93results about How to "Improve predictability" patented technology

The invention relates to a heat supply prediction method and system based on spatial-temporal feature fusion deep learning, and the method comprises the following steps: S1, carrying out the collection and fusion of multi-source heterogeneous data, and constructing an integrated data set; s2, preprocessing the data; s3, constructing a graph structure model of the heat supply system, and constructing a weighted undirected graph; s4, constructing and executing forward calculation of the space-time double-flow deep network; s5, designing a composite loss function including mean square error loss and physical constraint loss, and performing joint optimization training on the space-time double-flow deep network; and S6, performing multi-step heat supply load prediction by using the trained model, outputting a heat supply load curve of each heat exchange station in a specified time period in the future, and integrating a prediction result with a heat supply scheduling system. The method has the advantages that the prediction precision is improved compared with that of a traditional machine learning model by capturing the spatial-temporal characteristics at the same time, and the advantages are more remarkable in extreme weather.

The invention discloses a geological disaster multi-scale environment control factor identification system based on machine learning, and relates to the technical field of geological disaster identification, and the system comprises a multi-scale environment factor collection module which obtains historical geological disaster data of a target area, extracts geological disaster multi-scale environment features, and constructs a geological disaster-environment factor correlation feature set; the quantitative evaluation module is used for establishing a geological disaster risk probability prediction model, quantitatively evaluating the marginal contribution degree of each environmental factor on different spatial scales, identifying the environmental factors dominating geological disaster development in multiple scales of a region, a drainage basin and a slope, and establishing a geological disaster risk probability curved surface of a target region and an environmental factor contribution spatial distribution diagram; and the prevention and control module introduces a human activity intensity index and an ecological system state index in a target area, establishes an environmental factor dynamic coupling risk propagation model and a real-time multi-scale risk transmission path, and generates a dynamic risk grading early warning map. According to the invention, the accuracy of geological disaster risk assessment is improved.

This invention discloses a method for enhancing and controlling the radiation of an LPP-EUV light source based on dual-pulse spatiotemporal co-constraint, belonging to the field of semiconductor manufacturing technology. This invention obtains a spatiotemporal reference by real-time monitoring of a liquid metal droplet, uses a pre-pulse laser to induce target material deformation into a fogged target cloud, and combines high-speed imaging and a hydrodynamic model to predict the time and coordinates of the target cloud's energy absorption peak. It dynamically adjusts the delay time and optical axis direction of the main pulse laser to achieve dual-pulse spatiotemporal co-constraint, and constructs a closed-loop control system through a recursive least squares algorithm with a dynamic forgetting factor. This invention effectively improves the extreme ultraviolet light conversion efficiency, controls the power fluctuation of the light source within ±0.5%, and extends the maintenance cycle of optical components by 2 times. It can be widely applied to next-generation high-power extreme ultraviolet lithography light source systems, meeting the application requirements of semiconductor miniaturization processes.

The application discloses a lining cloth dyeing control method and system based on artificial intelligence, and is used for the control field, and the method comprises the following steps: real-time monitoring of multi-source data in the lining cloth dye vat, capturing the video stream inside the lining cloth dye vat; using a Gaussian mixture variational autoencoder model to extract features from the multi-source data, obtaining multi-source feature data; obtaining the changing moment of the fabric state in the video stream, and extracting the fabric state change feature data according to the observed fabric color change and the heterogeneity of the dye distribution in the video stream; fusion of multi-source feature data and fabric state change feature data; introducing a model predictive control layer, predicting the result to adjust the dyeing parameters in real time; establishing an intelligent feedback mechanism. The Gaussian mixture variational autoencoder model is trained and optimized through the small-batch stochastic gradient descent and back propagation algorithm, important features are learned and captured from the data.

