154results about How to "Implement update" patented technology

The invention discloses a task integrity judgment method for multi-device cooperative work under complex constraint conditions. The method comprises the steps that a comprehensive data collection system is established, multi-dimensional data of cooperative devices are collected in real time and preprocessed, constraint modeling is combined, and the complex constraint conditions are quantified into a computable constraint condition model; a multi-agent collaborative evaluation model is constructed, each device participating in collaborative work is regarded as an agent by the multi-agent collaborative evaluation model, and evaluation of the integrity of the whole task is achieved by simulating the collaborative process between the devices; automatically extracting advanced features from the multi-dimensional data by using a deep learning technology; and a distributed real-time analysis system is designed, and large-scale data processing and continuous model optimization are realized in combination with an adaptive optimization mechanism. According to the method, the reliability and efficiency of the cooperative task can be improved, powerful support can be provided for equipment task decision making, and the method plays an important role in improving the intelligent level of application guarantee and the decision making accuracy.

The invention relates to the technical field of electrical digital data processing, in particular to an anomaly detection and processing method and system based on deep learning. The method comprises the following steps: firstly, performing feature extraction and fusion on a log text sequence, a log timestamp sequence and a running state index sequence set to obtain an initial feature vector sequence; then, constructing a hierarchical graph neural network to perform feature updating, propagation and fusion on the initial feature vector sequence to obtain a multi-level fusion feature vector sequence, and calculating a standardized mode vector sequence in combination with a log text sequence and a running state index sequence set; obtaining a self-adaptive abnormal threshold value according to the standardized mode vector sequence and detecting candidate abnormal logs; and finally, verifying the candidate abnormal logs, determining verified abnormal logs, classifying the verified abnormal logs, generating a processing suggestion text according to a classification result, and carrying out early warning prompt. The false detection rate can be reduced, and the log anomaly detection accuracy is improved.

The invention discloses a cache processing method of heterogeneous equipment, a heterogeneous system, a product, a device and a medium, and relates to the technical field of data storage. And according to the target virtual address access times corresponding to each device in the heterogeneous system, realizing a global data caching mechanism. And determining a file page corresponding to the target heterogeneous device based on the target virtual address access frequency, so that the file system layer has the capability of managing the memory cache of the heterogeneous device. And the predicted file page of the target heterogeneous device is verified, and the file page is moved under the condition that the verification is passed, so that the distribution accuracy of the target heterogeneous device is improved. The file page of the target heterogeneous device is mapped and moved to the memory of the host side, the target heterogeneous device does not need to be accessed, the file page stored in the memory of the processor is directly accessed, the increased access rate of the processor accessing the target heterogeneous device is avoided, the delay of accessing the memory of the target heterogeneous device is reduced, and the access efficiency is improved. And the data transmission rate and the system efficiency of the heterogeneous system are improved.

The invention provides a large-scale language model knowledge editing method and device based on pattern matching, and the method comprises the steps: obtaining target editing knowledge which is used for carrying out the knowledge updating of a large-scale language model; determining a plurality of mode matching degrees between each level in the large language model and the target editing knowledge; determining the highest mode matching degree in the plurality of mode matching degrees, and taking the hierarchy corresponding to the highest mode matching degree as a target editing layer; performing rank-one editing on the multi-layer perceptron of the target editing layer based on the target editing knowledge to obtain an edited large language model; according to the method and the device, other irrelevant data is not influenced while knowledge editing is accurately carried out.

The invention relates to an uncertainty online evaluation method based on time sequence data decomposition and a Bayesian principle, and aims to solve the problem that a traditional uncertainty evaluation method is difficult to process online and dynamically update. The method comprises the following steps: firstly, collecting measurement data within a certain time range, constructing a time sequence data set, and decomposing the time sequence data into a trend period item and a random item through an STL decomposition technology; then, on the basis of the data of the random item, parameters of prior distribution and a likelihood function are calculated by using a Bayesian statistical method, joint posterior distribution is further determined, and the uncertainty of a measurement result is calculated on the basis of the posterior distribution; afterwards, the posterior distribution result at the current moment is used as the prior information of uncertainty evaluation at the next moment to be fused and updated with the new observation data, so that the real-time online evaluation of the measurement uncertainty is realized. The method not only improves the accuracy and real-time performance of the evaluation result, but also realizes the continuous updating and optimization of the measurement information, and is suitable for a complex and rapid-change measurement environment.

