128 results about "Critical threshold" patented technology

The invention discloses a geotechnical engineering catastrophe dynamic real-time intelligent early warning method and system based on displacement monitoring, and the method comprises the steps: collecting the real-time displacement data and related parameters of a geotechnical engineering region through displacement monitoring equipment, and transmitting the real-time displacement data and related parameters to a bank slope stability evolution analysis platform to establish a multi-dimensional database; calling a fractured rock mass effective stress analysis model to calculate rock mass effective stress distribution characteristics, and inputting a multi-grid sliding surface stress calculation algorithm to obtain a potential sliding surface stress state and a critical threshold value; inputting the sliding surface stress parameters and the displacement data into a multi-field coupling analysis learning prediction model to obtain a displacement evolution trend and a catastrophe risk coefficient; and finally, real-time early warning information is generated and fed back through the catastrophe dynamic real-time intelligent early warning module. The method improves the real-time performance and accuracy of early warning, can effectively guarantee the safety of geotechnical engineering, and is suitable for catastrophe early warning scenes of geotechnical engineering such as bank slopes and foundation pits.

The invention relates to the technical field of geotechnical engineering and geological disaster monitoring, in particular to a rockburst tendency dynamic discrimination method, and aims to solve the limitation caused by the fact that a dynamic evolution process is simplified into a quasi-static attribute in traditional rockburst tendency evaluation. According to the method, rockburst tendency is defined as a hidden state variable evolved along with time, a physical constraint state space model containing a hidden state kinetic equation and a multi-modal observation equation is constructed, continuous stress-strain and discrete acoustic emission data are fused, hidden state probability distribution is estimated in real time through online Bayesian inference, and the probability distribution of the hidden state is estimated in real time. And in combination with adaptive information weight updating and physical consistency constraint, predicting a future state trajectory, calculating a risk probability exceeding a critical threshold, and outputting a dynamic rockburst tendency level. According to the scheme, continuous, dynamic and prospective judgment of the rockburst tendency is realized, and the accuracy and reliability of early warning are improved.

The invention discloses a digital project management method and system based on artificial intelligence, and relates to the technical field of project management, and the method comprises the steps: constructing a project digital portrait and multi-dimensional feature analysis framework, determining an analysis domain boundary of intelligent auditing, and automatically generating an intelligent analysis grid adaptive to multi-source heterogeneous data; and performing grid division on project progress data according to an analysis domain boundary, performing adaptive partition on a project grid through an unsupervised clustering algorithm, dynamically determining a critical threshold value of risk early warning based on a project digital portrait and intelligent analysis grid and comprehensive risk stress analysis, and outputting a risk early warning decision management conclusion containing the critical threshold value. According to the management system, an intelligent analysis grid adaptive to multi-source heterogeneous data is generated by constructing a project digital portrait and a multi-dimensional feature analysis framework, and a risk early warning critical threshold value is dynamically determined, so that real-time perception, accurate analysis and intelligent decision support of the full life cycle state of a project are realized.

The invention discloses a battery health state prediction and fault judgment method and system in the technical field of lithium battery management, and the method comprises the steps: collecting multi-dimensional original monitoring data in real time, and calculating derived characteristic parameters; constructing a state evolution trajectory of the battery system and calculating a local curvature at each state point; comparing the local curvature with a critical threshold value to obtain PID (Proportion Integration Differentiation); identifying all unstable state points, defining a set of unstable state points which are adjacent on state space coordinates and continuous on a time sequence as a DAC (Digital-to-Analog Converter), and calculating a chain scale; calculating a monitoring GER; and continuously monitoring a local instability condition, a cross-regional association condition and an energy triggering condition, and generating a corresponding early warning signal according to the satisfaction condition of the conditions. According to the method, a multi-level and layered physical criterion system composed of PDI, DAC to GER is constructed, and extremely high reliability close to zero false alarm is achieved while sufficient early warning advance is provided.