The invention relates to a low-fault-energy micro-twin synergistic deformation cobalt-based alloy and a preparation method thereof, and belongs to the field of cobalt-based high-temperature alloys. According to the alloy, on the basis of Co-Al-W, Ti and Ta which are smaller than or equal to 4 wt% are added according to calculation of a first principle, and the stacking fault energy is controlled to be-95 mJ / m < 2 > to-89 mJ / m < 2 > (0K). Aiming at the defect of insufficient high-temperature plasticity of the gamma '-phase strengthened cobalt-based alloy, an electronic structure is accurately regulated and controlled through a first principle, intrinsic stacking fault energy is designed to reach an optimal negative value interval, a micro-twin mechanism is activated, dislocation slippage and micro-twin coordination is realized, and the problem of sudden plasticity drop caused by single deformation mechanism (dislocation slippage leading) and grain boundary weakening of a traditional alloy is solved; the high-temperature strength and the plasticity are synchronously improved.

The application relates to a water quality change trend rapid prediction method based on multi-source data fusion and physical constraints, and specifically comprises the following steps: step 1: synchronously collecting data such as spectrum information, DO, COD, temperature and pH at key monitoring sites, constructing a water dynamics-water quality coupling equation, and simulating the space-time dynamic distribution of water quality parameters; step 2: outputting a water quality sensitive area through a water dynamics-water quality model, screening sensor layout points by combining information entropy evaluation and spatial clustering, realizing low-cost water quality sensor network deployment through a multi-objective optimization algorithm, and calculating a water body global water quality distribution map by adopting a spatial interpolation method; step 3: analyzing main pollution sources according to the synchronous collection of spectrum information at key monitoring sites, and adopting principal component analysis and an attention mechanism neural network; step 4: based on real-time optical characteristic value-DO data, combining a spatial topological network, a water quality gradient and a cross-region covariance to capture the spatial correlation of water quality parameters between different points, and constructing an optical characteristic value-DO-COD dynamic prediction model; combining pollution tracing and spectrum characteristic correction to correct the COD prediction value, adopting ensemble Kalman filtering to assimilate multi-source data, and improving the model accuracy.

The invention discloses a path tracking control method suitable for crawler-type agricultural equipment. The method comprises the following steps: S1, building a navigation hardware control system on crawler-type equipment; s2, designing a Kalman filtering algorithm to filter the course angle of the crawler-type equipment; s3, correcting an equipment positioning error caused by the attitude angle; s4, a fusion algorithm of the Stanley algorithm and the Pure Pursuit algorithm is designed; s5, designing an enhanced SPP algorithm; s6, performing secondary optimization on the control law output by the SPP algorithm by using a fuzzy PID control algorithm; and S7, fitting a total control law equation in combination with the control algorithm, and converting the control law into the linear speed of the left and right tracks of the crawler-type equipment so as to realize steering and straight movement of the crawler-type equipment. According to the invention, a complex agricultural environment is regarded as a black box system, and item-by-item optimization is carried out by superposing an algorithm with high interpretability, so that the adaptability of a control system to the black box system is improved, and finally, the equipment path tracking precision is improved step by step.

The present application relates to the technical field of food detection, and more particularly to a milk aroma active ingredient detection method based on enzymatic hydrolysis-smell identification combination, which provides a milk aroma active ingredient detection method, comprising: extracting and enriching volatile components in milk, and detecting aroma active ingredients therein by using gas chromatography-smell-mass spectrometry combination technology; wherein the extraction and enrichment method comprises: first, using streptomyces protease to perform enzymatic hydrolysis treatment on the milk, and then using sequential stirring rod adsorption extraction technology to extract and enrich the volatile components. The method provided by the present application can significantly reduce the detection limit of milk aroma active ingredients, improve the detection sensitivity, and broaden the detection range of aroma active ingredients, and is significantly superior to the prior art in terms of the number and structure type of detected components, and has the advantages of high detection efficiency, short cycle, convenient operation and the like, and has good application prospect.

