106results about How to "Guaranteed rationality" patented technology

The invention provides an expandable block chain identity authentication method and system for a distributed resource aggregation scene, and relates to the technical field of block chain identity authentication, and the method comprises the steps: receiving a user identity authentication request, generating an identity identification string through a distributed Hash algorithm, and selecting a verification node cluster to deploy a smart contract; each verification node executes the smart contract to verify the identity identification string, constructs an access authority control strategy and generates an authentication block; and when the number of the blocks reaches a preset threshold value, selecting a newly added verification node based on the terminal equipment information, deploying an intelligent contract, and realizing distributed storage through the verification node cluster broadcast authentication blocks. According to the invention, the expandability of identity authentication is improved, the dynamic expansion of the verification node is realized, and the reliable storage and efficient propagation of the authentication information are ensured.

The invention relates to the technical field of material management, and discloses an infrastructure material cyclic application management and control system, which comprises the following modules: an intelligent material identification and real-time data acquisition module, which is used for carrying out automatic identification, classification and real-time data acquisition on infrastructure materials based on various sensor technologies (visual identification, RFID, laser scanning and NFC) and a deep learning algorithm, a digital material file is generated, and dynamic tracking and accurate positioning of materials are achieved; and the block chain-based full life cycle management module is used for carrying out data management and encrypted storage on the full life cycle (from purchasing, transportation, storage, use, maintenance, cyclic utilization to scrapping treatment) of the materials. Through close combination of a multi-mode sensor technology (visual identification, RFID, laser scanning and NFC) and a deep learning algorithm, all-directional and multi-dimensional identification and real-time data acquisition can be performed on capital construction materials in a complex and changeable environment.

The invention discloses a data management system based on a monitoring video stream, belongs to the field of data analysis, and aims to solve the problems of camera connection acquisition, image quality optimization, pedestrian related information analysis and data storage retrieval and backup in video monitoring. The system comprises a data acquisition module, a target detection module and a data storage module. The data acquisition module is used for identifying and connecting a video monitoring camera, performing video stream data acquisition, adjusting an acquisition frame rate by estimating a data size, and evaluating and optimizing image quality to obtain a detection image data set; the target detection module is used for carrying out feature extraction, classification and marking on pedestrians in the detection image data set, recording pedestrian trajectory information, carrying out real-time tracking and updating, identifying a behavior mode according to the trajectory information, dividing a gathering area and obtaining the pedestrian flow; and the data storage module is used for classifying and labeling the data, constructing an index structure to guarantee efficient retrieval, dividing data grades according to multi-dimensional features, and dynamically adjusting a backup time interval.

The invention discloses an electric power engineering technical-economic review method based on deep learning. The method comprises the following steps: S1, automatically capturing project data such as engineering quantity, an equipment list and material cost, and carrying out preliminary detection; s2, analyzing data by using a deep learning model, and analyzing and classifying text information through natural language processing; s3, establishing a charging benchmark rule base, and automatically checking the cost data in the technical and economic files; s4, adopting a self-adaptive material semantic matching algorithm to examine equipment and material data, and carrying out market information price matching; s5, constructing a mapping relation between the project amount and the typical cost, and generating a deviation report; s6, establishing a data center to support multi-dimensional statistical analysis and a real-time cost report; and S7, combining historical and real-time data, performing early warning through a deep learning algorithm, and generating an intelligent review report. According to the invention, automation and intellectualization of electric power engineering technical-economic review are realized, and data processing efficiency and review accuracy are optimized.

The invention belongs to the technical field of seam welding detection, and particularly discloses and provides a roof waterproof roll seam welding detection method which comprises the following steps: constructing a three-dimensional model of a to-be-constructed welding area, and marking the type of a welding detection point; welding characteristic analysis is conducted on the welding area, and all welding characteristic indexes are obtained; the number of welding detection points is determined, and the welding detection points are marked; confirming a standard passing threshold value of each welding detection point corresponding to each welding detection index; building a welding quality inspection model; sequentially carrying out quality inspection according to a set welding quality inspection plan, and recording quality inspection values; and the welding quality score value is output, and a welding quality inspection report of the waterproof coiled material is constructed and fed back. According to the method, the defect that current welding detection points are arranged comprehensively is effectively overcome, the specific welding characteristics of the waterproof coiled material are fully combined, the adaptability of a seam welding detection scene of the roof waterproof coiled material is improved, and meanwhile the representativeness and rationality of a welding detection result are guaranteed.