The invention discloses an ad-hoc network type dual-mode communication system integrating HPLC and HRF, which comprises a dual-mode communication unit, a central coordinator, a quasi-quantity acquisition module, an adaptive networking module and an automatic route repairing and updating module, and is characterized in that the dual-mode communication unit comprises an HPLC carrier module with a receiving and transmitting end and an HRF wireless module with a receiving and transmitting end; the dual-mode communication unit further comprises a communication modulation module and a signal equalization processing module. The invention relates to the technical field of network communication. According to the ad hoc network type dual-mode communication system integrating the HPLC and the HRF, the whole dual-mode communication is more stable and reliable by adopting communication modulation and signal equalization processing, and the purposes of ensuring the stability of the dual-mode communication, eliminating interference caused by a multipath effect and optimizing the system performance are well achieved; according to the invention, the security of networking communication can be improved by carrying out comprehensive security analysis processing on each sub-node before networking.

According to the multi-source information fusion robot positioning method and system for the unstructured environment provided by the invention, fusion processing is carried out on multi-source information data such as laser point cloud, environment image information and acceleration which are acquired in real time, so that the multi-source information fusion robot positioning method and system for the unstructured environment can be realized in a severe weather state and a dynamic unstructured environment. Carrying out high-robustness real-time positioning under the condition of violent illumination change; in a geometrically degraded roadway area, registration positioning of laser point cloud emission fails due to lack of enough external characteristics, and at the moment, the visual positioning module can still work normally and complete robot repositioning by detecting matched image information; in an environment lacking enough illumination, the laser point cloud and acceleration information can still provide enough positioning fusion data input for the computing unit.

The invention belongs to the technical field of human resource data processing, and provides a talent selection standard-based enterprise relation knowledge graph construction method and system, and the method comprises the following steps: obtaining an enterprise relation knowledge graph of a to-be-queried enterprise, and obtaining the enterprise data of each enterprise in the enterprise relation knowledge graph; screening out expired associated enterprises according to the enterprise data; and updating the enterprise relationship knowledge graph according to the expired associated enterprises, and outputting the updated enterprise relationship knowledge graph. According to the construction method provided by the embodiment of the invention, real-time monitoring and updating of enterprise activities are realized through data interaction with an attendance checking system or an internal mobile application program of an enterprise, and the timeliness and practicability of the enterprise relational knowledge graph are ensured.

The invention discloses an airborne multi-source integrity monitoring method and device for an aviation navigation operation network, and belongs to the field of satellite navigation, and the method comprises the steps: constructing an overall design architecture of an airborne multi-source high-performance navigation receiver; an ionosphere gradient monitoring algorithm based on carrier phase difference is provided, IGM detection statistical error characteristics of the carrier phase are researched, an ionosphere gradient monitoring threshold is established, and a switching mechanism from an airborne DFree mode to an IFree mode is realized; an aviation navigation multipath mitigation suppression algorithm is researched, multivariate feature extraction of observation data is combined, an observation data feature matrix is established, a parallel time convolutional neural network architecture is designed, and the weight is updated through a stochastic gradient descent method. According to the airborne multi-source integrity monitoring method and device for the aviation navigation operation network provided by the invention, accurate monitoring of the ionosphere gradient is realized, a switching mechanism between a DFree mode and an IFree mode is optimized, and the integrity monitoring capability and the system availability of the aviation navigation operation network are improved.

The invention provides a method and system for determining a water quality risk value of industrial sewage, and the method comprises the steps: obtaining water quality monitoring data of different monitoring points, obtaining a physical index parameter, a chemical index parameter and a biological index parameter, and constructing a water quality parameter of a target water area; the method comprises the following steps: training historical physical index parameters, historical chemical index parameters and historical biological index parameters of historical water quality monitoring data to obtain a water quality monitoring deduction model, and deducing water quality parameters of a target water area through the water quality monitoring deduction model to obtain an initial water quality risk value; the corresponding actual index parameters are obtained by updating the water quality monitoring data of different monitoring points in real time, the parameters of the water quality monitoring deduction model are optimized, and the optimized water quality risk value is obtained through deduction again. The industrial sewage is subjected to multi-index analysis, the water quality risk trend is predicted, and the water quality monitoring accuracy of the industrial sewage is improved.

