67results about How to "Break the limitations" patented technology

The invention provides an obstacle association method and device, computer equipment and a storage medium, and the method comprises the steps: obtaining measurement data from at least one sensor, and enabling the measurement data to comprise a plurality of obstacle measurements and detection information thereof; for each obstacle measurement to be associated, selecting a target reference point type from a plurality of predefined candidate reference point types according to detection information of the obstacle measurement to be associated; determining a measurement reference point from the detection information of the obstacle measurement based on a target reference point type selected for each obstacle measurement; determining a matching measure between a measurement reference point and a track reference point based on the measurement reference point measured by the obstacle and the track reference point determined for the fused track; according to the calculation result of the matching measurement between all the obstacle measurements and all the fused tracks, the association relationship between the obstacle measurements and the fused tracks is determined, and the accuracy and the reliability of obstacle association can be remarkably improved by adopting the method.

The invention provides an anti-semantic interference training method and a semantic communication method based on electroencephalogram joint learning. The method comprises the following steps: applying semantic interference to an original image to generate a disturbance image; respectively inputting the original image and the disturbance image into an image encoder to extract image features, and inputting corresponding electroencephalogram signals into an electroencephalogram encoder to extract electroencephalogram features; and based on the original image features, the disturbance image features and the electroencephalogram features, performing comparative learning through a bidirectional InfoNCE loss function, and updating parameters of an image encoder and an electroencephalogram encoder. Joint comparative learning is carried out through the electroencephalogram signals and the image data, the attention of an image encoder to key information is enhanced by utilizing the characteristics of the electroencephalogram signals, and therefore the robustness of a semantic communication system when the semantic communication system is attacked by semantic noise is improved. According to the method, the semantic interference resistance of a semantic communication system is enhanced based on the natural robust feature of the electroencephalogram signal, and the method is suitable for the complex situation that diversified and multi-type semantic interference exists.

The application provides a kind of underwater structure apparent disease identification method and system based on deep learning, wherein, method includes: according to the combination of fusion model and target recognition model, generate the pre-set underwater structure apparent disease identification model;Underwater apparent disease is identified by the pre-set underwater structure apparent disease identification model;The fusion model is built by improved CycleGAN model and multi-scale Retinex algorithm (MSR) network, for converting underwater image into clear and clear image with obvious features;The target recognition model is obtained by YOLOv5 model, for realizing the positioning and classification of underwater structure apparent disease.The present application solves the problems of inaccurate classification and low recognition accuracy of underwater structure apparent disease by the underwater structure apparent disease identification model, caused by factors such as camera imaging blur, insufficient contrast, dispersion and noise in complex water area.

The present application relates to the technical field of medical devices, and discloses a multifunctional finger rehabilitation training device, which comprises a frame formed by an anti-skid base and a stand column, a hole plate training module installed on the frame, a surface of the hole plate training module being provided with through holes and being internally provided with a pressure sensor array, a grip strength training module, a rotating training module, an electric control module, and a micro-control unit, an analog-digital conversion interface, a storage unit and a communication interface of the electric control module being electrically connected with the pressure sensor array, the displacement sensor and the photoelectric encoder, and the electric control module being used for collecting, calibrating and analyzing training data and storing or transmitting the training data.

This application discloses a blueberry packaging box, including a box body, a mounting tray, a base, and multiple rotatable rollers. The box body is detachably fixed above the mounting tray, and the base and rollers are detachably mounted below the mounting tray. The mounting tray includes a first lug and a second lug, with the first lug located at the front and the second lug at the rear. The first lug has a connecting post, and the second lug has a connecting hole that mates with the connecting post. Thus, on the one hand, users can push the packaging box to roll, increasing interactivity during use and adding fun to the simple packaging function; on the other hand, simply inserting the connecting post of one blueberry packaging box into the connecting hole of another completes the assembly, enabling rapid linkage of multiple identical blueberry packaging boxes, meeting the combination and interaction needs of consumers (especially children), and further expanding the fun of the packaging box.