The invention provides a one-dimensional pneumatic design method and device for an axial flow compressor, and belongs to the field of axial flow compressor pneumatic design. The method comprises the following steps: taking values of a plurality of design variables as the state of a reinforcement learning agent; the intelligent agent outputs the adjustment amount of the design variable according to the state, and the adjustment amount serves as the action executed by the intelligent agent; applying the action to the value of the current design variable to obtain an updated design variable; utilizing a one-dimensional inverse problem design program to generate a one-dimensional pneumatic design scheme of the gas compressor; utilizing a one-dimensional normal problem analysis program to output performance indexes; constructing a reward function according to the performance indexes; based on feedback provided by the reward function, a depth deterministic strategy gradient algorithm is adopted to train the intelligent agent; and performing one-dimensional pneumatic design of the gas compressor by using the trained intelligent agent. According to the method and device provided by the invention, the problems that the one-dimensional design of the axial flow compressor depends on experience, the efficiency is low, automatic optimization is difficult and the response is slow can be solved.

The invention discloses a multi-modal analysis method based on an intelligent robot, and relates to the technical field of robot learning, and the method comprises the steps: obtaining the sensing modal dimension of the intelligent robot; training single-mode decision models in one-to-one correspondence with the robot sensing modes; obtaining sensing data of the intelligent robot in each sensing mode; determining a single-mode decision scheme in each sensing mode; constructing a decision feature type set of each single-mode decision scheme and a decision feature value of each single-mode decision scheme; obtaining a total set of decision feature types; determining at least one alternative decision feature value of each decision feature in the decision feature type total set; performing cross fusion to obtain at least one preliminary screening decision feature group; screening out an optimal decision feature group of the intelligent robot; and outputting the multi-mode comprehensive decision of the intelligent robot. The method has the advantages that the optimal scheme under the multi-modal decision is effectively fused, and the multi-modal automatic optimal decision of the intelligent robot is realized.

The invention discloses a loss diagnosis and health management system and method for a transformer, and belongs to the technical field of intelligent transformers, and the system comprises a thermal fingerprint module which is used for recording a temperature drop curve of each part of the transformer after planned power failure, and obtaining a thermal inertia fingerprint of the transformer based on the fitting of multiple temperature drop curves; the theoretical temperature module is used for calculating the theoretical cold body temperature of each part of the transformer based on the real-time environment temperature and the thermal inertia fingerprint when the transformer runs; the net temperature rise module is used for acquiring the actual temperature value of each part of the transformer and subtracting the corresponding theoretical cold body temperature from the actual temperature value; weak thermal characteristic signals caused by insulation aging and loss abnormity of the transformer can be accurately extracted from strong background noise such as load fluctuation and environment temperature through technologies such as thermal inertia fingerprint construction and net temperature rise separation, early diagnosis of progressive health deterioration is realized, support is provided for intervening potential faults in advance, and the fault diagnosis accuracy is improved. And the passive situation of post-treatment of operation and maintenance is changed.

The invention provides a vehicle control method and device, equipment and a storage medium. The vehicle control method comprises the steps that at least two speed limit values are determined; determining a target speed limit value based on the at least two speed limit values; and controlling the speed of the vehicle based on the target speed limit value. The method is used for solving the problem of unreasonable vehicle speed limiting.

The invention discloses a power grid project database processing method and device, equipment and a storage medium. The method comprises the steps that all GIM initial data of a target power grid project and unified management of multi-version and multi-type data are acquired; extracting header information of each piece of GIM initial data, and determining an extension file corresponding to each piece of GIM initial data according to the header information; each piece of GIM initial data is stored in each data table structure; processing each data table structure according to a relational database management system technology so as to extract a unique identifier of each piece of GIM initial data; determining primary key information and foreign key information corresponding to each data table structure; and constructing a target database based on each data table structure, the unique identifier, the primary key information and the foreign key information. According to the processing method of the power grid project database provided by the embodiment of the invention, the efficiency and quality of power grid project data management can be remarkably improved, and a solid technical basis is provided for sustainable development and intelligent upgrading of power grid projects.