The invention belongs to the technical field of data processing. The invention provides a spatio-temporal data prediction method and system for heterogeneous photovoltaic diagram structure data fusion, and the method comprises the steps: a current client obtains a photovoltaic power generation prediction result of the current client at each moment in the future after a current moment based on the historical photovoltaic power generation data of the current client and a trained global model; the global model training process comprises the steps that the central server distributes a global model pre-trained according to a photovoltaic generating capacity data set to all clients, and each client trains the global model through independent local graph data to perform local updating; each client uploads a local update result to a central server for aggregation, and the central server trains a GCN part of a global model according to an aggregation result and distributes the trained global model to each client for use; on the premise of ensuring data privacy of each client, updating and training of a global model are realized, and prediction comprehensiveness is greatly improved.

The invention belongs to the field of energy storage system frequency control, and discloses a safety reinforcement learning load frequency control method, system and device and a medium, and the safety reinforcement learning load frequency control method comprises the steps: constructing a frequency control model; acquiring historical data of the power system to construct a labeled data set; constructing a cost prediction network according to the label data set, taking the state and action of the frequency control model as the input of the cost prediction network, and predicting the control cost at the current moment; constructing a deep reinforcement learning controller, and converting an inequality constraint of a target function in the deep reinforcement learning controller based on a Lagrange multiplier; and according to a conversion result, optimizing an actor network of the deep reinforcement learning controller by predicting the control cost at the current moment, and applying the optimized actor network to real-time load frequency control to realize control of the load frequency. Operation cost and frequency modulation performance of the power system are considered, and comprehensive benefits of the power system are guaranteed.

The invention discloses an artificial intelligence and machine vision-based design and manufacturing method and system for a dock folded structural member, computer equipment and a readable storage medium. Comprising the following steps: constructing an initial 3D printing model of the dock folding structural member; in the 3D forming printing process, an infrared thermal imaging method is adopted to detect printing defects in real time, a convolutional neural network is utilized to extract image features of real-time infrared thermal imaging, the extracted image features are detected and recognized to obtain different defect types, initial printing parameters are adjusted according to a feedback result, and target printing parameters are obtained; carrying out X-ray nondestructive testing on the dock collapsed structural member, and obtaining internal structure defect parameters; and according to the internal structure defect parameters, the size correction amount is obtained, and target structure parameters and a target 3D printing model are obtained. By adopting artificial intelligence and machine vision methods, defects can be efficiently and accurately found and recognized, printing parameters are corrected, a target model is updated, and the product size and performance precision are improved.

The embodiment of the invention provides a point cloud registration method and device and intelligent mobile equipment, and relates to the field of artificial intelligence. The method comprises the following steps: acquiring a to-be-registered point cloud; determining an initial pose of the intelligent mobile device in a preset global coordinate system when the to-be-registered point cloud is generated; determining a target global pose of the to-be-registered point cloud in a global coordinate system based on the initial pose and distance values and normal vectors recorded by each grid of a preset grid map; wherein the distance value and the normal vector recorded by each grid of the grid map are obtained by updating the registration result of each frame of environment point cloud before the to-be-registered point cloud; and determining a registration result of the to-be-registered point cloud based on the target global pose. By applying the scheme provided by the embodiment of the invention, the global pose of each frame of environment point cloud detected by the intelligent mobile equipment in the global coordinate system can be determined in the process of constructing the scene map of the strange scene into which the intelligent mobile equipment enters.

The invention discloses a method for remotely measuring gas concentration two-dimensional distribution based on an absorption spectrum technology, and belongs to the technical field of gas monitoring and remote measurement. On the basis that the unmanned aerial vehicle is used for mounting a telemetering laser receiving and transmitting device to inspect the natural gas pipeline along the line, as the natural gas pipeline is buried underground, when a leakage point appears on the natural gas pipeline, a leaked natural gas mass is formed on the ground surface where the natural gas pipeline is buried; a remote measuring laser receiving and transmitting device carried by the unmanned aerial vehicle is used for detecting an area where the natural gas concentration exceeds a threshold value, and therefore the natural gas pipeline leakage point position is judged. According to the method, the high natural gas area can be more accurately positioned, so that the pipeline leakage point is deduced, the local constraint variable strategy is adopted, the resolving stability is improved, and artifacts or invalid data are avoided. And real-time generation and updating of a concentration distribution diagram are realized through simultaneous scanning and resolving.

