430results about How to "Improve responsiveness" patented technology

The invention relates to the technical field of virtual power plant resource configuration, and discloses a virtual power plant resource dynamic coordination configuration method and system, and the method comprises the following steps: collecting the operation data of various resources in a virtual power plant and the external power grid environment data in real time, and carrying out the dynamic coordination configuration of the resources based on the operation data; extracting operation characteristic parameters reflecting response speed differences of various resources; clustering analysis is carried out on the multiple resources to form resource clusters with different response speed levels, and the collaborative deployment demand intensity of the power grid in the current time period is evaluated; predicting a power grid load balance state in a future target time period, and determining the callable response capability of each resource cluster in the target time period; and carrying out multi-target optimization calculation meeting the stability constraint of the power grid, and generating a dynamic coordination configuration scheme of various resources in the target time period. According to the method, through the synergistic effect of multi-level technical characteristics, the matching problem between resource characteristic differences and dynamic requirements is fundamentally solved.

The invention discloses a design manuscript code generation and visual error iterative correction method and system based on multi-agent cooperation, and aims to solve the problems of low front-end code generation efficiency, poor visual restoration degree and lack of an automatic correction mechanism in the prior art. The system constructs a four-node state diagram based on LangGraph, automatically initializes a series engineering scaffold, obtains design data and generates a structured protocol, and generates a component code based on the protocol and performs visual verification and iterative correction on four processing nodes. The method comprises the following steps: dynamically generating an engineering scaffold through a large language model agent, converting Figma design data into a structured protocol, and carrying out iterative optimization by utilizing a judger-repairer mode until an error is lower than a threshold value; according to the method, high-fidelity automatic delivery from the design manuscript to the code is realized, and the executable front-end engineering code and the visual reduction degree analysis report are output.

The invention discloses a short-term wind power prediction method and system based on a dynamic graph neural network, and belongs to the field of wind power prediction. Dividing a power sequence into a high-frequency fluctuation set and a low-frequency stationary set by using VMD-CEEMDAN joint decomposition and SSA clustering optimization; a DGAT module is adopted to fuse geography, data and learnable prior, a local sub-graph is dynamically constructed to extract spatial features, meanwhile, a multi-scale convolution block is utilized to parallelly capture high-frequency mutation and low-frequency trends through an MS-TCN module, multi-scale time features are generated, time feature fusion is guided through space and geography combined representation, and time feature fusion is realized. Collaborative modeling of multi-source heterogeneous data is achieved, finally fusion features are input into a full-connection layer to predict fluctuation set prediction power, the prediction power is combined with stationary set prediction power, and a short-term wind power prediction value is output; according to the method, the modeling capability of wind power plant complex association is remarkably improved, and reliable support is provided for real-time scheduling of a power grid.

The invention discloses an intelligent trash-cleaning machine based on AI visual identification, and belongs to the field of visual identification, the intelligent trash-cleaning machine comprises an AI visual identification module, an intelligent control system and a rotary trash-cleaning execution mechanism, the AI visual identification module is in communication connection with the intelligent control system, and the intelligent control system is electrically connected with the rotary trash-cleaning execution mechanism; through cooperative work of the AI visual recognition module and the intelligent control system, precise recognition and efficient cleaning of dirt in water are achieved, and compared with a traditional dirt cleaning mode, the system has remarkable advantages. The method is excellent in recognition capability, sewage disposal efficiency, response speed, adaptability and the like, and can be widely applied to pretreatment scenes of pump station water inlets, urban river channels, reservoir spillways, sewage treatment plants and the like. Popularization and application of the trash remover can bring good economic, social and environmental benefits, powerful technical support is provided for water area treatment, and the trash remover has wide market prospects and development potential.

The invention provides a fine configuration method and system based on a strategy mode, and the method comprises the steps: defining themes used for abstracting entrance traffic, order distribution and other events through a configuration system, and configuring a basic data source and a data processing rule for each theme, wherein the data processing rule supports a user to carry out code development implementation in a basic class of each service line according to service requirements; the system automatically stores theme data to middleware, matches a corresponding theme through a strategy mode after receiving a user request, performs secondary data processing according to a configuration rule and returns a result; the technical effects of flexible configuration mode, quasi-real-time index calculation, support of multi-source data access, high-concurrency scene adaptation and good expansibility in flow fine management are realized, and the service operation demand change can be quickly responded.