The invention discloses an auditing process and authority control management system and method applied to data sharing, belongs to the auditing process and authority control management system and method applied to data sharing, and aims to solve the technical problem of how to realize management control of an auditing process and resource use authority of resource sharing. Comprising a resource data management module, a resource application management module, a resource authorization monitoring module, an authority management module and a message management module, and can realize strict control of auditing processes and use authorities related to resource authorization in a data sharing process. The resource authorization monitoring module and the authority management module are matched to strictly control the use range and the use time limit of resources, and the resource use reasonability and the resource application correctness are guaranteed; rapid application methods such as resource application search, batch application and form content default are provided, the application efficiency is greatly improved, functions such as auditing verification, information notification and batch auditing are provided, and the auditing efficiency is effectively improved.

The invention discloses a civil aircraft cockpit display interface availability evaluation index system construction method, which comprises the following steps: firstly, analyzing pilot human-computer interface interaction cognition through an EPIC model, extracting four-dimensional availability indexes, and preliminarily screening the availability indexes based on the experience and knowledge of a pilot; a civil aircraft cockpit display interface availability evaluation index system is constructed; secondly, in combination with a hierarchical clustering algorithm and a rough set information entropy algorithm, an HC-CEBARKNC algorithm is proposed to perform clustering reduction on the established index system, and a clustering reduction set of indexes of all dimensions is obtained; thirdly, verifying the reliability of each dimension index clustering reduction set by using the classification accuracy of the SVM so as to construct a reasonable civil aircraft cockpit display interface availability evaluation index system; and finally, calculating the weight of each index in the index system by using a rough set conditional information entropy improvement formula. The problem that an index system for civil aircraft cockpit display interface availability research is not comprehensive enough is solved.

The invention relates to a ball valve detection method and a ball valve, and relates to the field of ball valve leakage detection.The ball valve detection method comprises the steps that detection image information of a preset detection area is obtained; determining a left inflation position and a right inflation position according to the detection image information and preset interface features; a preset inflation device is controlled to inflate the left inflation position according to a preset left inflation air pressure value, and after inflation, the left air pressure value of the ball valve is obtained; based on the condition that the left side air pressure value is inconsistent with the left side inflation air pressure value, reporting a left side air leakage prompt; an inflation device is controlled to inflate the right inflation position according to the right inflation air pressure value, and after inflation, the right air pressure value of the ball valve is obtained; reporting a right side air leakage prompt based on the condition that the right side air pressure value is inconsistent with the right side inflation air pressure value; based on the condition that the left side air pressure value is consistent with the left side inflation air pressure value and the right side air pressure value is consistent with the right side inflation air pressure value, air leakage detection is completed. The method has the effect of improving the working efficiency.

The application provides a control method and a control device of compressor operation frequency and a water heater. The control method comprises the following steps: calculating the suction pressure attenuation ratio of the compressor; judging the frost degree of the heat exchange equipment according to the suction pressure attenuation ratio of the compressor; and dynamically setting the initial operation frequency of the compressor according to the frost degree of the heat exchange equipment. The control method further comprises the following steps: comparing the initial operation frequency of the compressor with the historical operation frequency of the compressor recorded in a database; and controlling the actual operation frequency of the compressor according to the comparison result. The control method can guarantee the rationality of the actual operation frequency of the compressor, solve the problem of low defrosting efficiency caused by the fixed operation frequency of the compressor during the defrosting process, and improve the energy efficiency.

