88results about How to "Easy to formulate" patented technology

The invention discloses a pollution research and water quality prediction method based on river segmented water environment capacity analysis. The method comprises the following steps: accurately dividing a drainage basin into water environment capacity accounting units; obtaining a river water body image through satellite remote sensing; identifying and quantifying the positions and the intensities of point source and non-point source pollution sources in the drainage basin by utilizing the water quality parameters of the river obtained by the remote sensing image; establishing a river water quality prediction model; calculating the water environment capacity of each river reach under different surface water environment quality standards; comparing the estimated pollutant discharge amount with the water environment capacity under each water quality standard, and judging whether the pollutant discharge amount exceeds the capacity or not; and predicting future water quality change by using the model. According to the method, remote sensing, GIS and machine learning technologies are utilized, rapid analysis of the river segmented water environment capacity and accurate prediction of the water quality are achieved, dependence on a large amount of field sampling and complex software simulation is reduced, and the working efficiency is greatly improved.

The invention discloses an intelligent precise irrigation system based on low-altitude remote sensing data driving. The intelligent precise irrigation system comprises a low-altitude unmanned aerial vehicle, a ground sensor network module, a meteorological data integration module, a space-time self-evolution feature map network module, a space-time adaptive attention network module, a context multi-arm tiger machine algorithm module and an automatic irrigation control module. The low-altitude unmanned aerial vehicle is used for acquiring remote sensing data of crops; the ground sensor network module is used for collecting real-time environment information; the meteorological data integration module is used for multi-modal data integration; the space-time self-evolution characteristic graph network module is used for generating a moisture demand distribution graph; the space-time adaptive attention network is used for optimizing an irrigation strategy; the context dobby machine algorithm module is used for dynamically selecting an optimal irrigation strategy; and the automatic irrigation control module is used for executing the optimal irrigation strategy and implementing differential intelligent irrigation management. According to the invention, precise and intelligent irrigation is realized by using the space-time self-evolution feature map network and the context multi-arm tiger machine algorithm.

The invention belongs to the field of tunnel engineering, and particularly discloses a tunnel surrounding rock multi-mode intelligent fine grading method and system, and the method comprises the steps: 1, constructing a sample library which comprises parameters while drilling of a tunnel face, a digital image and a corresponding tunnel face surrounding rock grade; 2, constructing a while-drilling parameter refined grading characteristic system; 3, constructing a surrounding rock intelligent grading model based on multi-modal data fusion; 4, dividing the rock mass in front of the tunnel face into a plurality of three-dimensional space unit bodies according to the tunnel contour and blast hole distribution characteristics; and 5, based on the surrounding rock intelligent grading model, finely and intelligently judging the grade of the tunnel face surrounding rock. According to the method, the intelligent surrounding rock grading model based on the multi-modal data fusion theory is constructed, the refined intelligent judgment of the tunnel face surrounding rock grade is realized, the precision and robustness of the refined intelligent judgment of the surrounding rock grade of the model are improved, the surrounding rock grading level in the construction stage is improved, more comprehensive reference is provided for a subsequent construction scheme, and the construction efficiency is improved. And tunnel intelligent construction is guided.

The invention relates to an exercise prescription recommendation method and device, electronic equipment and a storage medium. The exercise prescription recommendation method comprises the following steps: constructing multiple agents at least integrated with a user agent, a doctor agent, a nutritionist agent and an exercise health agent, and providing an interactive interface to realize information sharing, competition or negotiation and decision and scheme generation between every two agents; pre-training is carried out based on the professional domain knowledge maps corresponding to the different agents, so that a multi-agent exercise prescription recommendation model is obtained; and inputting the obtained various related conditions of the metabolic disease patient into the exercise prescription recommendation model for reasoning to obtain a target exercise prescription. According to the invention, accurate and personalized exercise prescriptions can be formulated for patients with metabolic diseases.

The invention discloses a thrombolysis prediction method based on deep learning and multi-modal fusion, and belongs to the technical field of thrombolysis prediction, and the method comprises the steps: S1, collecting an MRI image of a patient with ischemic cerebral apoplexy, and constructing a cerebral apoplexy automatic segmentation model; s2, carrying out image registration; s3, lesion segmentation; and S4, thrombolysis prediction. According to the cerebral apoplexy automatic segmentation model based on the gating parallel Mama network, the long-distance dependency relationship in the image can be effectively captured, ischemic cerebral apoplexy lesions can be rapidly and accurately segmented, and the lesion identification efficiency and accuracy are greatly improved; according to the algorithm provided by the invention, the linear time complexity is realized, the computing resource consumption is greatly reduced, and the bottleneck of the prior art is broken through; according to the cerebral apoplexy thrombolysis prediction model based on the multi-modal data, scientific automatic decision support is provided for judging whether the patient is suitable for thrombolysis treatment or not, and the quality and safety of medical decision are improved.