The invention belongs to the technical field of truss girder hoisting, and particularly relates to intelligent hoisting equipment for a suspension bridge truss girder in an extreme wind environment and a hoisting construction method.The intelligent hoisting equipment comprises a floating crane, and a hoisting tool component is fixedly installed at the lower end of a steel wire rope of the floating crane and comprises a posture adjusting device and an offset adjusting device. According to the intelligent hoisting equipment for the suspension bridge truss girder in the extreme wind environment and the hoisting construction method, by arranging the sling component and integrating the posture adjusting device and the offset adjusting device, multi-degree-of-freedom active adjustment can be conducted on the hoisted truss girder. The offset adjusting device generates reverse inertia force by driving the mass block to move, so that horizontal swinging of the truss girder caused by wind load is effectively counteracted; the posture adjusting device accurately corrects pitching and rolling postures of the truss girder by adjusting the length of the steel wire rope set, and therefore the overall wind resistance stability and posture keeping capacity of the hoisting system are remarkably enhanced in the extreme wind environment.

The invention discloses an immersive cinema dynamic content adaptation control method based on multi-modal fusion, and the method comprises the steps: collecting at least one non-contact physiological signal of a target audience seat area in real time, the physiological signal comprising a respiratory wave signal collected by a millimeter wave radar or a photoplethysmography signal collected by a near-infrared photoelectric sensor; performing time-frequency analysis on the physiological signal, and extracting a physiological wake-up characterization value in a current time window; the physiological wake-up characterization value comprises a heart rate variability change rate and a heart rate deviation value; constructing a dynamic damping adjustment model, and calculating a virtual damping coefficient of the seat movement system at the current moment based on the physiological wake-up characterization value; and the virtual damping coefficient is converted into an execution instruction of a seat motion controller, and damping force output of the motion platform is adjusted in real time. The technical problem that the pre-programmed motion feedback is disjointed with the real-time physiological and psychological state of the audience can be solved, the experience adaptability and comfort of the cinema seat are improved, and the system safety is improved.

The invention provides a Kubernetes-based large model reasoning optimization method, system and equipment, and the method comprises the steps: constructing a resource scheduling assembly for a large model, and monitoring a real-time resource state at a current moment; constructing a batch processing agent component for the large model, performing feature analysis on the received reasoning request queue, and determining request features corresponding to the reasoning requests in the reasoning request queue; the real-time resource state is evaluated according to the request features, and the batch processing size is adjusted based on the evaluation result to generate the optimal batch processing length; batching the reasoning requests in the reasoning request queue according to the optimal batch processing length, and packaging each batch of reasoning requests into batch data; the resource scheduling component is utilized to distribute batch data to Pod in the K8s cluster for reasoning, a large model reasoning result is obtained, the quantity of the reasoning Pod is automatically adjusted according to the flow and the resource load required by reasoning, a GPU with poor performance is prevented from becoming a system bottleneck, and the responsiveness and the stability of service are improved.

The invention relates to a Keystone-based deep ground security heterogeneous data fusion method and system, and the method comprises the steps: deploying a Keystone trusted execution environment on a deep ground edge computing node, creating a security enclave, carrying out the encryption access of multi-source heterogeneous data on the basis of remote authentication and key agreement, completing the space-time alignment and feature extraction after decryption in the enclave, and carrying out the fusion of the multi-source heterogeneous data. And performing cross-modal association analysis and risk assessment based on a preset model or a rule engine to obtain a fusion result, encrypting and signing the fusion result in the enclave, distributing the fusion result to an authorized receiver through a secure channel, and realizing one-time task destruction, long-term task cycle reconstruction and key refreshing in combination with enclave full life cycle management. According to the method, the credibility and the real-time performance of heterogeneous data fusion processing in a complex scene can be improved while the confidentiality and the integrity of deep operation and maintenance data are guaranteed.

The present application relates to a kind of preparation methods of essence.The problems that traditional process parameter adjustment relies on artificial experience and is difficult to realize cross batch self-adaption, multi-modal feature extraction, parameter-function-stage three-dimensional label matrix generation, graph neural network behavior atlas construction and expert strategy distribution constraint dual-channel strategy learning method are proposed.By process parameter and derived feature multidimensional fusion, time series causal strength analysis and action instruction simulation verification, optimization process parameter combination with explainable function synergistic relationship can be output.The technical scheme effectively realizes the automatic optimization of process control decision and the rapid self-adaption of model under new raw material batch, improves product consistency, quality stability and control energy efficiency.