The application provides a target positioning photoelectric detection system and method based on multi-band fusion, relates to the technical field of optical detection, and obtains a first input data set of a photoelectric detection target based on a terahertz quantum pulse source; a dynamic bias current is applied to the photoelectric detection target to obtain a second input data set; then the first input data set and the second input data set are fused in features to obtain a multi-modal feature matrix; the multi-modal feature matrix is fused in features for monitoring to obtain a detection discrimination matrix and a fusion feature vector, the micro-evolution trend of defects of the photoelectric detection target is determined based on the fusion feature vector and the detection discrimination matrix; the weight parameters of a multi-band deep fusion network are updated in negative feedback according to the micro-evolution trend, and then the defect result of the photoelectric detection target is output based on the updated multi-band deep fusion network, so that the application can realize micro-positioning and evolution prediction of defects based on multi-modal fusion detection, and the precision of photoelectric detection is improved.

The invention belongs to the technical field of medical instruments, and particularly relates to an invisible anterior tooth adduction correction device based on implant anchorage, which comprises a main body, two sides of the main body are fixedly connected with a pair of anchorage arms, one end, far away from the main body, of each anchorage arm is fixedly connected with a mounting part, and the edge of the main body is fixedly connected with a pair of fixing rings. The fixing ring is located between the pair of anchorage arms, a sliding groove is formed in the edge of the side, away from the fixing ring, of the body, a pair of sliding blocks are slidably connected to the inner side of the sliding groove, first hooks are fixedly connected to the sides, away from the fixing ring, of the sliding blocks, and a pair of second hooks are arranged on the two sides of the sliding groove. The anterior tooth adduction device has the beneficial effects that by arranging the main body, the anchorage arm, the anchorage nail and the fixing ring, the anterior tooth adduction device can be fixedly mounted in the palate skull of the oral cavity of a patient, and anchorage is provided for anterior tooth adduction of the patient, so that loss of anchorage is avoided, and accurate control on the anterior tooth adduction speed, direction and mode of the patient is realized.

According to the heterogeneous resource-oriented virtual power plant hierarchical clustering-cooperative game aggregation and trusted interaction system provided by the invention, refined and structured representation of a strong heterogeneous resource set is realized by constructing a dynamic digital twinborn archive and adaptive clustering of resources, and a hybrid prediction model fusing physical rules and data driving is adopted, so that the reliability of the system is improved, and the reliability of the system is improved. Physical rationality of behavior prediction and quantitative capture of uncertainty are ensured; through a hierarchical distributed optimization architecture of a master-slave-alliance collaborative game, a global complex optimization problem is efficiently decoupled, and real-time collaborative optimal scheduling under large-scale resource access is realized while privacy and autonomy of a resource main body are protected; through an online rolling credibility regulation capability interval evaluation mechanism, a diversified capability vector with a confidence level is output, so that the virtual power plant becomes a reliable transaction object which is transparent to a power grid and has a risk known, and the interaction credibility and credit rating of the virtual power plant in the power market are fundamentally enhanced.

This invention discloses an acidic oxidizing potential water generator and its preparation method for stable water quality control, belonging to the field of disinfection equipment technology. The device is designed with an inlet module, a brine preparation module, a mixing and control module, an electrolysis module, and a control system. Its core lies in employing a high-precision electric proportional control valve and a millisecond-level PID algorithm to achieve constant pressure and constant flow control of the inlet water flow. The brine preparation module uses a solid natural melting structure combined with closed-loop liquid level control, enabling long-term maintenance with a single salt addition lasting for six months. A built-in water quality prediction model based on electrolysis current (fma) is incorporated, using a specific algorithm formula to calculate pH, ORP, and available chlorine content in real time, achieving "soft measurement" and feedforward control of water quality. This solves the problems of high manual operation intensity and raw material concentration fluctuations, ensuring that the effluent water quality stably meets the high standard disinfection requirements of pH 2.5-2.6, ORP 1112-1115mV, and available chlorine 50-55mg / L.