The invention discloses a method for monitoring diversity of large benthic invertebrates in a river based on eDNA. The method comprises the following steps: step 1, selecting a river basin to be measured, and querying basic information of the basin; 2, collection and treatment of eDNA samples: designing sampling points and geographic positions, and collection and pretreatment of water samples; 3, measuring physical and chemical indexes; 4, extraction of eDNA, PCR amplification and high-throughput sequencing are carried out; and 5, performing data analysis on the results, wherein the data analysis comprises bioinformatics analysis, alpha diversity analysis, beta diversity analysis and correlation analysis of large benthic invertebrate communities and environmental factors. The diversity of the large benthic invertebrates is more accurately and efficiently investigated and monitored by analyzing DNA fragments existing in the environment.

The invention discloses a circuit and chip for supporting core particle parallel physical links through a PIPE interface, and the circuit comprises a data processing module which is located between the PIPE interface and a parallel PHY group, and comprises a data packaging module and a data analysis module, the data packaging module is used for generating a receiving direction data signal on the PIPE interface from data from the PIPE interface, compressing and packaging the receiving direction data signal and transmitting the receiving direction data signal to the parallel PHY group; and the data analysis module is used for analyzing the data from the parallel PHY group, recovering and restoring the compressed data, and then transmitting the data to an upper layer through the PIPE interface so as to send the data to a core particle interconnection controller on the PIPE interface. The invention aims to solve the problem of how to drive and use a plurality of parallel physical interfaces to carry out data transmission through a PIPE interface of a core particle interconnection protocol interface compatible with a PIPE interface on a physical layer, and data transmission is carried out through the PIPE interface and the plurality of parallel physical interfaces.

The invention discloses an urban road traffic state prediction method based on a macro-medium-micro hybrid simulation model, a storage medium and equipment, and the method comprises the steps: collecting historical electronic police data and traffic channelization data, inputting the historical electronic police data and traffic channelization data into a constructed macro-medium-micro integrated multi-level hybrid simulation model, and carrying out the simulation, obtaining a road traffic state in each time period and traffic flow data at each moment; constructing a traffic flow parameter prediction model based on an MVF-FA-LSTM algorithm, inputting the traffic flow data into the traffic flow parameter prediction model, and predicting the traffic flow and the passing speed of the road; and constructing a traffic state prediction model based on a fuzzy C-means clustering algorithm, inputting the predicted traffic flow and passing speed of the road into the traffic state prediction model, and predicting the traffic state of the road. According to the method, unification of microscopic, mesoscopic and macroscopic simulation models is realized, and road flow and passing speed prediction is realized, so that road traffic states are divided, and a traffic management department is guided to command and make decisions.

The invention discloses a design cost optimization method, system and device for a real estate project and a medium. The method comprises the steps that a plurality of product modular units are generated in a target engineering project; associating the product modular unit with a project unit identifier; in the target engineering project, obtaining a corresponding project product list library and a contract planning list; taking each product modular unit as a basic unit, determining a corresponding design cost influence factor according to the corresponding project product list library and the contract planning list, and performing engineering project cost budgeting to obtain a project cost budgeting result; in the planning and construction process, obtaining project construction data and actual construction cost of each product modular unit; obtaining a corresponding budget cost early warning interval based on the project unit identifier, judging whether the actual construction cost is within the corresponding budget cost early warning interval, and obtaining a budget cost evaluation result; according to the invention, the cost budgeting accuracy of the real estate project is improved.

The invention belongs to the technical field of data transmission supervision, and particularly relates to a multi-terminal series data transmission interaction system and method based on a communication network, and the system comprises a data initiating terminal, a series data processing node module, a data receiving terminal, a communication monitoring management module, an emergency decision module and a background supervision terminal. Data to be transmitted are preliminarily packaged through a data initiating end and sent to a serial data processing node module, each data processing node in the serial data processing node module is responsible for a specific data processing task, and after processing of all the data processing nodes, a data receiving end receives and analyzes the data and sends the data to a server; the data processing and transmission efficiency is improved, the whole data transmission process of the data transmission link is monitored in real time through the communication monitoring management module so as to identify abnormity of the data transmission process, high efficiency, safety and reliability of data transmission are ensured, and the data transmission process is more controllable and predictable.

