing, and relates to the technical field of natural language processing, and the method comprises the steps: constructing a marketing intention semantic tree through dependency syntax analysis, calculating audience perception vectors to form a conduction path graph, recognizing and demonstrating conflict unit pairs, and evaluating marketing persuasion. A double-layer optimization objective function is constructed for text reconstruction, scientific analysis and accurate optimization of marketing content are realized, the persuasion and the propagation effect of the marketing content are improved, the consumption of marketing resources is reduced, and the accuracy of a marketing strategy is enhanced.

The invention discloses a state monitoring method and system for multi-modal fusion features based on electroencephalogram and electrocardio, relates to the technical field of artificial intelligence monitoring, and solves the technical problems that the features are difficult to effectively and accurately extract and systematic and scientific analysis is lacked during model analysis. According to the method, error data in electroencephalogram and electrocardiosignals are corrected and processed, the signal quality is improved, a reliable data basis is provided for subsequent analysis, model hyper-parameters are scientifically and systematically selected by adopting a cross validation and grid search method, the model performance is effectively improved, real-time indexes and historical data are combined, and the real-time performance of the system is improved. According to the method, the time sequence diagram is drawn, the change trend of the characteristic indexes is deeply analyzed, abnormal changes of the physiological indexes can be found in time, potential risks can be warned in advance, historical abnormal state data are sorted, risk rating indexes are constructed, and a more comprehensive and objective basis is provided for state risk assessment.

The invention relates to the technical field of pre-class meeting abnormity early warning, in particular to a pre-class meeting data deep analysis and abnormity early warning method and system, which dynamically matches standard pre-class meeting process data according to text feature data of a pre-class meeting initiating department, and accurately judges whether a pre-class meeting process is abnormal or not in combination with obtained real-time pre-class meeting process data. If so, executing a pre-class flow adjustment operation; according to the real-time meeting-before-class flow data, corresponding meeting-before-class flow index data is collected, and a meeting-before-class index evaluation model is combined to accurately evaluate meeting-before-class indexes to generate meeting-before-class index evaluation data; and judging whether the flow index in the before-class meeting process is abnormal or not by combining an evaluation threshold scientifically set through an improved intelligent optimization algorithm, and if so, giving out early warning, thereby realizing scientific analysis of before-class meeting data and accurate early warning of before-class meeting abnormity.

The invention relates to the technical field of intelligent water affair management, and discloses a comprehensive management system for intelligent water affair. The system comprises a hydrological data acquisition module, an abnormal feature recognition module, a correlation analysis module, a grading early warning module and a decision output module. The hydrological data acquisition module acquires data such as water quality and water flow velocity of multiple monitoring points to generate a hydrological feature set; the abnormal feature recognition module extracts abnormal indexes and topological information to form a pipe network abnormal feature distribution diagram; the correlation analysis module analyzes the pollution diffusion path and generates an abnormal correlation analysis result; the grading early warning module divides risk grades and outputs an early warning parameter set; and the decision output module generates a partition regulation and control instruction and a resource allocation strategy. According to the system, comprehensive monitoring, accurate abnormity identification, scientific analysis and association, reasonable early warning and efficient decision making of the water supply pipe network are realized, and the intelligent water affair management level is improved.

The invention discloses an urban hydropower infrastructure failure analysis method, device and equipment and a storage medium, and relates to the field of urban hydropower failure analysis, and the method comprises the steps: determining the failure proportion of an upstream node, and determining whether the upstream node is in a failure state or not based on the failure proportion, a to-be-analyzed node corresponding to an urban hydropower infrastructure; under the condition of a non-failure state, determining the ponding depth of the node to be analyzed according to a ponding depth change model; when the ponding depth is greater than the ponding depth threshold, determining a target failure probability of the to-be-analyzed node based on the ponding depth and a target failure probability model; generating a random value of the to-be-analyzed node through a Monte Carlo simulation method, and determining whether the to-be-analyzed node is in a failure state again based on the target failure probability and the random value; if the state is still the non-failure state, further determining whether the state is the failure state based on the random failure probability; and generating a failure analysis result based on the state of the to-be-analyzed node, thereby realizing scientific analysis of the failure of the hydroelectric infrastructure.