The application relates to the technical field of plastic intelligent manufacturing, and discloses a machine vision driven plastic master batch feeding and cleaning parameter intelligent regulation and control system. The system comprises the following: an image acquisition and feature extraction module which, based on the equipment running state, identifies and extracts elements such as feeding speed and cleaning flow, maps to a preset parameter field and establishes an associated identifier, and forms a standardized feeding and cleaning data unit. A parameter matching and regulation rule generation module searches a database to match regulation rule conditions, calculates a parameter regulation complexity factor, compares parameters with constraint values, and generates a single parameter matching state judgment. A multi-working-condition correlation modeling module finds different working-condition shared entities, calculates a cross-working-condition correlation closeness index, and constructs a multi-working-condition correlation graph. An abnormal state identification and parameter correction module combines the associated working-condition judgment to calculate a risk score and generates a comprehensive regulation risk prompt. The system realizes intelligent regulation and control and abnormal identification of plastic master batch feeding and cleaning parameters.

This invention relates to a commercially compatible and flexibly deployable OFDM backscatter communication method and system, belonging to the field of wireless communication. This invention enables nodes to perform backscatter communication without deploying synchronization modules, transmitting their own information to a commercial OFDM receiver with low power consumption, thus avoiding the limitation of node deployment range imposed by the sensitivity of synchronization modules. This invention uses a single-carrier signal from the environment as the excitation signal and transmits node information to the OFDM receiver through low-power cross-system conversion from single-carrier to multi-carrier. For the incident single-carrier excitation signal, the node performs low-power replication and shifting of the signal's spectrum during reflection, converting it into an OFDM reflected signal with multi-carrier characteristics. Since the node does not need to synchronize with the excitation signal before reflection, this invention significantly increases the effective operating radius of the backscattering node and enhances node deployment flexibility. Simultaneously, because the node achieves cross-system conversion from single-carrier to multi-carrier OFDM signals, it also possesses the advantage of commercial compatibility.

The present application relates to the technical field of computer vision and human pose generation, and particularly relates to an aesthetic perception pose generation method based on vision and text prompts, which comprises the following steps: obtaining multi-modal input data comprising a no-human scene image, a human specified position, and a text description of human and scene attributes; extracting multi-modal features, and matching an adaptive target pose prototype in a pose prototype library pre-constructed through K-means clustering; generating predicted deformation parameters through a partial-level Transformer variational autoencoder; and finally restoring a 17-keypoint human pose conforming to portrait photography aesthetics, scene and human attribute adaptation. The present application optimizes the pose generation path and model training strategy, reduces the pose generation complexity, improves the matching efficiency, scene adaptability and pose naturalness, enhances the model robustness, generalization ability and expansibility, and comprehensively improves the efficiency, accuracy and aesthetics of pose generation, and adapts to various scenes and multiple requirements.

The application discloses a kind of pathological image classification methods based on dyeing perception intelligent feature modeling, belong to pathological image classification field, this method includes collecting the multi-staining full section image group data of different objects;Multi-staining full section image group data includes H&E dyeing image and several immunohistochemical dyeing images;Each multi-staining full section image group data is respectively preprocessed, obtains the several equal-size image blocks of each object;Based on the image block of each object, graph is constructed, and the multi-modal heterogeneous pathology graph of each object is obtained;With the multi-modal heterogeneous pathology graph of each object as training data, train pathological image classification model;The pathological image classification model of training completion is used to classify the pathological image to be measured.The application solves the problems of the existing method in processing digital pathology graph data, such as node category characteristics, edge information utilization, cross-staining interaction and non-perfect data processing.