The invention discloses a real-time monitoring and data processing method for a reinforced concrete structure, and particularly relates to the technical field of data processing, and the method comprises the steps: building a data anomaly detection influence model through obtaining the saline corrosion information, the dynamic load information of waves and inrush current and the attachment information of underwater organisms during the operation of an external sensor; measuring the influence of the dynamic load of saline corrosion, waves and inrush current and the attachment of underwater organisms on the existing data anomaly detection, comparing a data anomaly detection influence index with a preset data anomaly detection influence index threshold value, and when an anomaly detection influence signal is generated, constructing a data anomaly detection machine learning model, the data anomaly detection is optimized according to the influence degree of the data anomaly detection and the difference of the reinforced concrete structure data transmitted by the external sensor and the internal sensor, so that too frequent false report and missing report are avoided, the detection strategy is adjusted in time, and the accurate monitoring of the health state of the structure is improved.

The invention belongs to the technical field of medical diagnosis, and discloses an MRI lumbar sagittal view disease image diagnosis method based on a YOLOv8s algorithm, and the method comprises the following steps: S1, screening collected MRI lumbar sagittal view image data, self-building a VOC2007 data set, and marking the data set; s2, performing data enhancement and other processing on the existing data set; s3, establishing a YOLOv8s deep learning neural network detection model; dividing the data set into a training set, a verification set and a test set according to a proportion of 8: 1: 1, training the YOLOv8s network until convergence, and obtaining a lumbar disease image detection model based on the YOLOv8s network and a weight file; and S4, testing the randomly extracted MRI lumbar vertebra sagittal view image of the patient by using the trained YOLOv8s detection model, outputting a detection result, and evaluating the detection result. According to the invention, the diagnosis of the MRI lumbar sagittal view disease can be realized, the detection precision and efficiency are greatly improved, and the diagnosis accuracy is improved.

The invention discloses a carbon sequestration capability value evaluation system and method for a river and lake water ecosystem, and the system comprises a data collection module which is used for collecting different types of vegetation samples in a target region and corresponding vegetation image data; the ground monitoring terminal comprises a data analysis processing module which is used for processing the collected vegetation samples to obtain carbon content data of different types of vegetation, obtaining vegetation biomass data of different types of vegetation according to the vegetation samples and the vegetation image data, and sending the vegetation biomass data to the ground monitoring terminal; calculating carbon sequestration capability data of different types of vegetation according to the vegetation biomass data and the carbon content data; the evaluation module evaluates the carbon sequestration capacity value of the target area based on the sum of the carbon sequestration capacity data of different types of vegetation, and the mode is beneficial to understanding the influence of the vegetation types on the carbon sequestration capacity value of the river and lake water ecosystem, facilitates the formulation of ecological protection policies, and improves the pertinence and effectiveness of the control and protection of the river and lake water ecosystem.

The invention discloses a document key information retrieval method based on a large language model, a retrieval result is output according to a multi-stage input document and a question input by a user, and the method comprises the following steps: constructing a domain knowledge graph; constructing and training a question extraction model, and obtaining key information and intention of the question input by the user through the question extraction model; retrieving in a knowledge graph according to the key information and the intention to form paragraph description of the key information; screening the document and splitting the document into a plurality of text blocks to obtain a plurality of text blocks most related to the content input by the user; obtaining a corresponding text block with the highest embedding similarity by using a large language model; and integrating and reasoning the corresponding text blocks and paragraph descriptions by adopting a large language model to obtain information about the user input question in the document. The method has the beneficial effects that the accuracy and efficiency of information extraction can be improved, specific requirements of different fields can be met, and powerful technical support is provided for document automatic processing and knowledge management.

The invention provides an energy equipment data communication method based on a block chain, and the method comprises the steps: obtaining energy data of energy equipment which completes registration in a block chain network, and writing the energy data into a sub-chain of the block chain network based on the type of the energy data; the target energy equipment responds to a preset data interaction condition meeting the target control mode, initiates a first identity authentication request to the block chain network to perform first identity authentication, generates a data sharing request for the target type data based on the preset data interaction condition of the target control mode when the first identity authentication is successful, and performs second identity authentication; and when the access is successful, processing the data sharing request for the target type data by a sub-chain matched with the type of the target type data in the block chain network based on an intelligent contract, determining target shared energy data conforming to the access rule, and sharing the target shared energy data to the target energy equipment, therefore, energy data interaction between household energy devices can be realized safely and efficiently.

