65results about How to "Reduce blindness" patented technology

The invention provides an intelligent garden environment monitoring data analysis method and system. Sensors are deployed to collect temperature, humidity and other data in real time to form a data set. Analyzing an environment parameter change mode of each region by adopting a time sequence clustering algorithm, and determining characteristics and trends; and carrying out dimension reduction on the data by using a multi-dimensional scale transformation algorithm to a three-dimensional space for visualization, and generating an environment state map. And evaluating the plant fitness in combination with a plant physiological ecology knowledge base, and generating a scoring matrix to guide the preliminary layout scheme. And dynamically adjusting the layout by applying reinforcement learning, selecting an optimal scheme, and predicting a future environmental evolution path based on the optimal scheme and historical data. An automatic control system framework is constructed, a self-adaptive control algorithm is designed, intelligent regulation and control of plant layout are realized, garden management efficiency is improved, and ecological protection and sustainable development are promoted. Therefore, full-chain intelligent management from environment monitoring to plant layout optimization is realized, and the intelligent level of garden environment monitoring and management is remarkably improved.

The invention discloses a river pollution tracing method and system based on underground water quality pollution monitoring, and relates to the technical field of river pollution tracing. According to the river pollution tracing method based on underground water quality pollution monitoring, the real-time concentration value of each pollutant in underground water is obtained in real time and analyzed to obtain the underground water pollution real-time evaluation index; according to the method, a plurality of abnormal measurement points with abnormal concentration in a set area are identified, and the traceability position coordinate of each pollutant with abnormal concentration in underground water in a river is analyzed, so that the real-time evaluation index of underground water pollution can be continuously calculated by acquiring the pollutant concentration data of each measurement point in real time; and whether the pollutant concentration exceeds the preset range or not is judged in time, so that the defects of hysteresis and untimely data updating of traditional water quality monitoring are overcome, dynamic monitoring of the pollutant concentration can be realized, and quick response when the pollutant is abnormally increased is ensured.

The invention relates to the technical field of sewage treatment, in particular to a distributed rural sewage treatment station intelligent optimization method and system. According to the method, firstly, the water quality parameters and the operation parameter data are collected and cleaned, the preprocessed feature data are input into the prediction model to obtain the prediction result, the prediction result is compared with the real-time operation data to obtain the deviation data, and the model parameters are dynamically optimized and issued according to the deviation data, so that the blindness of parameter setting in a traditional method is reduced; the control strategy can be adjusted in real time according to the actual operation condition, the operation cost is remarkably reduced while the effluent reaches the standard, and the treatment efficiency is improved.

The invention provides a high-voltage circuit breaker partial discharge monitoring and early warning method and system, and relates to the technical field of partial discharge monitoring, and the method comprises the steps: obtaining the feature information of a target circuit; a circuit analysis model is called for analysis, and a target analysis result is obtained and comprises a plurality of target point locations; dynamically monitoring the first target point location through an ultrahigh frequency sensor to obtain first partial discharge information; calling a signal analysis model for processing and analysis to obtain a first signal feature set; activating a fault diagnosis model to analyze the first signal feature set to obtain a first diagnosis tag; and when the partial discharge fault of the target high-voltage circuit breaker at the first target point location is displayed, a first early warning signal is sent out. The technical problems that in the prior art, partial discharge monitoring mostly depends on artificial experience or fixed rules, intelligent analysis means are lacked, misjudgment or missed judgment is prone to occurring, accurate positioning is difficult, and the safety of the high-voltage circuit breaker is reduced are solved.