The invention aims to provide a single needle valve type high-response methanol-diesel injector based on opposed electromagnetic valve control, and belongs to the field of engines. Opposite type double-medium channel control assemblies are installed in an ejector connector body, an ejector middle body and an ejector throttling block, a methanol / diesel shared nozzle assembly is installed in a nozzle body, a diesel connector and a methanol connector are installed on the side of the ejector connector body, a high-pressure diesel channel is arranged in the diesel connector, and a high-pressure methanol channel is arranged in the methanol connector. Free connection and disconnection of an internal high-pressure methanol path and an internal high-pressure diesel path can be controlled, then independent injection of methanol fuel and diesel fuel is achieved, the two fuel injection modes are controlled through the same needle valve, the fuel is injected through the same injection hole, and the advantages of being high in reliability and simple in structure are achieved. And after methanol / diesel oil injection is finished, rapid cut-off of an internal passage of the injector and rapid seating of the needle valve can be achieved, and the response characteristic of fuel injection mode switching of the injector is improved.

The application relates to a proportional valve control method, system, device and storage medium, which comprises the following steps: obtaining the opening degree of the proportional valve; judging whether the opening degree change of the proportional valve belongs to a critical stage based on the change trend of the opening degree of the proportional valve, wherein the critical stage is a stage in which the opening degree of the proportional valve changes between being closed and being critically opened or a stage in which the opening degree of the proportional valve changes between a maximum opening degree and a critical maximum opening degree; when the opening degree change of the proportional valve belongs to the critical stage, a preset fixed duty ratio and a frequency change signal are used to control the opening degree of the proportional valve; and when the opening degree change of the proportional valve does not belong to the critical stage, a preset fixed frequency and a duty ratio change signal are used to control the opening degree of the proportional valve. The application can solve the problem of reduced control precision caused by flow hysteresis difference in the opening degree control of the proportional valve in the prior art.

The utility model relates to the technical field of man-machine interaction of electronic equipment, and particularly discloses a backlight touch key. The backlight touch key comprises a shell and a plurality of key assemblies, each key assembly comprises a key unit and a touch conduction unit, and each key unit is provided with a first end and a second end which are opposite to each other; the first end is embedded in the shell, the key unit penetrates through the touch conduction unit, the outer surface of the touch conduction unit is provided with a capacitive sensing surface, the capacitive sensing surface is attached to the shell, and the relative position of the shell and the touch conduction unit is fixed. According to the backlight touch key, the specific structure is improved, so that high integration of the structure and simplification of the manufacturing process are realized while the backlight uniformity and the induction sensitivity are ensured.

The invention discloses a biological agent for preventing and treating panax notoginseng root rot, and relates to the technical field of biological prevention and treatment, the biological agent is composed of four layers of functional florae: an A layer of sentinel-decoding flora is used for identifying a pathogen quorum sensing signal and is used as an event trigger source, a B layer of metabolic countering flora is used for decoupling conversion of disease-promoting saponin and controllable release of a metabolic false substrate, and a C layer of functional florae is used for controlling root rot of panax notoginseng. The C-layer self-healing conductive biological membrane construction flora forms a biological membrane with conductivity and self-healing capability on the root surface, and the D-layer electrically-enabled flora constructs stable biological micro-current at the rhizosphere by using ferric oxide particles as external electron acceptors. The layer A triggers to cause controlled release of the layer B, a conversion product of the layer B provides a carbon source and a structural unit for the layer C, and a conductive network of the layer C and the layer D form an electronic path. The biological agent is used for early recognition and continuous inhibition of pathogens in panax notoginseng planting soil, can start defense response in the early stage of quorum sensing signal occurrence, and keeps action stability under complex environmental conditions.

The utility model discloses a kind of melting mixing devices for plastic product processing, including mixing shaft, multiple blades are equipped with outside mixing shaft, moving device is arranged outside mixing shaft, protective device is connected with the top of mixing shaft, protective device includes control sleeve, displacement spring, clamping groove, connecting rod, displacement sleeve, connecting sleeve, displacement slot, clamping block, displacement block and card frame, displacement spring is connected with clamping block and displacement block, clamping groove is opened in the outside of connecting rod, displacement sleeve outer wall is connected with the inner wall of control sleeve by thread, displacement slot is opened in connecting sleeve, clamping block is arranged in one side of card frame, locking mechanism is installed in the outside of connecting sleeve, and locking mechanism includes rotary hole, rotating plate, sliding sleeve, movable spring, fixed block, movable block and support rod, rotary hole is opened on rotating plate, support rod is connected in one side of sliding sleeve, the utility model solves the technical defects of existing equipment in cleaning maintenance difficulty, power transmission system lacks effective protection and adjustable overload protection mechanism poor stability etc.