The application discloses a kind of collaborative robot job parameter dynamic optimization method, comprising: real-time acquisition of the multimodal sensor data of collaborative robot in the process of job, multiple job parameters are analyzed based on job quality evaluation model to identify key parameter set from it;Multi-objective function is constructed with job time, end force as optimization target, and multi-objective function is converted into single-target optimization function by weighting sum method;Key parameter set is input to machine learning model, and single-target optimization function is used as optimization target to carry out iterative optimization, in each iteration, the standard deviation σ of the current learning result of machine learning model is obtained, according to the comparison result of standard deviation σ and preset critical value s, dynamically select optimization strategy, when σ≥s, new parameter set is generated using random exploration strategy, when σ<s, new parameter set is generated using guided optimization strategy of machine learning model, and the optimized parameter set is output.

The utility model discloses a trimming device, which relates to the technical field of trimming equipment and comprises a supporting seat, a moving component is arranged at the bottom of the supporting seat and used for auxiliary movement of the supporting seat, an angle adjusting component is arranged at the top of the supporting seat, and a first supporting plate is arranged at the top of the angle adjusting component. The angle adjusting assembly is used for adjusting the included angle between the first supporting plate and the horizontal plane. A controller is matched with a color sensor to regulate and control the extension length of two first electric push rods, so that when the color sensor pushed by the two first electric push rods monitors a rough boundary of fistular onion stalk and fistular onion green, the controller controls the two first electric push rods to stop running, and then controls a second electric push rod to extend; the cutter is driven to move downwards to be inserted into the cutter groove to complete cutting of scallion leaves, so that scallion cutting is more regular and attractive, aerobic respiration of scallions is reduced, scallion cutting reasonability is guaranteed, and follow-up selling of scallions is facilitated.

The application provides a method and system for multi-party secure calculation of coefficient of variation, belonging to the field of multi-party secure calculation, and used for providing a new scheme for achieving the task of securely calculating the coefficient of variation of a data group, wherein the multi-party includes an initiator of a calculation task, a referee and a plurality of participants, the participants and the initiator hold private data, the initiator and the referee are two different parties, and the method comprises the following steps: the participants pre-process the data, the referee generates a public key and a private key based on a self-developed homomorphic encryption algorithm, and sends the public key to the participants, so that the private data of all the participants is encrypted, all the participants collect the encrypted data to the initiator, the initiator calculates an encrypted sum, the referee decrypts the sum and sends it to the initiator to obtain a mean value, all the participants calculate variance elements according to the mean value, and the variance elements are segmented, recombined and collected to the initiator, so that the initiator can calculate a standard deviation and then calculate a coefficient of variation.

This invention relates to the field of medical information technology, and in particular to a method and system for generating clinical multi-agent task sequences. The method includes the following steps: acquiring and structuring core clinical objectives, which include patient basic information, clinical indicators, and disease management goals; decomposing the core clinical objectives into several structured sub-objectives with dependencies and execution order based on a clinical pathway template library and a medical knowledge graph; for each structured sub-objective, splitting it into multiple minimum executable clinical sub-tasks according to a clinical sub-task decomposition rule library, and defining the execution subject type, input / output, and dependencies for each clinical sub-task to construct a sub-task-level directed acyclic graph; integrating the sub-task-level directed acyclic graphs, identifying dependencies across structured sub-objectives, generating a global clinical task directed acyclic graph, and performing dependency verification and clinical logic consistency verification.

The invention relates to an airport resource emergency dispatching method under an emergency, belongs to the technical field of resource dispatching, solves the problem that a flight parking stand allocation plan is invalid and difficult to recover due to parking stand service interruption under an emergency, and specifically comprises the following steps: step S0, constructing an initial data set; step S1, constructing a deviation preference dual-objective collaborative optimization evaluation index for an airport emergency scenario; step S2, constructing a dual-objective collaborative optimization emergency dispatching model; step S3, obtaining a single-objective optimization model; step S4, solving the single-objective optimization model to obtain an optimal feasible solution; step S5, continuing to execute steps S3 to S4 to obtain optimal feasible solutions of multiple single-objective optimization models, until the number of optimal feasible solutions reaches a set number requirement; step S6, obtaining multiple optimal solutions, generating a final aircraft parking stand dispatching plan, and executing the parking stand dispatching.