The invention provides a sandstone type uranium ore prospecting method based on a tectonic unit boundary, and the method comprises the steps: obtaining the geological data of a sedimentary basin, determining the spatial distribution and the tectonic and stratum characteristics of tectonic units in the sedimentary basin, and determining the types of beneficial metallogenic tectonic units according to the spatial distribution and the tectonic and stratum characteristics of the tectonic units; and determining a first-level exploration target region of the sandstone type uranium mine by combining the gravity data and / or seismic data and / or oil and gas bearing conditions of the favorable metallogenic structure units for different types of favorable metallogenic structure units. According to the method, on the basis of deep analysis of uranium-controlled metallogenic characteristics of the tectonic unit boundary, the upheaval and fracture of the tectonic unit boundary are taken as important marks for prospecting, and geological and geophysical prospecting methods are combined, so that a novel efficient and low-cost prospecting method is formed, an optimal target of a sandstone type uranium ore prospecting area can be accurately locked, and the prospecting efficiency of the sandstone type uranium ore prospecting area is improved. The blindness in the prospecting process can be obviously reduced, and the exploration efficiency is improved.

The invention discloses an adrenal vein blood sampling auxiliary system based on three-dimensional reconstruction. The system comprises an image acquisition module used for acquiring medical image data of an adrenal gland and a surrounding human organ tissue structure; the image preprocessing module carries out preprocessing operation on the acquired image data; the contour recognition module recognizes contours of adrenal gland, blood vessels and peripheral human organ tissue structures from the preprocessed image; the three-dimensional reconstruction module constructs a three-dimensional model of the adrenal vein and the peripheral human organ tissue structure according to the contour information; the model correction module is used for correcting and perfecting the three-dimensional model; the rendering module carries out rendering processing on the corrected three-dimensional model so as to enhance the visualization effect; and the positioning auxiliary module provides positioning auxiliary information for adrenal vein blood sampling operation. The system can effectively cope with the complex condition of a blood vessel loop, improves the three-dimensional reconstruction precision, provides accurate guidance for adrenal vein blood sampling, and assists in clinical decision making.

The invention relates to the technical field of agricultural equipment control, in particular to a rain-sheltering cultivation greenhouse control method and system based on intelligent perception. Importing the real-time growth state model diagram into a dictionary search tree for search matching, and obtaining growth moisture requirement range data of the pepper seedlings in the current growth stage in the target greenhouse; collecting real-time moisture data of soil in the target greenhouse at a plurality of preset time nodes, and analyzing according to the collected real-time moisture data and the growth moisture requirement range data in combination with a Bezier curve algorithm to obtain a soil moisture suitability deviation coefficient of the pepper seedlings in the target greenhouse; the moisture condition of soil in the target greenhouse is analyzed according to the soil moisture suitability deviation coefficient, the target greenhouse is regulated and controlled according to the analysis result, the greenhouse can be intelligently regulated and controlled according to the soil moisture condition, it is ensured that pepper seedlings grow under the appropriate soil moisture condition, and the yield of the pepper seedlings is improved. Therefore, the growth quality and yield of pepper seedlings are improved.

The invention provides an engineering safety management method and system based on a BIM model, and relates to the technical field, and the method comprises the steps: obtaining engineering information, constructing an engineering BIM model, carrying out the monitoring region division of the engineering BIM model, obtaining an engineering model monitoring region, and obtaining the region group association information; calculating an area scheme influence coefficient to obtain a risk area, and calculating a type influence coefficient of each engineering monitoring type to obtain a risk type; calculating an engineering cumulative risk influence coefficient, comparing the engineering cumulative risk influence coefficient with a preset cumulative influence threshold value, obtaining cumulative risk judgment of the engineering BIM model, and further obtaining risk influence early warning information; according to the risk early warning information, the abnormal risk monitoring type and the risk area information, reversely obtaining the wind direction source information, and adjusting the risk source information until the risk early warning information does not exist, the method can comprehensively and accurately identify and evaluate the potential risk in the project, and realizes real-time monitoring and effective early warning.