The invention discloses a method for measuring the rigidity of paired main bearings of an RV speed reducer. The method comprises the following steps of 1, customizing a bearing mounting tool according to the size of a bearing to be measured; step 2, inputting a test load spectrum and an axial measurement load on the measurement controller; 3, completing the assembly of the bearing installation tool and the two to-be-tested bearings, and connecting a tool upper cover with the top platform; 4, rotating the tool spacer ring and driving the outer rings of the two to-be-tested bearings to rotate, and eliminating gaps between the ferrules of the two to-be-tested bearings and the rolling balls; step 5, applying an axial load to the two to-be-measured bearings until the axial load is consistent with the axial measurement load set on the measurement controller, thereby completing the preloading of the two to-be-measured bearings; step 6, calculating the assembly height of the paired bearings; and step 7, taking the numerical value of the assembly height of the paired bearings as an original point, continuously applying an axial load to the two to-be-tested bearings, and finally drawing a stress-displacement curve by using test data. The method is high in measurement efficiency.

The invention relates to a subway passenger flow prediction method and device based on a multi-scale space-time diagram attention network. The method comprises the steps of collecting passenger flow data of subway OD pairs, subway line network structure data and land use type data; constructing an OD-level urban rail transit knowledge graph based on the collected data, and calculating node features of the knowledge graph, including calculating historical passenger flow features, calculating land use information, calculating accessibility of OD pairs and calculating correlation of the OD pairs; inputting node features of the knowledge graph into a multi-scale space-time diagram attention network, performing diagram filtering on the node features, and updating the node features of the knowledge graph in combination with a result of a space-time attention mechanism; and inputting the updated node features into the multi-scale LSTM model, and outputting a multi-scale prediction result of the subway passenger flow. Compared with the prior art, the method has the advantages of being more accurate in prediction, beneficial to intelligent scheduling and the like.

The invention relates to the technical field of data processing, in particular to an intelligent data processing method and system based on surgical nursing, and the method comprises the steps: firstly obtaining food intake and physiological indexes of a patient within a preset time, comparing the food intake and physiological indexes with a standard food intake set, and generating a food intake standard score; in conjunction with the physiological metric, the system determines a real-time feeding score and a total feeding score. By comparing the real-time and total feeding scores at different time points, the system finally generates a feeding balance score of the patient. According to the method, food intake and physiological data are effectively integrated, a scientific and quantitative food intake evaluation tool is provided for surgical nursing, nutrition management of a patient is optimized, nursing quality is improved, the absolute value of the food intake is considered in the evaluation, the relevance between time distribution of food intake and physiological indexes is concerned, and the evaluation accuracy is improved. Therefore, more comprehensive and in-depth patient state information is provided for nursing personnel. Especially, due to the introduction of a feeding balance degree score, an important basis is provided for formulating a more reasonable nutrition intervention scheme.

The invention belongs to the technical field of vagina detection, and discloses a vagina detection and evaluation system and method based on tactile imaging. Comprising the following steps: acquiring pressure data in the vagina of a target patient based on a flexible sensor to obtain a corresponding pressure sensing signal; the signal processing module is used for processing the collected pressure sensing signals and constructing a corresponding pressure distribution image based on the pressure sensing signals after signal processing; the image processing module is used for processing the obtained pressure distribution image to obtain a corresponding vagina tactile image; performing abnormal degree evaluation on the vagina of the corresponding patient based on the obtained vagina tactile image to obtain a corresponding abnormal evaluation report, and performing feedback; the accuracy, efficiency and clinical application value of vagina detection can be improved from multiple aspects, and powerful support is provided for medical work.

The invention discloses a system and a method for predicting the optimal excitation frequency of a vibratory roller based on machine learning, and the method comprises the following steps: S1, collecting the original data of soil under different conditions and the working parameters of the vibratory roller under the conditions, investigating the parameters of different models of vibratory rollers, and processing and storing the data; s2, a machine learning algorithm in MATLAB is selected and trained, a machine learning-based optimal excitation frequency prediction model of the vibratory roller is obtained, and thus the predicted soil inherent frequency can be obtained; and S3, comparing the difference between the predicted soil inherent frequency and the soil inherent frequency measured in actual work, and adjusting and optimizing the prediction model in S2. According to the method, the optimal excitation frequency of the vibratory roller is predicted before construction, the prediction precision is improved by integrating factors such as the environment, the pavement type, the soil density and the compaction degree, and the operation requirements of the vibratory roller under different regions and different pavement conditions can be met.