The present invention relates to the field of vehicle control platform testing technology, and discloses a joint debugging test system and method for a vehicle control platform. The method first obtains user historical joint debugging test record data, determines the test cycle and constructs a data set, and then determines the periodic user characteristic data set according to personalized rules; then extracts scene features, constructs paths, analyzes and scores to determine the optimal data; groups the scene feature path nodes of the optimal data as a benchmark, analyzes the adapted scene features, and determines the recommended score range; then filters and pushes test data according to the score range, and realizes automatic periodic updates. The system includes test record acquisition, scene feature processing, test adaptation recommendation analysis, and feedback update modules. The method and system effectively utilize historical data to realize scientific analysis of test scenarios, personalized recommendations, and flexible periodic updates, thereby improving the efficiency and accuracy of joint debugging testing.

The application relates to the technical field of customer service man-machine interaction processing, and discloses a customer service man-machine intelligent interaction system and method based on communication object information. The system comprises a user information acquisition module, a customer service man-machine interaction information analysis module and a customer service man-machine interaction execution module. The appearance national type of a customer service user is scientifically analyzed through the matching success rate of the user appearance feature image, the appearance national type of a communication object is scientifically analyzed based on the appearance feature of the communication object, the customer service man-machine interaction AI model required for customer service man-machine interaction is accurately screened according to the appearance national type information of the customer service user, the language type used and the characteristic text data of the customer service man-machine interaction AI model scientifically set by combining an intelligent recognition algorithm, the customer service man-machine interaction AI model is scientifically customized based on the appearance national type and the language type of the communication object, and the service experience and quality of the customer service man-machine interaction are improved.

The invention discloses a supporting device for forest tree pest and disease damage data acquisition, and relates to the technical field of agriculture and forestry, and the supporting device is characterized by comprising a telescopic rod, a fixing plate is arranged on the telescopic rod, an insect pest trapping and killing mechanism is arranged on the fixing plate, and an insect pest data acquisition mechanism is arranged on the insect pest trapping and killing mechanism; a supporting mechanism is arranged at the bottom of the telescopic rod, a clamping mechanism is arranged on the telescopic rod, and the clamping mechanism is clamped on a forest tree and used for improving the stability of the device. The system can adapt to different tree heights, trunk diameters and complex woodland terrains, is matched with solar power supply, realizes stable field long-term operation, can accurately identify plant diseases and insect pests, predicts trends through fusion of meteorological and forest basic data, scientific analysis and an ARIMA model, triggers graded early warning and pushes prevention and treatment suggestions, and has good application prospects. Large-scale and refined forest management requirements are met, a scientific basis is provided for disease and pest control decisions, and the accuracy and efficiency of forest management and protection are improved.

The invention relates to the technical field of hydrographic measuring instruments, in particular to a flow velocity meter suitable for low-water-depth and clean water environments, which comprises a buoy with two conical ends, simulates the working principle of a submarine, and can realize diving and floating of the buoy by controlling a water inlet valve, a water outlet valve and a high-pressure gas cylinder. In the floating process, the depth sensor records the water depth in real time, and the propeller synchronously measures the flow velocity, so that continuous and high-resolution flow velocity-depth profile data from the water bottom to the water surface can be collected, compared with traditional discrete point measurement, the data is more complete and more accurate, the accuracy of flow calculation and scientific analysis can be greatly improved, and the measurement precision is improved. Through the designed cross-shaped guide assembly, the whole buoy becomes a large underwater wind vane. No matter how the water flow direction changes, the empennage can generate restoring torque under the impact of the water flow, and passively and automatically drive the whole platform to rotate around the axis of the mooring rope until the head (one end provided with the propeller) of the platform is completely aligned with the incoming flow direction.