The invention discloses a photovoltaic module inspection method and inspection system based on an unmanned aerial vehicle. The inspection method for the photovoltaic module based on the unmanned aerial vehicle comprises the following steps: performing first inspection on the photovoltaic module to obtain a first coordinate of a fault module; taking the first coordinate as a first inspection point, and planning a first inspection path based on the first inspection point; according to the first inspection path, utilizing the unmanned aerial vehicle to obtain an electroluminescent image set corresponding to the fault component; fault identification is carried out according to the electroluminescent image set, a second fault type of the target fault component is obtained, and the flight height of the unmanned aerial vehicle during first inspection is larger than the flight height of the unmanned aerial vehicle during flying of the first inspection path. According to the photovoltaic module inspection method based on the unmanned aerial vehicle provided by the embodiment of the invention, the blindness of inspection can be reduced, targeted fault type acquisition and fault cause acquisition are performed on the fault module, and the fault identification accuracy is ensured while high-efficiency inspection is ensured.

The invention discloses an air-ground cooperative unmanned vehicle path planning method in a complex environment, and the method comprises the steps: firstly obtaining distribution point position information, distribution point material demand information, environment information, distribution center position information and unmanned vehicle information; secondly, preliminarily performing global path planning according to the information; then, the unmanned vehicle runs according to a path obtained by global planning, and when the unmanned vehicle senses that the surrounding environment cannot pass through, a built-in unmanned aerial vehicle of the unmanned vehicle lifts off to recollect surrounding environment information to obtain updated environment information; and finally, according to the updated environment data, local path planning is carried out on each path through traversal constraint, re-planning path constraint and energy consumption constraint, and a distribution path of the unmanned vehicle in a complex environment is obtained. Aiming at the requirements of maneuverability, rapidity and continuity of the unmanned vehicle in a complex environment, the unmanned vehicle is not restrained by an existing road, so that the emergency material distribution time is shortened, and the rescue efficiency is improved.

The invention provides a three-dimensional ventilation digital twinning system, which comprises a ventilation information investigation module, a three-dimensional visual modeling module, a ventilation system analysis module and a ventilation system optimization module, and is characterized in that the ventilation information investigation module collects underground ventilation system engineering, production operation, ventilation structures and ventilation equipment materials, combines mining area ventilation lines, and optimizes the ventilation system engineering, the production operation, the ventilation structures and the ventilation equipment materials; temperature, humidity, air volume and wind direction information parameter detection is carried out on main nodes of an underground ventilation system; the three-dimensional visual modeling module is used for establishing a three-dimensional visual model of the whole mine ventilation system according to 1: 1 in combination with ventilation information basic data and related materials; the ventilation system analysis module diagnoses and analyzes air volume distribution, air speed standard reaching, ventilation resistance distribution and a diesel oil equipment tail gas diffusion path in a multi-dimensional mode based on a ventilation numerical value analysis model; the change condition of the mine ventilation system can be scientifically and reasonably predicted, and the mine ventilation cost and working conditions can be quantitatively analyzed.

This application relates to the field of IoT detection technology, specifically to an online accuracy detection method for filling machines using multi-sensor fusion. The method includes: collecting multi-source heterogeneous sensor signals from the filling machine head and adding consistent timestamps based on business events; reconstructing a two-dimensional event matrix using the cumulative mass flow corresponding to the flow signal as the progress coordinate, locating progress anchor points, and defining a transient window; within the transient window, performing adaptive cancellation on the weighing signal using the pressure signal as a reference to obtain a steady-state weighing value, performing dynamic density correction on the flow signal using temperature and pressure signals to obtain a flow integral value, and performing dynamic weight fusion based on the real-time signal-to-noise ratio to obtain a fused output value; using the fused output value at the end of the transient window for qualification judgment and source tracing to generate a traceability tag, and combining the final filling quality detection value to generate an accuracy data package for online detection. This application effectively improves the metrological robustness of the final filling value under valve-closing transients and enhances the traceability of the detection.

The invention relates to the technical field of fracturing in oil and gas field development, in particular to a method for water injection pressure recovery degree and soaking time of an old well energy storage group, which comprises the following steps of: 1, establishing a multiphase flow fluid-solid coupling seepage model, and carrying out historical fitting of production dynamics before oil well refracturing to obtain four-dimensional ground stress and formation pressure distribution of an oil reservoir; calculating the remaining oil reserve; 2, according to the remaining oil reserve threshold value interval of the area, it is determined that the group refractures the group well, if the remaining oil reserve is within the threshold value interval, the operation is continued, and if the remaining oil reserve is not within the threshold value interval, the operation is stopped; and 3, according to production characteristics before water injection and energy increasing of the target group well. According to the method, blindness of refracturing construction design of the old well energy storage group is reduced, the overall reconstruction effect of fracturing is enhanced to the maximum extent, the reservoir reconstruction volume and the resource utilization degree are improved, and efficient development of tight reservoir oil and gas resources is achieved.