The invention discloses an aviation part quality optimization management method and system based on data analysis, and relates to the technical field of quality management, and the method comprises the steps: collecting an acoustic emission signal and an eddy current signal in the SLM forming process of an aviation part through a multi-modal sensor, and generating a multi-modal data set; key features are extracted from the multi-modal data set, multi-dimensional principal component feature vectors are obtained through fusion, a phase space is constructed, dynamic feature parameters are calculated, and a nonlinear dynamic model is constructed; inputting a multi-modal data set acquired in real time into the nonlinear dynamic model, predicting a dynamic characteristic parameter evolution trajectory, triggering quality abnormality early warning in combination with a critical threshold, and determining a quality risk level according to a supercritical threshold amplitude; and calling a pre-stored laser parameter regulation and control scheme according to the quality risk level, adjusting the mode and power of the laser beam, and monitoring the regulation and control effect in real time until the state of the molten pool is recovered to be stable, so that high-precision quality optimization and active control in the SLM forming process of the aviation parts are realized.

The invention relates to the technical field of soil engineering model tests, and discloses a test system and method for simulating water and mud bursting of a subsea tunnel under the action of vibration, and the system comprises a multi-degree-of-freedom servo feedback vibration module which is used for providing a multidirectional vibration loading platform and feeding back a motor current signal in real time; the visual rock-soil water inrush simulation and multi-field loading module is mounted above the vibration table and is used for accommodating a sample and applying confining pressure and water pressure load; the hierarchical multi-source data acquisition module is communicated with the discharge port and the observation window, and is used for acquiring the outburst mixture and monitoring physical field data; and the intelligent control and risk assessment analysis module is connected with each module to regulate and control loading parameters and invert a catastrophe state based on feedback data. According to the method, a self-adaptive optimization loading mechanism based on the improved particle swarm optimization algorithm is constructed, so that collaborative progressive regulation and control of pore water pressure and vibration frequency parameters are realized, and a critical threshold point of water inrush and mud inrush catastrophe can be accurately captured.

The invention relates to the technical field of electronic component manufacturing, solves the technical problem that interface contact resistance bounces and rises due to thermal stress mismatch, and particularly relates to an electronic component preparation parameter optimization method and system. Generating a gradient layer of which the thermal expansion coefficient continuously changes; and calculating a target thermal expansion coefficient for eliminating the interface thermal stress and an actual thermal expansion coefficient of the in-situ monitoring gradient layer based on the metal and ceramic concentration distribution function. According to the method, component continuous transition is achieved through metal / ceramic precursor dynamic flow control, continuous gradual change from metal to ceramic components is achieved, the coefficient of thermal expansion is in smooth transition in the thickness direction, and internal stress accumulation caused by material expansion difference is blocked from the source; and dynamic deposition regulation is combined to ensure that the thermal expansion gradient at any position is lower than a critical threshold value, and stripping or cracking caused by stress concentration in thermal circulation is avoided.

The invention provides a roof-based subsidence monitoring method for a middle-deep underground mining mine, which comprises the following steps: S1, a deep anchor type anchoring datum point is arranged in a stable rock mass, far away from a mining disturbance area, of a mine roadway or a goaf, and the depth of the deep anchor type anchoring datum point needs to penetrate through a fissure zone and go deep into an original rock stress area; s2, a displacement sensor is installed at the key part of the top plate of the area to be monitored, and the displacement sensor is configured to take the deep anchor type anchoring datum point as a physical zero point; s3, acquiring a distance change original signal of the roof relative to the deep anchor type anchoring datum point through a displacement sensor, and directly acquiring roof subsidence data; and S4, performing signal noise reduction, anomaly detection, nonlinear feature analysis and parameter inversion on the roof subsidence data by using a computer system, and triggering an early warning mechanism when the roof is judged to be in an unstable state or a subsidence parameter exceeds a critical threshold. And an unstable bottom plate is fundamentally abandoned as a measurement basis, and the authenticity and the accuracy of the subsidence data of the top plate are ensured.