The present application relates to a method, device, equipment and medium for verifying the commissioning status of power equipment, and relates to the technical fields of power engineering auditing and artificial intelligence. It includes: parsing the submitted review materials using a multimodal document parsing model; inputting the dispatching operation power time series into a variational autoencoder model for sequence reconstruction calculation to obtain the reconstruction error and generate a time series anomaly feature component; generating a trajectory space anomaly feature component based on the spatio-temporal data of project personnel clock-in and the benchmark coordinates of the equipment ledger, and at the same time performing error level analysis on the on-site commissioning image data to generate an image anti-counterfeiting anomaly feature component; submitting the above multi-source heterogeneous data to a multimodal large model for cross-comparison and logical reasoning, breaking the limitation of only relying on the submitted review materials by a single party, identifying forgery behaviors from the source. With the equipment identifier as the only primary key, in the face of false commissioning scenarios with strong concealment and across multiple links, a multi-dimensional cross-verification closed loop is formed to identify deep造假行为 is misspelled. It should be "deep造假行为 is misspelled. It should be "deep forgery behaviors" here. So the corrected translation is as follows: The present application relates to a method, device, equipment and medium for verifying the commissioning status of power equipment, and relates to the technical fields of power engineering auditing and artificial intelligence. It includes: parsing the submitted review materials using a multimodal document parsing model; inputting the dispatching operation power time series into a variational autoencoder model for sequence reconstruction calculation to obtain the reconstruction error and generate a time series anomaly feature component; generating a trajectory space anomaly feature component based on the spatio-temporal data of project personnel clock-in and the benchmark coordinates of the equipment ledger, and at the same time performing error level analysis on the on-site commissioning image data to generate an image anti-counterfeiting anomaly feature component; submitting the above multi-source heterogeneous data to a multimodal large model for cross-comparison and logical reasoning, breaking the limitation of only relying on the submitted review materials by a single party, identifying forgery behaviors from the source. With the equipment identifier as the only primary key, in the face of false commissioning scenarios with strong concealment and across multiple links, a multi-dimensional cross-verification closed loop is formed to identify deep forgery behaviors.

Embodiments of the present application disclose a picture display method and device, computer equipment and a storage medium, and belong to the technical field of computers. The method comprises the following steps: creating a first color parameter corresponding to a picture, the first color parameter belonging to a first color space, and the first color space being a color space supported by a local device; converting the first color parameter from the first color space to a second color space to obtain a second color parameter, the second color space being a color space of a target display device; and outputting the second color parameter to the target display device, the target display device being configured to display the picture based on the second color parameter. Since the color parameter created by the local device belongs to the first color space, but the color space of the display device is the second color space, the color parameter is converted from the first color space to the second color space, and the corresponding picture is displayed by the display device based on the converted color parameter, so that the display capability of the display device is fully utilized, and the limitation of picture display is broken.

This invention provides a method, medium, and system for fast loading and caching optimization of online map tiles, belonging to the field of map processing technology. The invention establishes a tile index library and exchanges a priority matrix, calculates the viewport movement trend vector based on user swiping operations to predict future viewport range, and filters the list of pre-loaded tiles. It checks the cache validity of tiles and establishes a small change detection vector to determine whether updates are needed. A tile hit rate statistical matrix is ​​established, and a heat score is calculated by fusing time decay factors and spatial correlation factors. A thermodynamic entropy reduction algorithm is used to cluster high-heat tiles in fast-access areas to achieve ordered caching. Furthermore, it predicts the user's next tile demand. This invention solves the technical problem of disordered distribution of cached resources during online map tile loading, which leads to excessively long access paths for high-value tiles and reduces the overall loading response speed.

The present application relates to a kind of computing method for realizing wide range dynamic noise map system fast update, comprising the following steps: using the data information of system database, based on existing day and night period and city road grade, simplify the structure of traditional road sound level mechanism model;Using big data technology, using hybrid modeling method, regression each grade road sound source (day and night) sound level contribution amount prediction model;Road noise fast calculation method based on sound level contribution amount prediction model is constructed, the fast update of dynamic noise map is realized.Compared with prior art, while ensuring the calculation precision, the operation and update efficiency of noise map system is greatly improved, and the technical constraints of foreign core computing software are broken, the localization of noise map core computing technology is realized, which provides technical support for wide range deep development of noise map.