A self-adaptive multi-objective evolution method for optimizing the capacity of an off-grid wind and light hydrogen production and energy storage system comprises the following steps: firstly, according to an energy storage system model, taking unit hydrogen production cost, wind and light abandoning penalty and load shedding penalty as minimization objectives; secondly, the capacity of each component of the wind-solar power generation unit, the power storage unit and the hydrogen and oxygen storage unit is used as a decision variable, and the system is set to conform to the actual constraint; thirdly, initializing a population; individuals in the population are initialized according to the constructed search space, so that the individuals meet constraint conditions; then adaptively selecting a search strategy; the strategy adaptive network selects a proper search strategy based on individual decision variables and objective function values, and evolves a new sub-population; and fusing the parent population and the child population to calculate the non-dominated level and the congestion degree of all individuals, determining parameters of the reward updating strategy adaptive network according to the non-dominated level, and screening out a new population. According to the method, the randomness and blindness of algorithm search can be reduced, and the search efficiency of the algorithm is enhanced.

The invention relates to a design method and system for a micro-energy acquisition electronic tag, and the method comprises the steps: obtaining an energy receiving parameter and environment condition data of the micro-energy acquisition electronic tag, and carrying out the matching analysis, and obtaining a corresponding tag energy receiving scheme; acquiring system architecture information of the micro-energy acquisition electronic tag, and performing energy management analysis on the system architecture information and the tag energy receiving scheme to obtain a corresponding energy management strategy group; acquiring tag power consumption data of the micro-energy acquisition electronic tag, and performing power consumption prediction on the energy management strategy group to obtain a corresponding energy utilization trend; performing module task identification on the tag power consumption data according to the system architecture information, and performing task planning according to the energy utilization trend to obtain a corresponding task execution strategy; and performing global optimization on the initial power consumption control scheme and the task execution strategy to obtain a corresponding global energy optimization strategy. According to the invention, fine management of system energy distribution can be realized.

The invention relates to the field of intelligent operation and maintenance of power equipment, in particular to a transformer maintenance-free respirator control method integrating temperature, humidity and pressure monitoring and electric heating regeneration and a storage medium. The method comprises the following steps: firstly, deploying a sensor in the respirator, collecting humidity and internal temperature and pressure data of a drying agent, and obtaining accurate data after moving average filtering and temperature compensation; and the control module is combined with the data, a humidity threshold value dynamically adjusted along with the load rate of the transformer and a regeneration period to trigger the regeneration system to start. During regeneration, the electric heating piece heats the drying agent, the fan adjusts the rotating speed according to the real-time temperature and humidity to discharge steam, meanwhile, the moisture absorption capacity recovery rate is corrected by combining aging of the drying agent, and starting and stopping or temperature adjusting delay are conducted according to the standard condition. The process data is uploaded to the operation and maintenance cloud platform through the LoRa module encrypted by AES-128, and the platform analyzes the trend through weighted linear regression and gives an alarm; and operation and maintenance personnel optimize parameters according to the parameters and regurgitate a judgment link. Related programs are stored in the storage medium and can be executed by the processor to achieve the method, and support is provided for maintenance-free of the respirator.

In order to solve the problem of intelligent color recognition in the waste glass sorting process, a convolutional neural network color recognition algorithm based on deep learning and embedded with spatial information is invented in a waste glass image collecting and sorting system, intelligent color recognition in the waste glass sorting process is achieved, and the intelligent color recognition efficiency is improved. And an intelligent color identification technology is provided for quickly and accurately sorting out waste glass with different colors during waste glass sorting.