The invention discloses an execution method and device of an early warning event, a medium, electronic equipment and a product, the execution method of the early warning event comprises the steps that log data, collected through a preset collection strategy, of a client is acquired, the log data comprises multi-dimensional operation data, and the multi-dimensional operation data comprises network performance data and system resource data; performing anomaly analysis on the log data through a large language model to determine a trend type of an anomaly trend existing in the log data, the trend type including at least one of memory overflow, security attack, high concurrent traffic and response delay; and determining an early warning level of the client according to the trend type, and executing an early warning event on the client according to the early warning level. The problems that in a distributed system, a monitoring scheme for a client depends on fixed log collection and regular health examination, so that anomaly detection lags behind, and an active early warning mechanism is lacked are solved.

This invention discloses an electromechanical braking system and its control method based on heterogeneous motor redundancy, relating to the field of brake-by-wire technology for new energy vehicles. The system includes the following steps: During vehicle braking, a permanent magnet synchronous motor (PMSM) acts as the main drive source, outputting braking torque, while a switched reluctance motor (SRM) operates in standby or low-power auxiliary mode, forming a heterogeneous motor redundant drive structure. This invention achieves complementary failure modes and reduces the risk of common-mode failures by employing a heterogeneous redundancy structure of a PMSM and a SRM; simultaneously, it optimizes system economy by utilizing the low cost and low standby energy consumption characteristics of the SRM. A deep learning health prediction model is introduced to achieve early fault prediction and proactive switching, and a rapid, seamless switching mechanism within 20ms ensures braking continuity and system safety.

The invention relates to the technical field of three-dimensional data processing, and discloses a three-dimensional grid data processing and multiplexing method and system, and the method comprises the steps: S1, obtaining and analyzing grid data, obtaining three-dimensional grid original data, and carrying out the format recognition, geometric analysis and topology analysis of the three-dimensional grid original data; s2, carrying out reuse-oriented standardization processing; s3, constructing multiplexing description information; s4, grid resource storage and index management; s5, determining a subset based on the request; s6, on-demand conversion and result generation; and S7, unified scheduling control. By constructing multiplexing description information containing a unique identifier, a hierarchy mapping relationship, a block mapping relationship, version information and a service adaptation mark, unified management and efficient multiplexing of grid data under different hierarchy and service scenes are realized, and unified data semantic support is provided for hierarchical retrieval, on-demand extraction and multi-service collaboration; therefore, the reusability of the three-dimensional grid data and the system cooperation efficiency are remarkably improved.

The invention discloses a Spring framework timed task multi-thread optimization method. The method comprises the following steps: newly establishing a native spring timed task item; a class A is newly created, a Boolean type member variable Execute of the class A is newly increased, and a set method of the member variable is newly increased; configuring a trigger thread pool P1 of the timed task: newly establishing a class B, and marking a Configuration annotation (at) and an EnableAsync annotation (at) on the class B; and configuring an execution thread pool P2 of the timed task: newly establishing a class C, and annotating and registering the class C to a spring container by using a (at) Component. The invention provides a method for improving a (at) Scheduling annotation in a Spring framework. The method is used for improving the performance and resource utilization of a timed task. According to the method, a multi-thread execution and intelligent task scheduling strategy is introduced, so that the timed task management function of the Spring framework is enhanced.

The present application relates to a kind of systems for improving the thermal efficiency of underwater transport platform fuel cell auxiliary system, including water circulation pipeline consisting of fuel cell stack, alloy hydrogen storage tank assembly, circulating water tank and circulating water pump in series;Hot water delivery pipeline;And, oxygen inlet pipeline and hydrogen inlet pipeline;The water outlet of the circulating water tank is divided into two routes, one is connected with fuel cell stack, another is connected with hot water delivery pipeline;The hot water delivery pipeline includes heating water tank that can provide hot water to fuel cell stack, and heating device in heating water tank and heat release by chemical reaction.The present application provides suitable circulating hot water in the temperature range of fuel cell stack and alloy hydrogen storage tank assembly by chemical reaction of heating agent and water heat release for fuel cell system when cold start, high-power variable load and continuous high-power operation, without increasing power consumption, so that the efficiency of the whole system is improved by more than 10%.