The invention specifically relates to a variable-frequency power supply control system, and relates to the technical field of variable-frequency power supplies. An analysis module; and the adjusting module is controlled. According to the invention, the mains supply monitoring module accurately collects voltage, current and frequency parameter information of the mains supply according to a set time interval in a preset monitoring time zone, and the analysis module uses a scientific analysis method to respectively obtain a voltage abnormal value, a current abnormal value and an unbalance frequency ratio and comprehensively processes the values into evaluation coefficients. Compared with a traditional monitoring system, the comprehensive and accurate parameter analysis mode can more accurately reflect the actual operation state of the commercial power, can timely and accurately discover tiny anomalies in the operation of the commercial power, gives an early warning in advance, and provides a reliable basis for guaranteeing the stable operation of electric equipment.

The invention relates to a geothermal energy development information management system, relates to the technical field of geothermal energy development, and realizes real-time sharing and seamless joint of information among different departments by establishing a unified information standard and a data interface. Through an integrated platform, all departments can conveniently obtain and use required information, and the efficiency and accuracy of information exchange are improved; according to the invention, integration and centralized management of geothermal information are realized, the problem of information dispersion in traditional geothermal resource management is solved, a user can conveniently obtain various required geothermal information in a one-stop manner, and the utilization efficiency of the information is improved. The geothermal resource management method is beneficial to improving the management efficiency and the utilization level of geothermal resources, promotes reasonable development and sustainable utilization of the geothermal resources through comprehensive mastering and scientific analysis of geothermal resource information, and has important economic and environmental benefits. Meanwhile, based on advanced technologies such as Vue3, ECharts and JavaScript, the performance and interactivity of the system are improved, the fluency of the animation effect and the response speed of the system are ensured, and the user experience is improved.

The invention discloses an outdoor operation method, system and equipment based on a satellite remote sensing technology, and a medium, and relates to the technical field of outdoor operation. The method comprises the following steps: acquiring multi-source remote sensing data of a target outdoor area through a satellite remote sensing module; generating a disaster situation map through the ground control center according to the multi-source remote sensing data; generating an operation task list through the ground control center according to the disaster situation map; distributing the operation task list to a plurality of robot dogs through the ground control center; and carrying out collaborative operation through the robot dogs according to the operation task list. Therefore, by fusing satellite remote sensing, intelligent analysis and multi-robot-dog cooperative control, integrated emergency response of rapid sensing, scientific analysis, automatic distribution and unmanned operation in a disaster scene is realized, and the intelligence, high efficiency and safety level of outdoor disaster disposal are remarkably improved; the key technical problems of information lag, decision-making dependence on experience, high personnel risk, low response efficiency and the like in traditional rescue are effectively solved.

The invention relates to the technical field of petroleum drilling scheme planning, and discloses a petroleum drilling process drilling scheme analysis system and method based on big data, and the system comprises a petroleum drilling bit object processing module, a drilling bit working state processing module, and a petroleum drilling bit scheduling module. Intelligent analysis processing of drill bit types needed by petroleum drilling operation is carried out based on petroleum drilling stratum geological information and petroleum drilling operation daily production capacity information in combination with an intelligent recognition algorithm and petroleum drilling drill bit type information stored based on big data, and scientific analysis of matching of the drill bit types needed by petroleum drilling is achieved; the real-time lithologic characteristic information of the petroleum drilling bit end is combined with an intelligent search algorithm and the petroleum drilling bit working parameters stored based on big data to intelligently analyze the petroleum drilling bit operation state parameters, so that the petroleum drilling bit working parameters are accurately matched, and the intelligence and applicability of petroleum drilling are improved.