The invention discloses an encryption communication method and system based on biological genetic coding chaos driving, and the method comprises the steps: receiving an original bit stream and an initial secret key, and generating a chaos sequence group according to the initial secret key through two hyperchaos models; performing DNA coding encryption on the original bit stream by using the chaos sequence to obtain a gene transmission sequence, and performing DNA decoding on the gene transmission sequence to obtain a transmission bit stream; performing constellation mapping on the transmission bit stream to obtain a constellation diagram, and performing subcarrier scrambling, symbol scrambling and constellation rotation on the constellation diagram according to the chaos sequence; performing OCDM modulation on the constellation diagram through an inverse discrete Fresnel transformation matrix to obtain a transmission signal; hiding the initial key in a frame header of a transmission signal, and sending the transmission signal to a receiver through a transmitter; according to the invention, multi-layer encryption of the OCDM signal and dynamic secret key follow-up transmission are realized.

The invention relates to the technical field of image processing, and discloses a medical image denoising method based on a 3D chaotic mapping dung beetle algorithm, and the method comprises the following steps: 1, inputting a to-be-processed original medical image, carrying out the noise adding of the original medical image, and generating a noisy image; step 2, inputting the noisy image into a hybrid filter used for denoising the image; 3, calculating an optimal parameter combination of each filter in the hybrid filter by adopting a dung beetle optimization algorithm, and configuring the hybrid filter by adopting the optimal parameter combination; step 4, performing denoising processing on the noisy image by using the configured hybrid filter to generate a denoised image; wherein in the step 3, the distribution position of the population is initialized by adopting 3D chaotic mapping; the technical problem of poor medical image denoising effect in the prior art is solved.

The invention relates to a method and system for updating firmware in an electronic control unit of a vehicle and electronic equipment. The method can comprise the following steps: in response to a starting instruction of a target updating process of target firmware in a target electronic control unit, reading a target updating mirror image file corresponding to the target firmware; analyzing the target updating mirror image file according to a target information format corresponding to the target electronic control unit to obtain target updating information; determining a target information sending mode based on a target configuration file of a plug-in in the upper computer; and in response to an execution instruction of the target updating process, sending the target updating information to the target electronic control unit according to the target information sending mode so as to perform firmware updating. According to the method, the information sending mode is determined based on the target configuration file of the plug-in in the upper computer, so that the method adapts to upgrading protocols of different manufacturers and vehicle types, modular development and management of OTA upper computer functions are achieved, development and test complexity is reduced, and reusability and universality of tools are improved.

The invention discloses a method, a system and a device for remotely updating an FPGA device and a storage medium, which are used for simplifying the updating process of the FPGA device and reducing the updating maintenance cost. The method comprises the following steps: a test instrument receives an update file and an update instruction issued by an upper computer through a network port; the ARM processor of the test instrument analyzes the update file according to the update instruction and a preset format and packages an analysis result into message information in a paging manner; the ARM processor sends the message information to an FPGA (Field Programmable Gate Array) of the test instrument through a serial communication interface; and the FPGA analyzes the received message information and generates a Flash standard instruction, and performs read-write operation on a Flash memory through the Flash standard instruction so as to update the code of the FPGA.

The invention discloses a transformer abnormal state diagnosis and early warning method based on voiceprint characteristics. The method comprises the following steps: acquiring a network topological graph and voiceprint information of a transformer network node; the method comprises the following steps: dividing a transformer into category voiceprint information data by using a support vector machine algorithm, generating a category voiceprint data set, establishing a transformer abnormal voiceprint data optimization model, and updating and outputting transformer abnormal state voiceprint features by using feature smoothing processing according to the transformer abnormal voiceprint data optimization model. And according to the abnormal voiceprint map feature database, through similarity analysis, generating a transformer abnormal state analysis result and outputting the transformer abnormal state analysis result. According to the method, the transformer voiceprint information can be recognized and updated in a complex sound field environment by optimizing and smoothing the voiceprint features, so that the precision and robustness of a subsequent fusion diagnosis model are improved, and the abnormal state diagnosis and early warning effects of the transformer are further improved.