The invention relates to the technical field of hydraulic support auxiliary equipment monitoring, in particular to a hydraulic support concentrated solution state online monitoring intelligent supplementing system which comprises a basic monitoring unit, a core calibration unit and an intelligent supplementing control unit. A basic monitoring unit collects multi-position flow velocity signals and sampling point concentration original data through a circulating pipeline built-in sensor, and a core calibration unit constructs a layered flow velocity weight model based on pipeline fluid dynamic characteristics, divides a central high flow velocity area and a near-wall low flow velocity area, dynamically distributes concentration weight coefficients of the two areas, and performs calibration on the flow velocity signals and the sampling point concentration original data. Data are processed through a weighted fusion algorithm, an actual concentration estimated value is output to eliminate detection negative deviation caused by flow velocity layering, an intelligent supplement control unit takes the value as a target threshold value to construct a trend prediction model, and when the concentration is continuously lower than the threshold value, a dual-constraint mechanism is started to generate a valve opening instruction; the concentration of the concentrated solution is stably maintained in an anti-rust and anti-foaming critical threshold range, and stable operation of the hydraulic support is guaranteed.

The application discloses a near electric field alarm safety helmet and an alarm method for omnidirectional field intensity vector monitoring, and relates to the field of electric power safety protection. The safety helmet comprises an omnidirectional field intensity sensing array, a vector field signal processing module and an alarm module which are assembled on a safety helmet body. The omnidirectional field intensity sensing array comprises at least five electric field sensors which are arranged on the top of the safety helmet body and around the brim of the safety helmet body. The vector field signal processing module is used for acquiring electric field intensity components collected by the electric field sensors, and performing vector synthesis on the electric field intensity components to determine the spatial electric field intensity and the field source direction. The spatial electric field intensity is compared with preset safety threshold values and critical threshold values respectively to determine the alarm level of the position where the safety helmet is located. The alarm module is used for outputting corresponding alarm prompts according to the alarm level. The spatial electric field intensity and the field source direction are determined by synthesizing electric field intensity components in different directions, thereby solving the problem that the electric field detection result of the existing safety helmet is inaccurate.

This invention belongs to the field of optical glass manufacturing technology. It provides a dynamic optimization control method for furnace parameters in continuous melting of optical glass, comprising: analyzing the mapping relationship between kiln pressure and spurious liquid level responses based on historical and step test data, determining dynamic critical thresholds for each operating condition, and constructing a decoupling discrimination criterion library. Secondly, monitoring kiln pressure and liquid level, when exceeding the threshold, using multi-source sensors and time-series correlation analysis, distinguishing between spurious and real fluctuations, and outputting the true liquid level change. Then, analyzing the mapping law between liquid level deviation and adjustment parameters, forming a matching rule library of operating conditions, liquid level ranges, and adjustment strategies. Finally, constructing a coupled model of adjustment amount and liquid level change based on random forest, inputting the true liquid level change, and outputting the target value of the adjustment parameter. This invention achieves accurate online distinction between spurious and real fluctuations, avoids erroneous adjustments during material feeding, and improves liquid level control accuracy and product optical quality.

The present application relates to the technical field of dynamic partition storage, in particular to a solid state disk read-write quality adaptive enhancement method and system based on dynamic partitioning. It includes the following method steps: collecting the actual value of each area of the solid state disk to determine whether the read-write quality of each area of the solid state disk meets the standard. The present application collects the actual value of each area of the solid state disk, normalizes the actual value to obtain the normalized actual value, calculates the comprehensive performance value, calculates the stall rate and reversely normalizes, combines the preset weight coefficient to calculate the actual read-write quality benchmark score, sets the initial weight coefficient combination, calculates the optimal solid state disk read-write quality score with the normalized actual value, screens the read-write quality critical threshold, determines whether the read-write quality of each area of the solid state disk meets the standard, quantifies the comprehensive quality of the partition in the solid state disk through multi-dimensional weighting, avoids the one-sidedness of single index evaluation, can accurately identify the read-write quality decline of high-frequency areas caused by high load during the promotion period, and improves the accuracy of evaluating the read-write quality.