The invention relates to the technical field of mine car automatic ore loading, in particular to an underground rail mine car automatic ore loading system and method based on industrial vision and the AI technology, and the method comprises the steps: accurately matching the real-time environment image data of an underground rail mine car with the environment image feature data of different mine car positions, and generating the real-time position meter number of the underground rail mine car; the method comprises the following steps: calculating the meter number of a mine car, comparing the meter number with a preset meter number of a wellhead brake point position, controlling the speed of the mine car according to a numerical comparison result, correcting the position of the mine car after the speed of the mine car is 0, and executing discharging operation of an ore drawing machine after the position of the mine car is corrected. And then scientific analysis is carried out on the mine car material level change image feature data through a constructed mine car material level identification model, mine car material level full scale analysis data is generated, and whether the discharging operation of the ore drawing machine is ended or not is judged according to the mine car material level full scale analysis data. Automatic ore loading of the underground tramcar and accurate control over the ore loading process are achieved.

The present invention discloses a method for constructing a shale temperature-pressure model based on logging information and its application. The model construction method includes: constructing a shale matrix microscopic geometric distribution model; obtaining the values of shale compaction geometric parameters based on the microscopic geometric distribution model and logging information; constructing a shale temperature-pressure model based on the microscopic geometric distribution model and the conversion between the stiffness matrix and velocity; substituting the obtained values of the shale compaction geometric parameters into the shale temperature-pressure model after determining the fitting parameters to obtain the shale temperature-pressure model based on logging information. The present invention can process the logging information to extract the temperature-pressure elastic parameters of shale, which can not only support the subsequent forward and inverse inversion technologies, but also prepare for the scientific analysis of the elastic characteristics of shale.

This invention discloses an intelligent retrofitting system and method for existing earth-rock dams, comprising: a sensing module for collecting monitoring data, calculating a comprehensive monitoring system evaluation index, identifying and optimizing the monitoring system based on the index, and outputting optimized monitoring data and multi-dimensional defect identification results; an analysis module for calculating an analysis model evaluation index, diagnosing and optimizing the analysis model based on the index, and outputting dam safety status assessment results based on the optimized analysis model; a decision-making module for calculating a decision-making efficiency index, diagnosing and optimizing the decision-making process based on the index, and outputting control commands based on the optimized decision-making process; and a control module for calculating a control performance index, diagnosing and optimizing the control configuration based on the index, executing control commands based on the optimized control configuration, and feeding back the execution result data to the sensing module. This invention enables precise monitoring, scientific analysis, intelligent decision-making, and efficient control.

The invention relates to the technical field of industrial equipment monitoring, in particular to a bearing state monitoring sampling optimization method and system based on reinforcement learning, and the method and system are characterized in that multi-dimensional parameters such as equipment operation conditions, real-time vibration signals and bearing key degrees are integrated, and dynamic baseline prediction, health index correction and sampling strategy optimization are adopted. And finally, a self-adaptive monitoring sampling strategy which is highly matched with the real-time health state of the bearing is generated, so that the conversion from uniform monitoring to on-demand monitoring is realized, the overall efficiency and the intelligent level of the monitoring system are remarkably improved on the premise of guaranteeing the equipment safety, and scientific analysis and accurate optimization of the bearing state monitoring sampling strategy are realized.

The present invention relates to the technical field of medical devices, and particularly to a quantitatively damaging forceps for medical use. The present invention is provided with a base platform, a forceps body, an FBG strain sensor, an information mapping module, a clamping control component, a clamping analysis module, and a compensation execution module. The wavelength of the FBG is obtained through the FBG strain sensor, and a unique mapping relationship between the wavelength of each FBG and the clamping force of the clamping end is pre-established through the information mapping module. Whether the clamping effect of the clamping end is abnormal is determined through the clamping analysis module. Any cam rotation mechanism is controlled by the pre-compensation unit to rotate a preset angle in the pre-compensation direction, and the operation adjustment mode for the two cam rotation mechanisms is determined through the compensation execution module. Furthermore, the abnormal phenomenon of the forceps causing damage is timely detected according to the real-time data feedback situation, and the clamping state is timely adjusted according to scientific analysis, thereby improving the stability of the construction of the traumatic lesion model.