This invention discloses a bidirectional guided fusion method for image information, a target detection method, and a system. The fusion method includes: inputting the image information to be processed into a YOLO model to obtain a shallow feature image from the Backbone network and a deep feature image from the Neck network; decoupling the feature frequency bands of the shallow feature image and the upsampled deep feature image to obtain a shallow high-frequency feature map and a deep low-frequency feature map, respectively; analyzing the semantic information represented by the deep low-frequency feature map to guide the shallow high-frequency feature map to enhance details, resulting in a detail-enhanced image; evaluating the weights of each feature channel using the shallow high-frequency feature map to guide the deep low-frequency feature map to calibrate semantics, resulting in a calibrated image; and fusing the detail-enhanced image with the calibrated image. This invention solves the problems of detail loss and semantic ambiguity in existing target detection networks, especially for small-scale targets.

This invention relates to the field of lithium battery asset management and value assessment technology, particularly a lithium battery asset lifecycle health management and value assessment system. The system comprises a physical asset access layer, a digital twin construction and assessment layer, an economic value mapping and calculation layer, and a strategy generation and closed-loop optimization layer forming a two-way data closed loop, all connected sequentially. The system accesses multi-source heterogeneous time-series data throughout the lithium battery lifecycle, constructs a digital twin coupling an electrochemical degradation mechanism model and a data-driven model, calculates the real-time dynamic economic value vector of the lithium battery, generates operational optimization strategies with the goal of maximizing the asset value throughout the lifecycle, and iteratively optimizes the model through feedback on execution results. This invention achieves deep integration of lithium battery health management and asset value management, and can be widely adapted to the refined management needs of lithium batteries throughout their entire lifecycle in various scenarios.

The invention discloses an unmanned aerial vehicle water-air dual-medium adaptive communication optimization method and related equipment. The method comprises the following steps: acquiring unmanned aerial vehicle environment sensing information; determining the current communication medium state of the unmanned aerial vehicle according to the unmanned aerial vehicle environment sensing information; the communication medium state comprises an air state, an underwater state and a water-air interface crossing state; generating a target communication strategy according to the current communication medium state of the unmanned aerial vehicle, and controlling the unmanned aerial vehicle to execute the target communication strategy; the communication strategies comprise an air communication strategy, an underwater communication strategy and a water-air dual-medium communication strategy; and dynamically monitoring the communication link performance index of the unmanned aerial vehicle, and dynamically optimizing the target communication strategy in combination with the environment change information and the communication link performance index. The technical problem that the communication performance of the unmanned aerial vehicle on the water-air interface is sharply reduced can be effectively solved, smooth transition and high-reliability maintenance of the communication link in the double-medium environment are achieved, and the method can be widely applied to the technical field of unmanned aerial vehicle communication.

The present application relates to the technical field of detection circuit suitable for various electric energy information collection terminals, and discloses a detection circuit method suitable for various electric energy information collection terminals. The method sets the ambient temperature, calibrates the shunt resistor and the thermistor, constructs a three-order resistance-temperature mapping relationship, and calculates the thermal resistance and the thermal response characteristics to realize accurate modeling. The thermistor is attached to the shunt resistor and forms a thermal coupling structure by adding heat-conducting silicone grease. The constant current source and the differential amplifier are used to collect voltage, convert resistance value to temperature in real time, calculate the instantaneous current based on the heat balance equation, and then complete energy integration and grade judgment to output various electric parameters. The method integrates modeling, collection, conversion and inversion processes, constructs a complete thermal-electric detection link, does not need traditional current sensors, has the advantages of compact structure, low cost, flexible deployment and the like, and is suitable for low-power distributed terminals.