The invention belongs to the field of data processing and water resources, and particularly relates to a running water ecological landscape water demand calculation method based on a mountainous area. The method comprises the following steps: identifying characteristics such as karst landforms and ancient terraces through remote sensing data; constructing a nonlinear regulation and storage model of the underground water storage reservoir to simulate a base flow hysteresis release effect; calculating a landscape fragmentation degree and a connectivity index, and establishing a mapping relation between a space structure and a hydrological process; constructing an ecological water demand quota correction matrix based on nonlinear regression; and outputting a final water demand calculation result in combination with the base flow supply sequence and the dynamic landscape parameters. According to the method, by introducing the nonlinear regulation and storage theory and the landscape pattern index, deep coupling and dynamic correction of the ecological water demand and the space structure are achieved, and the precision and scientificity of water demand calculation in the complex environment are improved.

This application provides a method and system for elastic scheduling of containerized resources in a cloud computing environment, relating to the field of elastic scheduling technology for containerized resources. This application generates detailed data recording the resource competition relationships between tenants by acquiring various resource contention events; identifies preset high-frequency conflict patterns through in-depth data analysis, determining specific tenant groups with strong resource mutual exclusion effects; dynamically estimates the probability level of resource conflicts between new containers and specific tenant groups by combining historical contention information and real-time resource load status; generates a dynamic isolation scheduling strategy based on the conflict risk indicated by the probability level; and configures and adjusts independent conflict buffer resource pools for designated key tenants. This enables the identification of tenant resource conflict patterns and the implementation of dynamic isolation scheduling and buffer resource configuration, improving the resource utilization efficiency and system stability of multi-tenant containers in a cloud computing environment.

The present application relates to a tire rubber performance detection method, and particularly relates to a method and system for measuring a low-temperature network dissipation index for characterizing the low-temperature rolling energy consumption tendency of rubber tire tread rubber. The present application performs a strain amplitude scanning under constant frequency at T0+ / -DeltaT three temperature points by RPA / DMA, calculates the area type Payne value A(T) of the logarithmic strain coordinate and the temperature derivative thereof at T0, and outputs an index; the mixed area can be normalized or G'' is introduced. Through regression calibration k of the whole tire rolling resistance according to ISO 28580 and a threshold value, fast, comparable and quantifiable prediction of low-temperature energy consumption of the material grade is realized, and the present application is suitable for formula development, incoming material release and process control.

The invention belongs to the technical field of computer data processing and automatic control, and particularly discloses and provides a digital configuration and BIM (Building Information Modeling) mapping fabricated electromechanical facility linkage method, which comprises the following steps of: analyzing a building information model and digital configuration, and constructing an initial weighted mapping network; initial virtual pressure of each node is calculated, conduction and superposition of the pressure in the network are iteratively simulated, and a dynamic pressure distribution diagram representing global risks is generated; and when an anomaly is detected, reverse tracing is carried out along a path with the maximum pressure contribution degree gradient so as to locate a risk source. Furthermore, various candidate control strategies are deduced through simulation, scoring is carried out from multiple dimensions, and the optimal strategy is selected. In addition, by comparing simulation and actual execution effects, deviation data is utilized to adaptively optimize the weighted mapping network and simulation model parameters. According to the method, accurate prediction, rapid traceability, optimal decision and continuous self-learning of the risk of the complex facility system are realized, and the intelligence and reliability of operation and maintenance are improved.

The present application belongs to the technical field of valve cooling system state monitoring and testing, and relates to a valve cooling state early warning method and system based on digital twinning and counterfactual intervention. The present application simulates the running state of a physical valve cooling system by constructing a dynamic digital twin, applies a virtual disturbance signal to identify sensitive disturbances, and then generates a reversible reverse excitation signal to act on the actual system. By comparing the differences between the actual and virtual responses, the digital twin model is corrected to improve the prediction accuracy. The system uses the calibrated digital twin to simulate future state deduction and maintenance, generates predictive risk trends and recommended intervention strategies, and realizes accurate early warning and intelligent decision-making. The present application improves the test sensitivity and predictability, changes the correlation analysis to causal positioning, improves the accuracy and reliability of fault diagnosis, provides a quantitative basis and optimization strategy for equipment maintenance, and realizes the leap from state perception to intelligent decision-making.