The invention relates to the technical field of metal material performance detection, and discloses a method for detecting ductile-brittle transition temperature of a metal material based on a thermal method. The method comprises the following steps: acquiring the average grain size of a material through three-dimensional characterization, quantitatively estimating the movable dislocation density generated by grain boundary thermal activation emission at a specific temperature in combination with a preset dislocation emission coefficient, and linearly superposing the movable dislocation density with the inherent pre-stored movable dislocation density of the material to obtain a total movable dislocation density estimated value. And comparing the total movable dislocation density calculated at different temperatures with the ductile-brittle transition critical threshold obtained from the material knowledge base to determine the critical temperature meeting the condition, namely the ductile-brittle transition temperature. According to the method, the mechanical prediction of the ductile-brittle transition temperature is realized by quantifying the contribution of a key dislocation source from a plastic deformation microphysical mechanism, and the dependence of a traditional method on a large number of destructive experiments is reduced.

The invention is suitable for the technical field of mask plate automatic detection, and provides a thermal compensation intelligent control method and system for a mask plate A0I detection platform, and the method comprises the steps: carrying out the scanning detection of a mask plate, carrying out the interval collection of a reference pattern on the mask plate in the scanning detection process, solving to obtain a drift compensation parameter, and carrying out the calculation of the drift compensation parameter. And triggering interruption calibration when the detection confidence is lower than a critical threshold. The method has the advantages that thermal drift can be inhibited without changing the thermal state or structure of the detection equipment, a high-standard constant-temperature chamber does not need to be constructed, and the cost can be remarkably reduced; in a current thermal state, a drift compensation parameter in coordinate mapping is re-estimated by expanding reference observation, so that geometric errors caused by thermal drift are corrected in a detection result or a detection process which may cause problems is interrupted in time, and the detection precision is maintained without depending on a constant-temperature environment.

The invention discloses a closed-loop mine atmosphere intelligent control system and method based on a space-time prediction model. The closed-loop mine atmosphere intelligent control system comprises a sensing layer which is used for collecting multi-dimensional data including atmospheric environment parameters and mine operation data in real time; the artificial intelligence processing core is in data communication with the sensing layer, and the artificial intelligence processing core is configured to receive multi-dimensional data collected by the sensing layer; utilizing a space-time prediction model to predict the three-dimensional space distribution and migration track of the to-be-measured object in the atmosphere in a preset time period in the future according to the current and historical data; based on the prediction result, generating a preemptive control instruction; the execution layer is in instruction communication with the artificial intelligence processing core, the execution layer is configured to receive and execute the preemptive control instruction, and before the prediction risk of the to-be-tested object reaches a critical threshold value, physical intervention is carried out on a prediction migration path of the to-be-tested object; the problems that an existing mine atmosphere monitoring system is lagged in response, sensing and action are disjointed, and the control strategy is extensive are solved.

The invention relates to the field of aerodynamics and icing wind tunnel design, in particular to an SLD environment vertical icing wind tunnel contraction section profile design method which comprises the steps that a first-stage contraction section and a second-stage contraction section with the specific contraction ratio and length are determined; respectively generating two sections of two-dimensional contraction molded lines by adopting a Vickers curve; and constructing a three-dimensional shrinkage curved surface model, performing computational fluid mechanics simulation, and iteratively optimizing shrinkage ratio and length parameters by taking temperature consistency and speed consistency of water drops and air flow as optimization targets, so as to finally obtain an optimal three-dimensional shrinkage molded surface. By adopting the contraction section designed by the invention, the weber number of the water drops can be controlled below a critical threshold value, the breakage rate of the large water drops is effectively reduced, the temperature and speed following performance of the water drops is remarkably improved, and a key technical support is provided for actually simulating a supercooled large water drop environment in a wind tunnel.

The invention belongs to the technical field of network analysis, and particularly relates to a crowd-sourcing high-order network critical threshold prediction method and device based on a graph neural network. The method comprises the following steps: integrating local structure features of nodes, position codes of positions of the nodes in a whole graph and parameters influencing the global state of a system, and providing comprehensive and three-dimensional cognition on the network for a model; in a network information processing level, a local and global mixed GNN architecture is adopted, and a GIN module and a global self-attention module are arranged in parallel: the former is used for accurately capturing a local neighborhood structure of a node, and the latter is used for capturing a long-distance dependency relationship in a whole graph range; by fusing the information of the two dimensions, the model can understand how the local structure affects the global dynamics more deeply. The problems that the prior art depends on dynamic evolution data, and critical threshold prediction cannot be accurately carried out on the high-order network are solved.