The invention discloses a chemical wounded intelligent transfer cabin based on RFID and a dynamic triage classification method, and belongs to the technical field of medical rescue equipment. The transfer cabin main body integrates the RFID identification module, the vital sign monitoring module, the environment monitoring module, the data transmission module, the cabin body regulation and control module and the emergency response module, and the RFID identification module and the transfer cabin main body are in multi-unit collaborative design, so that rapid and accurate acquisition and storage of identity information of multiple wounded personnel are realized; the problems that the identity of the wounded person is disordered and information is lost on a chemical accident site are solved, the dynamic triage classification method depends on the wounded person identity information, physiological data and environmental data collected by the transfer cabin, dynamic evaluation and classification of the injury condition of the wounded person are achieved through multi-dimensional information fusion, and the dynamic triage classification method cooperates with the transfer cabin body to work. Identity recognition, state monitoring, injury condition grading and transfer scheduling of the chemical wounded personnel in the process of transferring the chemical wounded personnel from a site to a treatment point are completed, and efficient and accurate transfer and injury inspection support is provided for wounded personnel treatment.

The invention discloses a natural language dialogue method and device, electronic equipment, a medium and a product, and relates to the technical field of artificial intelligence, the natural language dialogue method comprises the following steps: inputting dialogue input content and a preset cue word template into a preset large model; guiding the preset large model to generate a concept feature set related to the dialogue input content through the preset cue word template; and guiding the preset large model to generate each language segment through the concept features of different concept dimensions in the concept feature set, and determining reply content of the dialogue input content based on each language segment. According to the method, a hierarchical dialogue generation framework for guiding the preset large model to gradually think is generated, a systematic thinking mode of human is successfully simulated, the limitation of the large model in an open domain dialogue scene is broken through, and the dialogue reply quality is effectively improved.

The application relates to the technical field of intelligent water and fertilizer allocation, and discloses a mineral fertilizer intelligent allocation control method for water and fertilizer integration. The method comprises the following steps: collecting real-time data of soil humidity, pH value and nutrient concentration through a wireless sensor network, and synchronously acquiring precipitation, air temperature and light intensity data of a remote meteorological server; combining environmental data and a crop growth calendar to construct a soil nutrient consumption simulation model; after being corrected according to real-time monitoring data, generating a farmland nutrient deficiency distribution map by using a geographic statistics method; inputting the map into a fertilizer recommendation algorithm to calculate the application amount per unit area, and simultaneously analyzing the trends of the two types of data to identify abnormal fertilization; when the application amount exceeds the safe range, triggering multi-level alarms and adjusting the amount of fertilizer to be put according to the abnormal results. The method is suitable for the dynamic changes of soil and environment, and realizes intelligent and accurate fertilizer allocation.

The application provides a method for rapidly detecting seed germination rate, comprising: obtaining a plurality of seed samples with known germination rates, performing volatile organic compound detection on each sample to obtain volatile component data, and after data cleaning and arrangement, constructing a model of a machine learning algorithm of an integrated model, a linear model and a kernel method; using standardized feature data to establish an optimal prediction model of seed germination rate, which can be used for testing of unknown seed germination rate samples. Compared with a traditional manual statistical detection method, the detection period of the traditional method is compressed to within 2 hours, the detection efficiency is greatly improved, the manual germination and grain-by-grain counting operations are omitted, the labor input is significantly reduced, the human subjective error is reduced, the objectivity and repeatability of the detection result are greatly improved, and the error with the actual measurement value is within ± 5%. The method can be widely applied to seed quality detection scenes of various crops, and has good industry application and promotion value.