This invention belongs to the field of biodetection technology, specifically disclosing a novel skin typing method, biomarkers based on skin surface metabolomics typing, and their applications. Based on population-level skin surface metabolite measurement data and through multi-dimensional scientific analysis, this application ultimately discovered that the skin samples of the subjects formed two distinct clusters. This demonstrates that differences in metabolomics clusters based on skin typing objectively exist. Furthermore, the two distinct clusters based on the aforementioned skin surface metabolomics data are named "Metabolic Type 1" or "Metabolic Type 2." Simultaneously, these two typing methods also exhibit differences in various skin condition indicators (e.g., sebum levels, actual age, wrinkles, freckles, etc.). By using the typing method provided in this application to study skin surface metabolomics substances, one or more metabolites can be used as biomarkers to identify the specific skin typing level and guide adjustments to the desired skin condition. This application overcomes the limitations of existing methods that define skin typing solely based on dry, oily, etc., providing more comprehensive guidance for practice.

The utility model belongs to the technical field of the scientific analysis instrument industry, and particularly relates to a sampling needle cleaning mechanism which comprises a shell, a cleaning cavity arranged in the shell and a recycling cavity arranged on the outer side of the cleaning cavity in a surrounding mode, a liquid inlet is formed in the cleaning cavity, a notch is formed in the upper end of the cleaning cavity, and the liquid inlet is communicated with the liquid inlet. And the cleaning cavity is communicated with the recycling cavity through the notch. According to the cleaning device, the liquid inlet speed at the liquid inlet can be adjusted through the water pump, so that the sampling needle in the cleaning cavity is cleaned, and the side wall of the cleaning cavity is cleaned; by arranging the scraping plate, the side wall of the recycling cavity can be cleaned so as to ensure that the side wall of the recycling cavity is clean, and filtering holes are formed in the scraping plate so as to ensure that large-particle impurities are retained on the scraping plate.

The present invention discloses a method and system for analyzing and modeling the surface roughness of pores in shale, the method includes preparing a shale sample, obtaining a photo of the fresh cross-section of the shale sample, splicing photos of large-area shale cross-sections, performing roughness analysis on the pore morphology photos, obtaining relevant parameters of the pore structure, and establishing a pore molecular model; based on high-resolution and large field-of-view scanning electron microscope photos, the present invention can quickly perform roughness analysis and pore structure identification on nanoscale-micron-scale organic matter pores and clay mineral pores, with high identification accuracy, reducing the influence of artificial point selection factors, and based on the surface roughness of pores in the shale sample and the pore structure characteristics, a molecular structure model that more conforms to the actual pore characteristics of shale is established. This model can truly reflect the internal pore structure composition of shale, providing a more reliable model for later scientific analysis and research using this model.

The invention relates to the technical field of water resource scheduling management, and discloses an intelligent water resource dynamic simulation, regulation and control system and method based on karst hydrogeological investigation, and the method carries out the precise measurement of the total water storage capacity of a non-water-storage space structure in karst geology based on the three-dimensional model information of a karst geology space in combination with geologic structure analysis software. The water storage capacity of the karst geographic area is reliably evaluated according to the geological space characteristics of the karst geographic area, and the karst geological water resource scheduling precision is improved; according to the karst geological space three-dimensional model information, an intelligent search algorithm and different water storage rate standard karst geological space structure three-dimensional model information based on big data storage are combined to carry out karst geology water storage scheduling rate scientific analysis, and the water storage rate of a karst geological area is intelligently matched based on karst geological area space characteristics. Intelligent and environment-friendly karst geology water resource dispatching operation is achieved, and the efficiency and accuracy of karst geology water resource dispatching are improved.