Picking up a food product from a pick up area and release it from a releasing location to a receiving location using a gripper device having a first jaw (101, 201) and a second jaw (102,202), each having a leading edge (104, 105), the jaws being configured to be moved by a moving mechanism (103) relative to each other from a gripping position to an open position where there is a suitable opening between the leading edges so that the food product (209) may be controllably released from the gripper device (100), and vice versa, by moving the gripper device to a gripping position and picking up the food product, followed by moving the gripper device to the releasing location and releasing the food product at the releasing location to the receiving location by means of moving the first jaw (101, 201) relative to the second jaw from the gripping position to the open position such that one side (208) of the food product (209) is un-supported from the first jaw (101,102) while an other side (207) of the food product (209) is temporarily resting on the second jaw (102,202) so as to cause a tilting of the food product around a longitudinal axis (205) of the food product (209) when releasing the food product to the receiving location.

The invention discloses a stack space static distribution method in a battery management system and the battery management system, relates to the technical field of battery management, and aims to solve the problem of shared stack peak value superposition caused by sudden fault trigger diagnosis deep call under static stack division and periodic monitoring interruption concurrence. A stack description table is generated in a compiling and linking stage, and a stack pointer is redirected according to an execution entity during operation, so that monitoring type and diagnosis type execution streams are operated on a physically isolated stack space, the stack expansion of one execution stream is prevented from occupying the stack frame of the other execution stream, and the stack overflow risk caused by instantaneous resource conflict is weakened from the source; a stack switching mechanism of an interrupt preamble code is introduced, so that an interrupt service routine is executed on a pre-planned interrupt stack storage area, and when the interrupt exits, the interrupt service routine is recovered to a stack to which an interrupted execution stream belongs, so that interrupt stack occupation is converted from scattered superposition to task stacks to centralized planning to interrupt stacks.

This invention discloses a method for monitoring low-altitude targets in substations based on 5G-A integrated sensing technology, belonging to the field of integrated sensing security technology. The method includes: acquiring an electronic map and key equipment location information of the substation to construct a three-dimensional semantic map of the substation area; combining the kinematic features of a unique low-altitude target's continuous trajectory with the functional semantic annotations of key equipment in the three-dimensional semantic map of the substation area to perform behavioral pattern recognition and intent understanding on the unique low-altitude target, outputting target type labels, intent labels, and corresponding threat levels; comparing the target type labels, intent labels, corresponding threat levels, and the unique low-altitude target's continuous trajectory with an electronic fence to generate graded alarm events and countermeasure suggestions, and issuing linkage commands to defense equipment and a linkage platform to trigger corresponding actions. This invention achieves accurate mapping from target behavior to threat intent by extracting kinematic features and functional semantic annotations, improving the ability to recognize and predict hidden risks.

This invention discloses a high-strength passive daytime radiation cooling film and its preparation method, belonging to the field of functional polymer materials and thermal management technology. The film has a bilayer composite structure, including an upper reflective layer and a lower emitting layer. This invention employs an integrated process of melt blending-lamination-biaxial stretching-induced phase separation-extraction pore-fixing. Through a process design of stretching followed by extraction and a hierarchical biaxial stretching strategy, it achieves highly oriented molecular chains to enhance mechanical properties while precisely constructing a multi-level structure with both nanopores and micropores. The resulting film exhibits an average reflectivity >93% in the solar radiation band (0.25–2.5 μm), an average emissivity >95% in the atmospheric window (8–14 μm), a thermal conductivity <0.1 W / (m·K), and a tensile strength >30 MPa. This invention solves the technical bottleneck of achieving high reflectivity, high emissivity, low thermal conductivity, and high strength simultaneously in radiation cooling materials, and can be widely applied in building energy conservation, outdoor equipment thermal management, and electronic device heat dissipation.