The invention relates to the field of aluminum electrolysis cells, and discloses a grade standard setting method and system for an electrolysis cell and electronic equipment. According to the method, an index scoring standard corresponding to each operation index is formulated according to historical data corresponding to each operation index of the aluminum electrolysis cell through an established data classification model, so that comprehensive scoring is performed on the historical data of the aluminum electrolysis cell according to the index scoring standards, and a historical comprehensive score is obtained; scoring intervals corresponding to different electrolytic cell grades of the aluminum electrolytic cell are formulated according to historical comprehensive scores through a data classification model, so that grade standard formulation of the aluminum electrolytic cell is achieved, the data classification model is established according to a normal distribution theory, and data are effectively classified according to the dispersion degree of the data; and subjective influence caused by experience judgment is eliminated, and an index scoring standard and an electrolytic cell grade standard are sequentially formulated through the data classification model, so that a user can conveniently formulate the grade standard of the aluminum electrolytic cell.

The invention discloses an intelligent medical drug management method and a drug registration platform, relates to the technical field of drug management platforms, and breaks through the limitation that drug adjustment is judged only according to symptom representation traditionally by comprehensively considering environmental factors and emotion factors to evaluate the necessity of drug adjustment. Multi-element potential factors influencing the health state and the drug effect of patients are deeply mined, patient groups really needing drug adjustment are accurately positioned, highly personalized medical intervention is achieved, burden and potential risks caused by unnecessary drug adjustment to the patients are avoided, priorities are divided based on disease risk prediction values, and the accuracy of drug adjustment is improved. And the patient information is pushed to the on-duty doctor working machine in order, so that the vigor, the time, the medicine reserve and the like of the medical resource doctor are preferentially inclined to the patient with high risk and urgent need of medicine adjustment, the treatment delay of the patient with high demand caused by average force of medical service is avoided, the overall medical service efficiency is improved, and the maximum treatment value of limited resources is brought into play.

The invention discloses an electric energy metering device state prediction method, and belongs to the field of electric energy metering devices. The electric energy metering device state prediction method comprises the following steps: S1, predicting fault time and residual life of an electric energy meter; s2, judging an operation state; s3, predicting the health degree of the electric energy metering device; s4, predicting the error state of the electric energy metering device; and S5, comprehensively evaluating the state of the electric energy metering device. The method solves the problem that the existing operation state evaluation method cannot predict the health and fault conditions of the electric energy metering device and thus cannot make corresponding countermeasures in advance, can timely know the residual life of the time machine when the fault of the electric energy metering device occurs, facilitates the timely making of a maintenance plan, and improves the maintenance efficiency of the electric energy metering device. The workload of the electric energy metering device is reduced, the accuracy of the prediction result is improved, and the maintenance efficiency is improved.

The present application discloses a data recommendation method, device, equipment and computer-readable storage medium, which belongs to the field of data processing technology. The method includes: obtaining the search data of the target user; determining the first recommended data corresponding to the search data; obtaining multiple second recommended data related to the first recommended data based on the recommended reference data, and the recommended reference data is obtained based on the historical self-driving data of the target user; and recommending the second recommended data that meets the recommendation conditions among the first recommended data and the multiple second recommended data. The method recommends more recommended data that meet the user's needs to the user based on the user's historical self-driving data, so that the results of data recommendation are more diversified, and through the screening of the recommended conditions, the recommended data is made more accurate, which saves a lot of redundant time, improves the recommendation efficiency, and facilitates the formulation of self-driving routes based on the recommended data.

The present invention discloses a pedestrian movement line simulation system in a building in the field of human flow simulation, including a building import module, a building equipment editing module and a pedestrian simulation module. The building import module is used to import building drawings, the building equipment editing module is used to edit and set equipment in the building, and the pedestrian simulation module is used to add pedestrian models and set behavior logic. The behavior logic includes process-based behavior and random behavior. The process-based behavior is used to simulate various behaviors of pedestrians in the building, such as receiving services, queuing, waiting, strolling, speed limits, etc., including node selection, path finding, facility interaction and leaving facility logic; pedestrian random behavior includes passive facility interaction logic, herd logic, idle time logic and companion logic. The technical solution of the present invention can improve the restoration degree of the initial human flow dispersion state by setting the pedestrian behavior logic.