The present invention belongs to the field of sample control technology, and specifically discloses a fully automatic sample test tube online refrigerator control system, which includes: a placement information import module, a sample status monitoring module, a placement status analysis module, a sample failure processing terminal, an environmental difference analysis module, an information library, and an environmental control execution terminal. The present invention analyzes the sample placement status according to the monitoring information and identification information of each placed sample, and performs failure processing and placement difference analysis according to the placement status, and then confirms the control information, thereby avoiding the one-sidedness of currently relying only on the instant analysis and control of the currently collected monitoring data, and realizes the periodic tracking and analysis of different placed samples, thereby ensuring the timeliness and effectiveness of the environmental control of the placed samples and the timeliness of the processing of invalid samples, while ensuring the stability and activity of the placed samples as much as possible, providing a guarantee for the subsequent call of samples.

The invention relates to a self-adaptive management method and system for a database plan cache, and the method comprises the steps: firstly judging whether the plan cache is hit or not after a database receives an SQL statement, and triggering a hard analysis generation plan and caching the plan when the plan cache is not hit; if the cache is hit, further judging whether a corresponding multi-execution plan exists or not; and when only a single execution plan exists, analyzing the relationship between the number distribution of execution tuples and the number of execution times by adopting an execution efficiency algorithm to dynamically judge whether the data is inclined. And when a plurality of execution plans exist, entering a multi-plan cache management stage, selecting the execution plans according to a matching result of the current binding variable predicate selection rate and the cache plan historical selection rate, and generating and caching a new plan when the matching fails. According to the method, the data skew is accurately identified by executing the efficiency algorithm, intelligent matching and multiplexing of plans are realized by means of a multi-plan cache management mechanism, and the overall performance of the database in a data skew scene is improved.

The present invention belongs to the field of road vehicle control and relates to the judgment or calculation of driving parameters of a road vehicle driving control system. Specifically, it relates to a method for calculating the drivable interval of a bus and a carpool shared lane based on utility selection. The method establishes a utility selection function based on carpool vehicles and constructs a probability selection model of carpool vehicles and a calculation model for the length of the drivable interval. When calculating the length of the drivable interval, the differences in traffic demand in different time periods are considered. The method can scientifically and reasonably dynamically adjust the length of the drivable interval of the bus and carpool shared lane to adapt to different traffic flow states, avoid local congestion caused by unreasonable interval settings, ensure the rationality of resource allocation of the bus and carpool shared lanes, and optimize the utilization efficiency of the shared lanes.

The invention discloses an analog signal range judgment and switching system with calibration and self-diagnosis functions, which relates to the technical field of analog signal monitoring and comprises an analog signal acquisition module, an analog signal range analysis module, an analog signal range switching module and a database, the method comprises the following steps: firstly, analyzing the influence of different environment temperature intervals on the optimal linear interval of the ADC to obtain the optimal linear interval of the ADC in the different environment temperature intervals, determining the optimal linear interval of the ADC according to the current environment temperature, and judging whether an analog signal falls into the optimal linear interval of the ADC and whether the current range gear loses efficacy; and then the target range gear is obtained by analyzing the influence among the range gears under different gear working conditions, and the current gear is switched to the target range gear, so that the effectiveness of range analysis and the precision of ADC sampling are guaranteed, and the rationality of range switching is also guaranteed.

The application provides a multi-round reasoning network traffic prediction method and device based on size model cooperation, which comprises the following steps: inputting historical traffic data into at least two time series prediction models, obtaining prediction results and calculating comprehensive confidence based on prediction errors, and generating a prediction effect ranking; inputting historical data, prediction results and confidence into a large language model, and evaluating and ranking the prediction effect of each model by the large language model; comparing the two rankings, and if they are consistent, calibrating and optimizing the large language model, and if they are inconsistent, adopting an independent adjustment strategy to enhance the sensitivity of the prediction results of the model with the best ranking, and obtaining target prediction results. Through the two-way comparison of the independent ranking of multiple models and the evaluation ranking of the large language model, the large language model can be isolated when the rankings are inconsistent, and an independent adjustment strategy is adopted, thereby effectively avoiding the direct impact of the reasoning deviation of the large language model on the prediction results, and improving the robustness and accuracy of network traffic prediction.