The present application relates to the technical field of medical equipment, and more particularly to a pancreatic anastomosis intelligent negative pressure drainage system for pancreatic fistula monitoring, which comprises: a baseline construction module for constructing an individual reference baseline data set within a preset time period; an enzyme concentration detection module for detecting whether the pancreatic amylase concentration in the drainage fluid exceeds an abnormal trigger threshold; a tube state identification module for determining a tube state identification result through tube state visual identification and flow rate consistency verification when the enzyme concentration abnormal duration exceeds a threshold; a saturation compensation module for extracting the plateau of the pancreatic amylase concentration curve and judging whether the saturation sequence of each detection point meets the requirements; and a correction module for correcting the initial negative pressure when the saturation sequence requirements are not met. Through the cooperation of multiple modules, the present application realizes real-time and accurate monitoring of the pancreatic anastomosis fistula, improves the reliability and response speed of postoperative complication identification, and provides intelligent drainage state judgment and early warning support for clinical use.

This invention discloses a method and system for anisotropic patterning correction of wafer warpage, comprising: obtaining the target anisotropic curvature compensation value of the wafer to be corrected; calculating the target equivalent thin film stress value to be achieved by the stress balance layer based on the curvature compensation value, the mechanical parameters of the wafer substrate, and the preset thickness of the patterned stress balance layer; determining the geometric parameters of the patterned stress balance layer using a quantitative relationship model, based on the target equivalent thin film stress value, the intrinsic stress of the selected thin film material, and Poisson's ratio; and fabricating a corresponding patterned stress balance layer on the back side of the wafer to complete the warpage correction. By designing the patterned stress balance layer, the anisotropic control of the overall thin film stress state of the back stress layer can be achieved; curvature compensation, both in magnitude and direction, can be independently designed for warpage differences in different directions of the wafer, thereby adapting to and correcting various complex asymmetric warpage morphologies.

The invention relates to the field of equipment monitoring, in particular to a real-time monitoring method and device for low-temperature processing equipment, the equipment and a storage medium. The method comprises the following steps: performing core cavity operation monitoring and equipment health quantitative evaluation on the low-temperature processing equipment, and generating an operation state rating report; setting a dynamic replacement temperature threshold based on the operating state rating report; performing thermal imaging monitoring on the cutter in the cavity according to the thermal infrared imager, and constructing a temperature rise distribution diagram; performing temperature rise differential calculation based on the temperature rise distribution diagram, and outputting a dynamic correction curve; and on the basis of the dynamic replacement temperature threshold, performing cross identification on the dynamic correction curve, and when it is detected that the platform clock reaches the tool replacement time point, triggering a tool replacement early warning signal. Machining stability, equipment safety and cutter life management are improved.

The present application relates to the technical field of big data, and particularly to a health insurance automatic pricing system based on big data, in which, through a multi-source heterogeneous data acquisition module, sleep depth, health behavior and living environment data are integrated in real time to solve the problem of single data dimension of traditional health insurance; a dynamic health portrait construction module adopts dynamic weight distribution and space-time alignment technology to unify multi-granularity data into a weighted daily dimension vector, eliminating the difference in data value evaluation and the fragmentation of time granularity; based on this, real-time dynamic health risk scores are generated and health behavior entropy values are extracted to quantify behavior stability, breaking through the limitations of static risk assessment; a risk transmission prediction module identifies and maps the disease development rate through the entropy value abnormal duration, constructs a personalized risk evolution path diagram, and finally converts the risk escalation node into an actuarial factor to dynamically generate a ladder-type premium gradient, realizing the accurate matching of premium level and user real-time risk trajectory.