This invention relates to the field of intelligent fault early warning technology, and discloses a nanoscale fault early warning and self-repair method based on quantum sensing and materials genome. The method includes: a detection layer: using a diamond NV color center quantum sensor to capture nanoscale lattice distortion, and fusing multimodal data through federated learning; an evaluation layer: dynamically updating the probability of fault tree nodes, combining pre-set SSC critical threshold conditions from a materials genome library, establishing a remaining lifetime prediction model, and simulating the remaining lifetime; and a repair layer: automatically triggering a repair mechanism when the quantum signal offset and AI confidence level > 90%, and verifying the repair effect. This application, through the interdisciplinary integration of quantum sensing, materials genome engineering, and industrial AI, constructs a closed-loop system of nanoscale damage detection, dynamic fault tree evaluation, and autonomous repair, solving the technical challenges of difficult nanoscale damage monitoring, poor dynamic evaluation adaptation, and delayed repair response in traditional turbochargers under extreme conditions of high sulfur, high pressure, and high volatility.

The present invention relates to a method for criticality assessment in a computer vision system, in which, during driving operation, an image (111) of the area in front of the vehicle is captured by a sensor. To determine a criticality limit, the image is divided into N image areas (120), a Shapley value is calculated for each of the N image areas, and the N image areas are sorted according to importance based on the Shapley value. Starting with the most important image area, a progressively less important image area is removed (130), and an object classification is performed for each remaining image. This is repeated until the object classification for an i-th remaining image yields no result (140), and the criticality limit is determined using a divisor i / N and averaging over several images.During a test drive, a standard criticality threshold is established. During a standard drive, a current criticality threshold is continuously calculated. If the current criticality threshold falls below the standard criticality threshold, a visual restriction of the sensor facing the area in front of the vehicle is detected, whereupon a warning is displayed on the driver's screen. Furthermore, a computer vision system implementing this procedure is presented.

The invention provides a nickel-based single-crystal high-temperature alloy component laser epitaxy repairing method based on energy field regulation and dynamic crystal selection. The nickel-based single-crystal high-temperature alloy component laser epitaxy repairing method comprises the steps that a damaged area is subjected to cleaning treatment and three-dimensional scanning, matrix crystallographic orientation is obtained, a three-dimensional thermal-structure finite element simulation model is established, and a repairing basic process is determined; homogeneous alloy powder is adopted, a laser machining head with a coaxial powder feeding nozzle is used for repairing the damaged area, in the repairing process, auxiliary induction heating is conducted, and the temperature field and the morphology of a molten pool are monitored; if the G / R is lower than the preset critical threshold value, the auxiliary induction heating power is dynamically enhanced; if the tail of the molten pool is disturbed, an ultrasonic vibration field is applied to the molten pool; and treating after repairing. A repair system is also provided. According to the method, the epitaxial growth of the single crystal consistent with the crystallographic orientation of the matrix can be dynamically guided, so that the nickel-based single crystal high-temperature alloy component can be repaired, the repair success rate and the structure consistency are remarkably improved, and the epitaxial proportion of the single crystal is increased to 95% or above.

The invention discloses a system for improving the condensation recovery rate of hydrochloric acid by an incineration method, relates to the technical field of condensation recovery of hydrochloric acid, and aims to solve the problems of low recovery efficiency and poor stability caused by multi-parameter coupling interference and multi-stage working condition disjunction in the condensation recovery process of incineration flue gas. According to the essence, a complete closed-loop control system is generated in a single-region-multi-region cross-linking monitoring mode, a single-path parameter integration unit obtains an initial data set and an action parameter set of a condensation part and calculates and dynamically calibrates an action efficiency coefficient, a series path parameter analysis unit establishes an adjacent condensation part parameter linkage mechanism, and a series path parameter analysis unit analyzes the action efficiency coefficient of the condensation part. The multi-channel cross-linking simulation action unit generates an optimal parameter set through coupling calculation and sends an interference instruction containing a critical threshold value, the efficiency difference is rapidly eliminated through front and back sequence cooperative adjustment, and overall energy consumption waste caused by local low-efficiency operation is avoided.