The invention discloses a super-early-strength polycarboxylate superplasticizer as well as a preparation method and application thereof, and belongs to the technical field of admixtures for concrete. The preparation method of the water reducer comprises the following steps: dropwise adding a carboxylic acid monomer aqueous solution, an ammonium persulfate aqueous solution and a vitamin C aqueous solution into a methyl allyl polyoxyethylene ether aqueous solution to prepare a prepolymer; the preparation method comprises the following steps: carrying out graft modification on a phosphate monomer and acrylamide, adding a ternary compound of triethanolamine, calcium formate and sodium citrate and an organic silicon defoamer, and adjusting the solid content to obtain the super-early-strength polycarboxylate superplasticizer. A specific monomer combination and a composite modifier are adopted to adapt to a high-sulfur-resistance cement-ultra-high-performance concrete system, the problems that a traditional water reducing agent is poor in adaptability, insufficient in early strength and weak in erosion resistance are solved, synergistic improvement of water reduction, early strength and durability is achieved, the raw materials are environmentally friendly, the preparation process is mild, and the method is suitable for industrial production. And the method is suitable for low-temperature, high-sulfur saline-alkali and other harsh construction scenes.

This invention belongs to the field of machining and intelligent manufacturing technology, specifically a smart control system and method for EDM discharge energy. It includes a multi-modal gap state sensing module, a high-throughput data synchronous acquisition and preprocessing module, a discharge pulse real-time classification and feature extraction module, an LSTM-based gap state trajectory prediction module, a multi-objective model prediction control module, and a high-frequency pulse power supply execution module. By fusing electrical parameters and in-situ optical turbidity signals, it achieves multi-dimensional perception of the discharge state and uses an LSTM network to predict future discharge trends, combined with an MPC controller to solve for the optimal pulse parameter combination online. By adopting the above technical solution, this application can achieve a dynamic optimal balance between material removal rate, surface quality, and stability during processing, improving overall processing efficiency.

The present application relates to computer bottom layer data processing and distributed feature operation technical field, specifically for a kind of multi-source gradient data processing system based on manifold reconstruction;Including: data and knowledge acquisition module, for obtaining the local model gradient update vector uploaded by multi-source data end, knowledge base contains gradient deviation typical mode feature;Ideal manifold reconstruction and simulation module, for generating gradient drift template and gradient anomaly template;Double-track difference feature extraction module, for calculating the theoretical drift deviation and theoretical anomaly deviation between gradient drift template, gradient anomaly template and quantization feature matrix respectively;Situation coupling decision module, for executing the trusted writing of multi-source gradient data or the release or isolated storage instruction of abnormal data rejection;The present application effectively improves the robustness of bottom layer multi-source feature data processing and the reliability of system memory update.

The invention relates to the technical field of intelligent implantable medical instruments, in particular to a magnetohydrodynamic pulse negative pressure micropump system integrated with wireless parameter monitoring, which comprises a fully implantable magnetohydrodynamic intelligent sensitive micropump, an in-vitro multifunctional driving read-out unit and an intelligent terminal, the fully-implanted magnetomotive intelligent-sensitive micropump is of a hollow titanium alloy screw structure, a magnetomotive power pump module and a wireless passive sensing module are arranged in the fully-implanted magnetomotive intelligent-sensitive micropump, the fully-implanted magnetomotive intelligent-sensitive micropump can be implanted into a bone in a minimally invasive mode, pulse negative pressure is generated, and intraosseous tissue gap hydraulic data are wirelessly transmitted. The in-vitro unit provides a driving magnetic field and radio frequency energy; and the intelligent terminal realizes data display, analysis and parameter adjustment to form intelligent closed-loop control. The system realizes integration of treatment and monitoring, is minimally invasive, has no infection risk, is accurate in monitoring and efficient in treatment, solves the problem of pain points in the prior art, and has important clinical application value.

The invention provides a cardiovascular intervention injector convenient to operate, and relates to the technical field of medical instruments. An internal control part is arranged in the injection part; a limiting part is arranged outside the injection part; through collaborative design of an inner matching block and a torsion inner block, rapid switching between a direct pushing mode and an outward pushing mode is achieved, medicine in a medicine storage body can be directly pushed in the direct pushing mode, other medicine can be pushed in the outward pushing mode by connecting an external torsion head with external medicine adding equipment, and multi-medicine delivery can be completed without detaching the device or replacing an injector; the external matching cylinder, the position adjusting knob block and the displacement sleeve are in threaded transmission fit, the relative distance between the stopping contact and the needle point of the intervention needle body can be accurately adjusted, the puncture depth can be preset, and the problems that a traditional injector is generally designed in a single-cavity single-medicine storage mode, only can load single medicine, and cannot be used for storing medicine are solved. Therefore, the problem that the injector needs to be frequently disassembled and replaced to complete multi-drug delivery in an operation is solved.