The invention discloses an enterprise human resource management evaluation method and system. The method comprises the following steps: acquiring, analyzing and evaluating management process data to obtain an index evaluation value of each preset monitoring index; determining a weight corresponding to each preset monitoring index, and performing calculation based on the weight and the index evaluation value to obtain an initial evaluation value of enterprise human resource management; obtaining management result data of the enterprise for analysis, and determining result parameter data related to enterprise human resource management; evaluating the enterprise human resource management result based on the result parameter data to obtain a management result evaluation value, and determining a correction coefficient based on the management result evaluation value; and correcting the initial evaluation value based on the correction coefficient to obtain a comprehensive management evaluation value. According to the invention, the transformation of human resource management from an empirical type and qualitative type to a data type and quantitative type is realized, an intelligent evaluation system capable of self-calibration and continuous optimization is established, and powerful technical support is provided for enterprises to improve the human resource management level.

The application discloses a new energy county area power grid frequency voltage cooperative enhancement system and method, relates to the technical field of new energy power grid. The method comprises the following steps: collecting real-time operation parameters of the county area power grid for mode recognition to obtain a current operation scenario label; calling frequency regulation rule fragments and voltage regulation rule fragments matched with the current operation scenario label to construct an initial regulation rule sequence; performing multi-domain constraint calculation on the sequence to establish a frequency-voltage linkage coupling relationship and generate an optimized regulation rule sequence; calculating an influence echo index between regulation actions, and selecting an inhibition type replacement rule fragment to correct the optimized regulation rule sequence when the influence echo index exceeds a preset echo threshold; and performing consistency review on the corrected regulation rule sequence, and triggering a rollback and a replacement branch when the consistency review fails, wherein if the replacement branch is unavailable, a minimum offset solution is performed to generate a final regulation rule sequence. The application significantly improves the stability and reliability of new energy county area power grid operation.

The application discloses an intelligent security management method based on artificial intelligence and relates to the technical field of security management.The intelligent security management method based on artificial intelligence comprises the following steps: S1, traffic congestion evaluation;S2, traffic signal fault evaluation;S3, traffic management evaluation; and S4, emergency security feedback.The traffic congestion index obtained through traffic data is used to determine whether to perform traffic signal fault evaluation, then the traffic signal fault index obtained based on traffic signal data is used to determine whether to perform traffic signal management, then the traffic management effective index obtained based on management data is used to determine whether to implement an emergency security strategy, and finally, the traffic management effective index obtained after the implementation of the emergency security strategy is used to determine whether to perform feedback, so that the effect of improving the security management efficiency of road traffic is achieved, and the problem that the state change of a traffic signal is not fully considered in the security management of road traffic in the prior art is solved.

The application relates to the technical field of power distribution, in particular to an AIDC load bus power supply management system. In the application, an admission control algorithm converts concurrent access behavior into a calculable and filterable controlled event, suppresses power superposition risk caused by instantaneous concurrency, forms a deterministic access sequence through time sequencing, adopts a finite state machine to perform explicit identification and switching control on a power stage after entering a power release stage, and makes the power change path have state continuity, avoids non-continuous jumps of power setting between different stages, limits a single period increment in combination with a stage power upper limit, a change rate and a duration, and makes the power release change from result constraint to process constraint. Joint discrimination is performed on a branch power accumulation and a peak value limit and a voltage interval on the bus side, and level and order participate in disposal decision, so that the pruning behavior has priority consistency and traceability.

The invention discloses a container repairing method and device and electronic equipment. The method comprises the following steps: acquiring load monitoring data of a container; the load monitoring data is analyzed by inputting a convex long short-term memory network IC-LSTM to obtain load prediction data, the IC-LSTM is provided with a non-negative weight constraint and a convex activation function, the non-negative weight constraint is used for performing non-negative constraint on the model weight of the IC-LSTM, and the convex activation function is used for performing convex activation on the model weight of the IC-LSTM; the convex activation function is used for maintaining a monotonic change relationship between the load prediction data and the load monitoring data; and determining an abnormal detection result of the container according to the load prediction data and a preset threshold value, and repairing the container according to the abnormal detection result. The technical problems of weak multi-dimensional data relevance, insufficient fault prediction capability and poor container scene adaptability existing in a container operation and maintenance method in related technologies are solved.