The present invention discloses a processing method, device, equipment and storage medium for a power grid engineering database, wherein the method includes obtaining all GIM initial data of a target power grid engineering and unified management of multi-version and multi-type data; extracting header information of each GIM initial data, and determining the extension file corresponding to each GIM initial data according to the header information; storing each GIM initial data in each data table structure; processing each data table structure according to relational database management system technology to extract a unique identifier for each GIM initial data; determining the primary key information and foreign key information corresponding to each data table structure; and constructing a target database based on each data table structure, unique identifier, primary key information and foreign key information. The processing method for a power grid engineering database provided by an embodiment of the present invention can significantly improve the efficiency and quality of power grid engineering data management, and provide a solid technical foundation for the sustainable development and intelligent upgrading of power grid engineering.

The invention discloses an intelligent construction engineering operation and maintenance management platform and method, and relates to the technical field of intelligent construction engineering.The intelligent construction engineering operation and maintenance management platform comprises a shopping mall information acquisition module, a shopping mall noise evaluation module, a shopping mall noise processing module, a display terminal and a database. Equipment noise and people stream noise are classified and processed, so that the reasonability of a noise processing mode of a shopping mall is effectively guaranteed, the noise processing quality is improved, the customer satisfaction degree is improved, the proportion of return customers is guaranteed, and the health problems of hearing loss, pressure increase, sleep disorder and the like of employees are avoided; according to the method, the group labels of the abnormal noise sub-regions in the shopping mall are generated, the noise processing urgency of each region in the shopping mall is analyzed, the reasonability of the noise processing sequence of each region in the shopping mall is guaranteed, the balance of the noise in the shopping mall is optimized, and the noise processing efficiency of the shopping mall is improved.

The embodiment of the present application provides a method, device, navigation server and storage medium for determining a recommended route, wherein the method includes: obtaining multiple routes from a first location to a second location; performing a first sorting on the multiple routes at least according to a first driving index, and determining the route ranked first in the first sorting as a main route; selecting at least one alternative route from the multiple routes whose second driving index is better than the main route, and whose comprehensive driving index is not lower than the route that has the same ranking as the alternative route in the recommended route in the first sorting; wherein the main route and the alternative route form a recommended route, the first driving index is different from the second driving index, and the comprehensive driving index includes a combination of multiple driving indexes. The embodiment of the present application can increase the diversity of alternative routes, so that users have a variety of optional routes when selecting a navigation route, so as to facilitate users to select a navigation route.

The invention relates to the technical field of LCD screen detection, in particular to an LCD surface mounting detection device and method, and the device comprises an AOI detection platform which is used for carrying out the optical detection of an LCD screen; the detection analysis module is used for analyzing the obtained optical detection result; the sorting module is used for sorting the LCD screens to different conveying belts according to the analysis result of the detection and analysis module; the chip mounting platform is used for carrying out chip mounting on the LCD screens meeting the chip mounting requirements; and the moving module can move the LCD screens which are sorted by the sorting module and meet the surface mounting requirements to a surface mounting platform. The AOI detection platform and the surface mounting platform are arranged adjacently, so that transmission between different procedures is reduced, the production stability is guaranteed, and the qualified rate of products is increased.

The application discloses a kind of based on multi-sensor's grid map two-way asynchronous construction method and system, the method includes: obtaining three-dimensional point cloud data, RGB image and depth map;Based on the space corresponding relation of RGB image and three-dimensional point cloud data, three-dimensional point cloud data is semantically labeled;Three-dimensional point cloud data, RGB image and depth map are timestamped alignment, coordinate transformation and filtering processing, obtain final point cloud data, with semantic point cloud data point cloud data is spatiotemporal alignment generation fusion point cloud data as semantic grid map input;Construct semantic grid map, adopt the two division strategies of front view map and rear view map, by independent thread asynchronous update;Establish motion object database and predict dynamic object motion trajectory based on time sequence prediction algorithm, update in semantic grid map synchronously.The application effectively guarantees the intelligent device obstacle avoidance success rate and path planning rationality, guarantee the operation safety and efficiency under complex environment.