An exercise device comprises a base, two resistance arms and a resistance mechanism, the two resistance arms are rotationally connected with the base and can be oppositely opened and closed, the resistance mechanism provides resistance for the two resistance arms to be oppositely closed, and the exercise device is characterized in that the resistance mechanism comprises a sliding block and a resistance part, the sliding block is arranged on the base in a vertically movable mode, and the resistance part is arranged on the sliding block; the resistance part is used for providing resistance for preventing the sliding block from moving upwards, the resistance arms comprise first driving parts, the sliding block is provided with second driving parts abutting against the first driving parts, and when the two resistance arms rotate in a relatively closed mode, the first driving parts and the second driving parts are matched to drive the sliding block to overcome the resistance of the resistance part to move upwards. Under the cooperation of the first driving part of the resisting arm and the second driving part of the sliding block, the sliding block is driven to overcome resistance to move upwards, the resistance is transmitted through the vertical movement of the sliding block, the resistance direction is consistent with the force exerting direction of the human body, force exerting in the human body exercising process is better met, and the better exercising effect is achieved.

The invention relates to an intelligent orthodontic image management method and system, and relates to the technical field of data management, and the system comprises an image obtaining module which is used for obtaining orthodontic data of historical patients; the image storage module is used for encrypting and storing the orthodontic data of historical patients; the feature acquisition module is used for acquiring the orthodontic image of the patient to be subjected to orthodontic treatment from the image generation terminal and extracting the oral features of the patient to be subjected to orthodontic treatment from the orthodontic image of the patient to be subjected to orthodontic treatment; the image searching module is used for determining a target historical patient based on the oral features of the to-be-orthodontic patient; the image sharing module is used for calling the orthodontic data of the target historical patient and sending the called orthodontic data of the target historical patient to the doctor terminal; and the scheme generation module is used for generating an auxiliary orthodontic scheme based on the oral features of the patient to be orthodontic and the orthodontic data of the target historical patient, and the method has the advantage of improving the quality of orthodontic image management.

The present invention provides a method, device and storage medium for dynamic testing of the performance of headlights of intelligent driving vehicles, including the following steps: S1, obtaining dynamic test data and performing data processing and feature extraction; S2, building a test model by combining a hybrid neural network model structure with a feature pyramid network; S3, training and debugging the model of step S2 using the data processed by step S1; S4, finally, performing performance evaluation and verification on the model trained in step S3 and using it to dynamically test the performance of headlights of intelligent driving vehicles. In the field of intelligent driving vehicles, the present invention introduces a dynamic testing system and method for headlight performance, which significantly improves the fit and comprehensiveness of test results with actual driving scenarios compared to traditional static tests. This innovation not only profoundly affects the safety and user experience of intelligent driving vehicles, but also promotes the intelligentization and standardization of lighting technology in the entire automotive industry.

The present invention discloses a method for evaluating storage utilization of a digital twin model, comprising the following steps: S1, collecting and modeling vertical warehouse space data; S2, constructing a digital twin vertical warehouse model based on the spatial data model; S3, evaluating and analyzing storage utilization based on the spatial data model, which uses spatial division and measurement methods to evaluate the utilization of the vertical warehouse space, and compares and analyzes the storage utilization rates of different areas to find out areas with insufficient or wasted space. The present invention uses spatial division and measurement methods to evaluate the utilization of the vertical warehouse space, which not only realizes the visual expression of space utilization, but also can calculate the storage utilization rate of the vertical warehouse from different dimensions such as shelf use, channel utilization, and overall space, so it can greatly improve the multi-dimensionality and precision of space utilization.

The utility model relates to the technical field of fire-fighting equipment, in particular to a forest fire-fighting supply cabinet which comprises a cabinet body, a mounting part is arranged on the cabinet body, a photovoltaic panel is arranged at the upper end of the mounting part, a storage chamber is arranged in the cabinet body, a partition plate is fixedly arranged in the storage chamber, a plurality of supporting parts are fixedly arranged on one side of the partition plate, and the supporting parts are fixedly arranged on the other side of the partition plate. A drawer is arranged on one side of the cabinet body, a partition plate is arranged on the other side of the cabinet body, a containing chamber is arranged on the other side of the partition plate, a portable water pump is arranged in the containing chamber, a water hose matched with the portable water pump is arranged in the drawer, and a moving mechanism matched with the portable water pump is further arranged in the containing chamber. The portable water pump can be moved to a water source near a fire disaster according to the position of the fire disaster, so that the laying length of a water hose is reduced, a processor and a wireless module are arranged in the cabinet body, and the position, the operation state and the material condition of the supply cabinet can be searched in real time on a platform or a mobile phone terminal.