The invention discloses a determination method for acquiring a denitrification rate based on river dissolved oxygen high-frequency monitoring. The determination method comprises the following steps: S1, constructing a dynamic response model of the river denitrification rate to heterotrophic respiration; s11, carrying out in-situ high-frequency DO observation on different types of rivers, collecting a water sample, and measuring the concentrations of dissolved N2 and O2 in the collected water sample by adopting an MIMS technology; s12, on the basis of the O2 concentration data, the river heterotrophic oxygen respiration rate is calculated through an O2 mass balance model; s13, based on the N2 concentration data, calculating the river denitrification rate through an N2 mass balance model; s14, fitting the obtained series of heterotrophic respiration rates with the denitrification rate to obtain a dynamic response model between the denitrification rate and heterotrophic respiration; and S2, based on field real-time high-frequency monitoring dissolved oxygen observation data, simulating the river denitrification rate through the constructed dynamic response model. According to the invention, the problems that the traditional denitrification rate measurement cost is high and real-time continuous monitoring cannot be realized are solved, and in-situ, real-time and high-frequency monitoring of the denitrification rate is realized.

The invention discloses an automobile demand prediction method and system based on large model time sequence cross-modal alignment, and belongs to the technical field of automobile demand prediction. The automobile demand prediction method based on large model time sequence cross-modal alignment comprises the following steps: acquiring time sequence data and prompt data related to a hydrogen fuel cell automobile; inputting the time sequence data into the time sequence coding branch in a reverse embedding manner to generate a time sequence embedding representation; inputting the prompt data into an LLM enhanced coding branch for coding, and generating a prompt embedding representation; and calculating a channel-level similarity matrix between the time sequence embedding representation and the prompt embedding representation, aggregating to the time sequence embedding representation based on the channel-level similarity matrix, generating an aligned cross-modal feature, and generating a demand prediction result of the hydrogen fuel cell vehicle based on a decoder. According to the method, multi-source heterogeneous information is effectively fused, the precision and robustness of demand prediction of the hydrogen fuel cell vehicle are improved, and the capability of responding to emergencies caused by external factors is enhanced.

The carbon dioxide responsive liquid crystal film containing amidine compound is formed by a cholesteric liquid crystal polymer capable of reflecting visible light and an amidine compound, and the film is prepared from the amidine compound, cholesteric liquid crystal monomer, crosslinking agent, chiral dopant, photoinitiator and porogen, and the amidine group in the amidine compound reacts with carbon dioxide to increase the hydrophilicity of the polymer network, and when water penetrates into the film, the light reflected by the film is red-shifted and the color is changed accordingly. The carbon dioxide responsive liquid crystal film prepared by the application has stable color change effect, obvious response effect, is easier to distinguish, is still reversible after multiple cycles, and the performance of the film is maintained well after multiple cycles.

This disclosure provides a photodetector. The detector includes a substrate and, sequentially stacked on the substrate surface, an N-type doped layer, an absorption region, a P-type doped layer, and a converging structure. The first cross-sectional area of ​​the absorption region along the direction parallel to the substrate surface is smaller than the second cross-sectional area of ​​the P-type doped layer parallel to the substrate surface; the surface of the P-type doped layer away from the absorption region is a photosensitive surface. The converging structure is used to focus incident light from the photosensitive surface to the absorption region, so that the photodetector converts the incident light into an electrical signal. This detector can simultaneously achieve high responsivity and high bandwidth.

The application provides a provincial meteorological and administrative collaborative wind speed prediction method based on dynamic federal learning, relates to the cross technical field of artificial intelligence and energy meteorology, S1, basic data of N meteorological monitoring stations in a province is acquired, is divided into M initial subgraphs according to the administrative boundary of a prefecture-level city and is allocated an edge server, each collaborative subgraph pair is determined according to the Pearson correlation coefficient of the wind speed sequence of the station, the time sequence data deviation of the synchronized subgraph is synchronized through a dynamic time warping algorithm after every 3 rounds of federal iteration, and the subgraph data after synchronization is output. Through an endogenous decision and optimization framework, three links of dynamic coordination of cross-domain collaboration, local learning and gradient transmission are coordinated, and finally a global optimal provincial meteorological and administrative collaborative wind speed prediction method based on dynamic federal learning is achieved among multiple targets such as prediction accuracy, convergence speed and communication cost.