This application discloses a method for determining the threshold of watershed ecological environment quality based on the PSR model, belonging to the field of watershed ecological assessment technology; it includes: determining the evaluation index items of the target watershed; arranging and combining all possible score values ​​of each index to obtain all score combinations; calculating the comprehensive score of each combination to generate a full sample space; performing fuzzy clustering on the full sample space, iteratively determining the membership degree and cluster center value of each sample to multiple preset cluster categories; sorting the cluster center values ​​of each cluster category in ascending order to form multiple health levels; classifying each sample to the cluster category with the largest membership degree based on the principle of maximum membership degree to obtain the sample set corresponding to each health level; fitting continuous distribution density curves to the sample sets of each health level, and determining the intersection of the distribution density curves of adjacent health levels as the critical threshold between adjacent health levels; and determining the health level of the target watershed based on each critical threshold.

The present application relates to a kind of filter method and system of containing glue waste gas treatment and cyclic regeneration, belong to industrial waste gas treatment technical field.Therein, the method includes: the critical control of the state of gelatinous matter adhesion in containing glue waste gas, based on the compensation filtering algorithm of gelatinous matter separation, the critical penetration block of gelatinous matter filtration coverage is carried out, and containing glue waste gas adsorption filtering parameter is obtained;Guiding model is constructed to waste gas cyclic regeneration, the deposition evolution stage of containing glue waste gas is segmented fitting, the phase transition characteristic quantity of gelatinous matter from discrete adhesion state to continuous film state is extracted, and cyclic regeneration recovery control signal is output;Pressure drop cyclic matching coefficient is calculated, and according to the deposition evolution stage after segmented fitting, the intensity of containing glue waste gas cyclic regeneration is adjusted, and film state solidification critical threshold is set;Based on filtering cyclic control mechanism, the error feedback correction of pore recovery degree after gel layer regeneration is carried out, and the closed-loop cyclic regeneration of containing glue waste gas cyclic filtration is controlled.

The invention provides a plastic particle crushing equipment operation state analysis method, which comprises the following steps: comparing an elastic recovery activation point with a discharge port particle size distribution curve peak value position, evaluating the influence degree of elastic recovery on particle size change, and identifying a particle size thickening trend in combination with a particle compression deformation state in a shearing area; when the particle size thickening trend continuously rises and the gap shrinkage reaches a warning interval, extracting the recovery feature and the resilience force of particle deformation resilience in the shearing area, and identifying a critical threshold value of particle deformation resilience escape from the shearing area; the cutter rotating speed and the feeding rate are adjusted through the compensated shearing force, the blade displacement sensing assembly is calibrated circularly according to the surface temperature change of the main shaft, and when the peak position and the peak width of a particle size distribution curve tend to converge, it is confirmed that particle size distribution reaches a stable state.

The present application provides a sand ecological-hydrological process critical threshold identification system and application thereof, comprising a multi-parameter sample collection device, a soil physicochemical index determination module, a vegetation water stress response monitoring module, a critical threshold calculation unit and a steady state transition early warning module; by determining soil aggregate stability index data and soil water characteristic curve data, monitoring vegetation transpiration conductance data and leaf water potential data, using multi-level lag response analysis and dynamic response surface construction method, calculating critical water content threshold value and steady state transition critical point data, accurate identification and dynamic early warning of sand ecological system steady state transition are realized.