The application provides a kind of SSL certificate deployment updating method and device based on reinforcement learning, which comprises the following steps: generating a to-be-processed asset list based on the multi-source heterogeneous asset scanning results of the global network space, and constructing a certificate asset knowledge graph based on the to-be-processed asset list; generating a technical fingerprint vector representing the service type and configuration state based on the protocol handshake message features and response header information of each service node in the certificate asset knowledge graph, and analyzing the configuration syntax structure of the target heterogeneous environment based on the technical fingerprint vector and generating an initial deployment configuration template adapted to the structure; constructing a state space of the reinforcement learning environment based on the initial deployment configuration template in combination with the topology dependency relationship in the certificate asset knowledge graph and the real-time load water level line of the current business system; and performing multiple rounds of simulation deduction using a reinforcement learning agent based on the state space to form a full life cycle closed-loop management log. The application improves the continuity and security of Web services.

The invention relates to the technical field of intelligent MES. The invention relates to an industrial production whole-process intelligent MES (Manufacturing Execution System) supporting multi-protocol docking and AI (Artificial Intelligence) collaboration. The system comprises a protocol adaptation module, a model establishment module, a space construction module, a state selection module and a space updating module. The protocol adaptation module is used for constructing an industrial unified protocol adaptation engine and establishing data connection with the production equipment according to the industrial unified protocol adaptation engine so as to collect historical industrial data corresponding to different production equipment; historical industrial data of production equipment is trained by adopting a deep learning algorithm, operation features of the equipment and process association features among the equipment can be extracted at the same time, a unique equipment identifier is bound for each equipment model, and the equipment models are sorted by strictly following a production processing sequence and process connection logic, so that the production efficiency is improved. An equipment model sequence is completely consistent with an actual production process, and linkage management and control of the industrial production whole-process equipment model are realized.

The invention discloses a pre-flood hydrological forecasting factor rapid identification method and system based on environmental perception, and the method abandons a conventional forecasting mode which depends on a hysteresis index after a flood occurs, and achieves the rapid and accurate identification of a hydrological forecasting factor through sensing a key environmental factor before the flood occurs. The design system comprises an environment factor sensing module, a data preprocessing module, a factor rapid screening module, a model training optimization module and an identification result output module, and the pre-flood environment data such as the soil water content, the early-stage accumulated rainfall and the vegetation coverage are collected and preprocessed, and then a multi-algorithm fusion screening strategy is adopted. The method can quickly lock the core forecasting factor with strong relevance to flood generation, provides advance support for hydrological forecasting, and solves the technical problems that the traditional hydrological forecasting factor is lagged in identification and poor in timeliness. The hydrological forecasting method remarkably improves the perspectiveness and accuracy of hydrological forecasting, and is suitable for scenes such as basin flood early warning and water resource scheduling.

The invention provides a wireless sensing system determination method and device, a wireless sensing method and device, equipment, a medium and a product, and relates to the technical field of wireless communication. The method comprises the following steps: acquiring signal strength information corresponding to an AP detected by a first wireless access point AP in a preset local area network, wherein the preset local area network comprises at least one first AP; and determining at least one sensing topology set according to the signal intensity information corresponding to the AP detected by each first AP, wherein each AP included in each sensing topology set is used for wireless sensing. According to the method provided by the invention, wireless sensing is carried out by establishing wireless communication between the wireless access points, so that a sensing result error caused by the change of the position of the mobile terminal is avoided, and the sensing accuracy is improved.