The present application relates to the technical field of image state recognition, in particular to a kind of based on pattern recognition's picking and replacing hook AI accurate identification and capture system and method, in the present application, the outline change of hook assembly in image sequence frame, boundary difference and gray dynamic are carried out node construction, and combined with edge displacement accumulation analysis, while through graph neural network, cosine value between nodes and coordinate difference are compared jointly, construct path jump sequence, to enhance the response sensitivity of state mutation, under the condition of complex background interference or local occlusion, still can stably extract the key path of morphological evolution, effectively improve the anti-interference and fault tolerance of spatial path recognition, further statistical modeling is carried out on state rate mutation point by hidden Markov model, by matching standard state mode, paragraph merging and invalid segment rejection operation are carried out to abnormal point section, construct state label sequence, realize the accurate division of high confidence, multi-section continuous state.

The application relates to the technical field of automobile transmission shaft production, in particular to a safety management system for automobile transmission shaft production based on big data, which comprises a data acquisition module, which is used for collecting production parameter data, environment parameter data, operator behavior data and quality inspection data of multiple production devices in the automobile transmission shaft production process in real time, and constructing an original safety data set; a big data processing platform, which is in communication connection with the data acquisition module, is used for cleaning, fusing and standardizing the original safety data set, and generating a standardized safety data set; a safety risk research and judgment module, which is connected with the big data processing platform, is used for storing a dynamic safety threshold model, and identifying abnormal states and safety risks in the transmission shaft production process in real time based on the standardized safety data set, and outputting quantitative research and judgment results; the safety risk research and judgment module realizes the whole domain monitoring, hierarchical early warning, millisecond-level emergency shutdown and closed-loop control of the transmission shaft production safety, and significantly improves the response speed and management efficiency.

A fast-response temperature and humidity sensor includes a humidity-sensitive material, a cylindrical frame disk, a temperature sensor, and an MCU with on-chip ROM. The frame disk has multiple deep-groove air channels evenly distributed around its perimeter. The frame disk has a socket for fixing the temperature sensor, which is electrically connected to the microcontroller. The temperature sensor measures the ambient temperature around the temperature and humidity sensor, and the MCU performs temperature correction on the humidity measurement value. The MCU's on-chip ROM stores a standard database containing multiple humidity-sensitive resistance (R)-humidity (H) curves of the fast-response temperature and humidity sensor at different temperatures (T). Based on the measured temperature value (T) and resistance value (R), the MCU looks up the corresponding humidity value (H) in the standard database.

This invention relates to a miniature photoacoustic probe and monitoring system for in-situ monitoring of dissolved gases in oil. The miniature photoacoustic probe includes a pump fiber, a pump fiber ferrule, a probe fiber, an acoustic transducer film, and an oil-gas separation membrane. The pump fiber ferrule has an inner hole, and the light-emitting end of the pump fiber is positioned at a predetermined distance from the first side of the acoustic transducer film, forming a gas photoacoustic cavity in the local space between the inner hole and the ferrule. The pump fiber ferrule also has a gas guiding channel for introducing the gas to be measured, separated by the oil-gas separation membrane, into the gas photoacoustic cavity. The end face of the probe fiber and the second side of the acoustic transducer film form a Photonic Optical Interference Cavity (FP). The pump light excites the gas to be measured within the gas photoacoustic cavity, generating photoacoustic pressure. The acoustic transducer film vibrates under pressure, causing changes in the FP optical interference cavity. This probe can shorten the gas diffusion path and the sound pressure transmission path, improve the response speed, and facilitate in-situ miniaturized gas detection.

This disclosure provides a drought monitoring method and system based on high spatiotemporal resolution water body features, relating to the field of drought monitoring technology. The method includes: acquiring water body remote sensing data and radar data; extracting multi-dimensional optical features from the water body remote sensing data and multi-dimensional radar features from the radar data; training random forest models based on the multi-dimensional optical and radar features respectively to generate optical and SAR water body probability maps; constructing comprehensive features based on the optical and SAR water body probability maps, inputting the comprehensive features into a water body probability discrimination model to generate the final water body probability map; and based on the water body probability map, introducing a hydrological-meteorological nonlinear coupling relationship and time-lag effect to construct a hydrological-meteorological coupled drought index and performing multi-objective constraint optimization through a differential evolution algorithm to achieve drought severity classification. This disclosure improves the accuracy, timeliness, and response capability to extreme events in drought monitoring.