The present invention discloses an industrial Internet information interaction method and system based on industrial algorithms, and relates to the technical field of industrial Internet information interaction. Through the blockchain recording module, data cannot be tampered with during the process of collection, processing and storage, ensuring the authenticity and transparency of information; this improvement enhances the trust basis of all parties and avoids the generation of information islands. The real-time data analysis module integrated in the system can quickly analyze the data standard set and calculate the equipment efficiency coefficient and energy consumption efficiency coefficient. This real-time feedback mechanism enables problems in the production process to be quickly identified and solved, improving production efficiency and resource utilization. The smart contract module automatically triggers contract execution according to real-time data, realizes the automation of information interaction, and reduces the need for human intervention. By automatically issuing alarms and adjusting production parameters, the system can more flexibly respond to equipment failures and excessive energy consumption problems, reducing production risks.

This invention discloses a well placement method, equipment, and storage medium for bioherm-type carbonate reservoirs. The well placement method includes the following steps: S1. Obtaining the amplitude spectrum data of the reservoir to be well placed; S2. Classifying the bioherm type and reservoir category, and determining the connectivity of the reservoir; S3. Determining the optimal well placement area and optimal well placement pattern based on the determined bioherm type, reservoir category, and reservoir connectivity; S4. Performing economic calculations on the wells to be placed within the optimal well placement area, establishing an economic model, and determining the optimal well spacing d. i And the optimal number of oil and gas wells N i This method, tailored to the characteristics of bioherm-type carbonate reservoirs, classifies them into different types, distribution ranges, and connectivity, providing a reliable reference for well placement. It designs optimal well placement areas and patterns, effectively improving well development efficiency. An economic model is established through economic accounting to optimize well spacing and the number of oil and gas wells, thereby increasing reservoir development utilization and economic benefits.

The application is named reservoir scale intelligent optimization demonstration system and method based on multi-target risk coupling, and belongs to the technical field of intelligent decision-making of water conservancy and hydropower engineering. The technical problem to be solved is that the traditional reservoir scale demonstration relies on static scenarios, cannot quantize the multi-target conflict coupling relationship, does not systematically consider multiple uncertainties and risks, has low optimization efficiency and insufficient scheme robustness. The technical solution points are that the application sets six modules of hydrological risk modeling, multi-target coupling analysis, scale optimization decision, uncertainty propagation simulation, comprehensive resilience evaluation and intelligent demonstration integration, generates dynamic hydrological risk indexes by fusing climate scenarios and historical data, quantizes the multi-target coupling relationship, optimizes the reservoir scale parameters by combining reinforcement learning and risk constraint, and automatically generates the optimal reservoir scale demonstration scheme with high robustness through uncertainty simulation and resilience evaluation.

The invention relates to the technical field of knowledge maps, and particularly discloses a knowledge map-based intelligent travel visualization method, which comprises the following steps of: presetting an initial period, calculating a crowding coefficient, dynamically rolling and updating the period, and setting an interval threshold value at the same time; accessing a scenic area API to obtain data, and periodically calculating the popularity of each scenic spot through a weighting formula; based on the new period and the scenic spot density threshold, dividing congestion levels, and drawing a red-yellow-green three-color thermodynamic diagram; screening surrounding scenic spots based on user coordinates, and recommending according to popularity ranking; and constructing a city 3D tourist map to associate the scenic spot popularity. According to the method, the real-time performance of data is guaranteed through dynamic periodic updating, a thermodynamic diagram is generated through multi-dimensional data to realize passenger flow visualization, low-congestion and high-heat scenic spots are recommended in combination with user coordinates, and optimization mechanisms such as 3D map linkage are supplemented, so that the management efficiency and the tourist experience are improved, and text travel management is promoted to be transformed into data driving.