The invention discloses a complex stratum disaster source critical safety distance refined prediction method, and belongs to the technical field of underground engineering and geotechnical engineering disaster prevention and control. The method comprises the following steps: collecting point-line-plane-body multi-source data, and constructing a three-dimensional parameter field reflecting the heterogeneity of the stratum; analyzing a stress-seepage-temperature three-field coupling mechanism, and determining a disaster triggering critical threshold value; establishing a microcosmic-mesoscopic-macroscopic multi-scale model, and iteratively calculating a critical safety distance; and a closed-loop system is formed by combining real-time monitoring and dynamic correction. The prediction error can be controlled within 5%, stratum changes caused by construction disturbance can be responded in real time, the method is suitable for various disaster sources such as water inrush, mud inrush and roof collapse and complex stratums containing faults and karst caves, engineering landing is facilitated on the basis of mature equipment and methods, and safety and economical efficiency are achieved.

The invention provides a sand ecological-hydrological process critical threshold recognition system and application thereof. The sand ecological-hydrological process critical threshold recognition system comprises a multi-parameter sample collection device, a soil physicochemical index measurement module, a vegetation water stress response monitoring module, a critical threshold calculation unit and a steady-state transition early warning module. The method comprises the following steps: measuring soil aggregate stability index data and soil moisture characteristic curve data, monitoring vegetation transpiration conductance data and leaf water potential data, and calculating a critical moisture content threshold value and steady-state transition critical point data by adopting a multi-level lag response analysis and dynamic response curved surface construction method; and accurate identification and dynamic early warning of steady-state transition of the sand ecosystem are realized.

The invention relates to a sponge facility overflow device arrangement method, system, equipment and program product. The method comprises the following steps: obtaining overflow device decision parameters corresponding to the sponge facility; the decision parameters of the overflow device comprise the total catchment area of the sponge facility, the maximum stagnant storage volume of the sponge facility, the soil permeability coefficient, the effective infiltration area of the sponge facility and the designed rainfall duration; based on the decision parameters of the overflow device, comprehensive capability parameters used for representing the rainwater treatment capability of the unit catchment area of the sponge facility are obtained through calculation; obtaining design rainfall corresponding to a waterlogging prevention and control design recurrence period of the city where the sponge facility is located, and determining a critical threshold value; and comparing the comprehensive capability parameter with a critical threshold value, and generating an overflow device arrangement decision scheme based on a comparison result. By adopting the method, hydrological, geological and engineering geometric parameters can be integrated as decision-making indexes, subjectivity of traditional experience decision-making and complexity of model simulation are avoided, and rapid and scientific decision-making of overflow device arrangement is realized.

The invention relates to the technical field of intelligent medical treatment, in particular to a hospital-oriented intelligent scoring performance assessment method, system and device and a medium, and the method comprises the steps: obtaining the performance data of a plurality of hospitals, and extracting a standardized performance indicator vector; unsupervised clustering analysis is carried out on the standardized performance indicator vectors, multiple performance levels are divided, and benchmark groups are determined based on the performance levels; on the basis of the performance data of the benchmark group, key performance indicators and critical threshold values thereof are identified, and score weights are deduced through reverse regression analysis; constructing a scoring formula based on the key performance indicators, the critical threshold values and the scoring weights; and based on the performance data, calculating the comprehensive performance score of each hospital by using a scoring formula. According to the method, objective and adaptive scoring based on data driving can be realized, and scientificity and efficiency of hospital performance assessment are remarkably improved.

The present application relates to the field of simulation technology, specifically to a device cluster job simulation planning method based on multi-agent cooperation, which constructs a land grid model and a yield density upper and lower bound channel, determines the capacity critical threshold interval by forward cumulative scanning, generates a target point based on the interval midpoint and passability constraints, and realizes cooperative device path guidance. The target point offset gating mechanism is introduced to control path re-planning triggering, improve path stability and responsiveness. The interval boundary is dynamically modified during the job process by combining the measured yield, and the final meeting point is locked when the interval length and meeting distance conditions are met. After the simulation is completed, the attribution analysis is performed by locking the deviation and cumulative displacement indicators, the row sequence is adjusted and iteratively re-simulated and optimized by combining the row accessibility, and the optimal job scheme is output. The method can improve the efficiency and simulation accuracy of device cooperative operation in complex environments.