This application provides a core-shell structure microwave absorbing material and its thickness optimization design method and application, relating to the field of electromagnetic wave absorbing materials technology. The core-shell structure microwave absorbing material comprises a sheet-like magnetic metal core and a silica shell covering the core, the silica shell being prepared via a sol-gel method. The optimization design method includes: obtaining the intrinsic electromagnetic parameters of the constituent materials; constructing a single-particle simulation model with shell thickness as the variable; calibrating the simulation parameters through a decoupling-testing-verification iterative process; optimizing the solution for the optimal thickness based on the calibration model with the goal of maximizing the effective absorption bandwidth of reflection loss; and finally determining the optimal thickness range through experimental verification. This application achieves synergistic optimization of microwave absorption performance and corrosion resistance, solving the problems of long development cycles and high costs associated with traditional trial-and-error methods. The designed core-shell structure microwave absorbing material can be widely used in fields such as electronic equipment shielding, stealth technology, and microwave anechoic chambers.

The application relates to a detection and communication integrated identification method for instantaneous permanent fault of a power collection line by means of IIDG active energy injection, and belongs to the technical field of power system relay protection and automation. The method comprises the following steps: after a fault occurs in a power collection line, starting an IIDG with network construction capability, realizing zero starting voltage rise through VF control, establishing a characteristic voltage, judging whether a composite voltage criterion is met, if yes, the fault is permanent, and the injection source exits after maintaining a constant frequency transmission; if not, the fault is instantaneous, and the injection source sends a frequency shift information after a time delay. Voltage is continuously monitored during the injection, and whether a complete frequency shift signal is received is determined through a frequency variance criterion and data segment correlation. If the voltage does not meet the composite voltage criterion during the detection process and the complete frequency shift signal is received, reclosing is allowed after power loss again, otherwise, reclosing is locked. The method aims to solve the technical problem that the fault nature of the power collection line under a voltage loss condition is difficult to identify in the prior art.

This invention relates to a method for optimizing the tubing size of injection and production wells in a water-driven sandstone oil and gas reservoir, comprising the following steps: 1. Determine the coefficients A and B of the binomial production capacity equation for the gas well and establish the production capacity equation. 2. Analyze and determine the critical sand production pressure difference during gas production in the target gas reservoir's injection and production wells. 3. Establish a binomial function relationship between formation pressure and cumulative gas production. 4. Calculate the formation pressure during the peak winter gas production period of the target gas reservoir based on the established binomial function relationship. 5. Use nodal analysis to perform dynamic modeling and calculate the production capacity of different tubing sizes under different formation pressures and production pressure differences. 6. Based on the production capacity under peak formation pressure, use cross-plots to quantitatively optimize the tubing size with a production capacity increase of 10% and a critical sand production pressure difference of less than 3 MPa. This significantly reduces the blind selection of tubing and ensures the gas supply capacity and reliability of the gas reservoir during the critical peak-shaving period.

The invention discloses an endangered plant phoebe hainanensis identification and systematic monitoring method based on multi-source data fusion, and belongs to the technical field of endangered plant protection. According to the method, a potential distribution area is delineated through a species distribution model, individual accurate identification and filing are achieved through a multi-branch feature fusion model, multi-scale growth and microenvironment data are collected through Internet of Things nodes, and finally a'discovery-identification-monitoring-protection 'whole-process closed loop is formed through a unified data management platform. According to the method, phenological feature extraction, transfer learning modeling, man-machine collaborative verification and low-power-consumption Internet of Things monitoring technologies are adopted, and the problems that a traditional method is low in efficiency, insufficient in recognition precision and fragmented in monitoring are solved. According to the method, efficient discovery, accurate identification and long-term dynamic monitoring of the wild population of the phoebe hainanensis are achieved, scientific support is provided for protection decision making, and the method is convenient to operate and high in practicability and has protection value and application prospects.

This invention provides a collaborative control system and method for urban lake stormwater and flood control, relating to the field of flood management. The system and method utilize a multi-source heterogeneous information fusion system, collecting and standardizing multi-dimensional data such as quantitative precipitation forecasts, hydrology, urban flooding, and water quality to construct a unified data lake. This achieves high-precision, multi-dimensional information perception, providing comprehensive and high-quality data support for control decisions. It addresses the problems of incomplete information perception and inconsistent data standards in existing technologies. Furthermore, it establishes a dynamic risk assessment model integrating flood control, ecological water quality, social, and water resource utilization risks. Risk indicators serve as both hard constraints and soft costs in scheme comparison, enabling quantitative assessment and control of multiple risks. This allows decision-makers to clearly understand the potential risks of different schemes, significantly reducing the blindness of decision-making and improving the safety of control schemes.

The invention relates to the technical field of electric power computing power scheduling, and discloses an electric power cross-domain computing power elastic scaling scheduling system supporting a creative GPU (Graphics Processing Unit). The system receives a power cross-domain computing power scheduling request, and searches a matched historical computing power use record set from a historical computing power database according to the request. And carrying out load category division on the historical record set to generate historical computing power record subsets of a plurality of load categories. Computing power feature core calculation is performed on the subsets to obtain a plurality of computing power feature core points and associated time intervals; and using the associated time intervals as the time range of a plurality of scheduling analysis layers, performing multi-scale scheduling feature analysis on the computing power monitoring data sequence of the current power cross-domain within the specified time range through the plurality of set scheduling analysis layers, and outputting a plurality of computing power scheduling feature sets. And carrying out cross-scale fusion calculation on the feature sets to obtain a fusion computing power scheduling feature set.

The invention discloses a cerebral apoplexy lower limb intelligent rehabilitation training system, which relates to the technical field of rehabilitation instruments and comprises a walking module, a body fixing bracket, a foot fixer, a leg adjusting module, a waist and shoulder auxiliary fixing module and a training posture recognition and correction module. According to the training posture recognition and correction module, a binocular 3D camera is innovatively adopted to collect data, a Voxel CNN network and multi-constraint energy function optimization are combined, high-precision joint coordinate recognition, joint angle calculation and motion trajectory similarity evaluation are achieved, and a self-adaptive admittance control algorithm based on performance is matched, so that the precision of the robot is improved. The training load and the auxiliary force can be dynamically adjusted in real time according to the rehabilitation ability of a patient, customized rehabilitation training of one person and one strategy is achieved, the one-step training mode of a traditional instrument is thoroughly changed, rehabilitation training better meets the individual requirements of the patient, and the rehabilitation effect and the training efficiency are remarkably improved.

The application discloses a hydraulic fracturing parameter optimization method based on nano-indentation spatial heterogeneity atlas, and relates to the field of coalbed methane exploitation.The method comprises the following steps: sampling and nano-indentation testing of a target coal seam, and obtaining load-displacement curves of each measuring point; analyzing and calculating the load-displacement curves of each measuring point, and drawing a heterogeneity atlas of the sampling points and a micro-mechanical spatial heterogeneity atlas of the entire coal seam; identifying the micro-mechanical spatial heterogeneity atlas of the entire coal seam, and constructing a hydraulic fracturing design scheme according to the distribution information of the advantageous path and the inferior path of the fracturing fissure in the coal seam; and combining resistivity tomography technology to monitor the fissure expansion range, and dynamically adjusting the fracturing parameters of the hydraulic fracturing design scheme.The application generates a micro-mechanical spatial heterogeneity atlas through a nano-indenter, depicts the mechanical heterogeneity inside the coal rock, saves the trial-and-error cost of fracturing design, and reduces the blindness of fracturing.

The invention belongs to the technical field of biomedical informatics and drug safety assessment, and provides a drug side effect frequency prediction method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out the weighted fusion of one-dimensional sequence features and two-dimensional structure features through employing learnable weight parameters; constructing a side effect similar graph through known drug-side effects, and initializing side effect nodes into semantic feature vectors by adopting preset medical term embedding; calculating an attention coefficient between the side-effect node and a neighbor node thereof by adopting a graph attention network, and updating a semantic feature vector; and training the drug weighted fusion result and the semantic feature vector to obtain a model for predicting the side effect frequency of the target drug, and the technical scheme of the invention realizes the accuracy and efficiency of drug-side effect frequency prediction.