The invention discloses a hyperspectral image clustering method and system based on a spatial-spectral joint dynamic hypergraph, and the method comprises the steps: determining a low-rank representation coefficient of a hyperspectral image, and obtaining a Laplace regular term of the hyperspectral image hypergraph and the weight of a hyperedge; according to the Laplacian regular term and the weight of the hyperedge, constructing a similarity-maintained low-rank subspace representation optimization model of the hypergraph structure; iteratively solving the low-rank subspace representation optimization model for keeping the similarity of the hypergraph structure to obtain a final low-rank representation coefficient, determining a Laplacian regular term of a new hypergraph and the weight of a hyperedge according to the low-rank representation coefficient solved in each round in the iteration solving process, and calculating the weight of the hyperedge by utilizing the Laplacian regular term of the new hypergraph. Performing the next round of solution; and determining a clustering result of the hyperspectral image according to the final low-rank representation coefficient. And the clustering precision is improved.

The invention discloses an auxiliary tool management method and system for a steel structure construction site, and relates to the technical field of construction site tool management.The method comprises the steps that firstly, auxiliary tools needed by steel structure construction are provided with RFID tags, basic information of the auxiliary tools is written into the tags, and the tags are uploaded to a digital management platform; defining the authority of each worker, and allocating different authority levels; an identity identification code is distributed to each worker, and the worker needs to carry out identity verification when borrowing and returning the tool; when the tool is borrowed, the digital management platform judges whether the worker has permission or not, and if yes, information is recorded and the state of the tool is updated; when the tool is returned, the digital management platform confirms the returning action, updates the tool state and records the returning time; and the digital management platform records the use information of the tool and manages the use condition of the tool. The method has remarkable progress in the aspects of improving the management efficiency, enhancing the safety and the like, and the auxiliary tool management efficiency of the steel structure construction site is effectively improved.

The invention discloses an intensive care unit video visiting management method and system based on image acquisition, and relates to the technical field of video visiting, the intensive care unit video visiting management method based on image acquisition comprises the following steps: acquiring an intensive care unit image in real time, and preprocessing the intensive care unit image; identifying a patient action image by using an intensive care unit image identification method, and analyzing whether the patient actions are the same or not; judging the state of the patient according to an analysis result, adjusting visiting times of the medical staff, and generating a visiting management table; and storing the generated visiting management table to a video platform, and updating in real time. According to the method, whether the actions of the patient are the same or not is analyzed, the visiting times of the medical personnel are flexibly adjusted, and resource allocation is performed according to the stability of the state of the patient, so that the optimization of visiting management is facilitated, the manpower resource and time cost is effectively reduced, the working efficiency is improved, and the medical personnel are ensured to more accurately pay attention to the needs of the patient.

The present invention discloses a method and system for integrating and fusing noise maps and automatic monitoring data, including the following steps: noise monitoring data and noise map basic data are processed to generate noise map data, and the data is published on a map interface to realize the integration of noise map and noise online automatic monitoring system; noise monitoring data, sound source attribute data, and noise map layers are associated using a database format, and a format in which data points and data contents are separated is adopted, and multi-level noise data is added to meet the requirement of segmenting and calculating data after the noise map and noise online automatic monitoring system are integrated; after the noise map and noise online automatic monitoring system are integrated, the noise map is corrected by automatic updating. The present invention has the following advantages and effects: the noise map and noise online automatic monitoring system are integrated, and the noise map can be continuously corrected by automatic updating.

The invention discloses an information security vulnerability processing system and method, and particularly relates to the technical field of computer security, and the system comprises a network monitoring module, an intrusion detection module, an abnormal network information detection module, an early warning module and an intrusion tracking module, illegal intrusion behaviors are collected through log records, the intrusion detection module judges the legality of network access by detecting data streams of a network, keyword matching is conducted on the captured data streams, and the abnormal network information detection module conducts abnormal information detection on the received data streams. The early warning module automatically responds to the detected network vulnerability, and the intrusion tracking module adopts information tracking to judge the trace of an attack intruder. Various network risks can be assessed by monitoring various data in the network and centralizing the data captured by the monitoring points in the abnormal network information detection module for processing.

The invention provides a fabricated intelligent ecological guardrail, which comprises a main body structure module, a communication module and a digital support module, and is characterized in that the main body structure module comprises a plurality of main body frame support sub-modules, a solar power generation and energy storage sub-module, a rainwater collection sub-module, a wall body sub-module, a green plant growth sub-module and a data acquisition and feedback device; the main body structure module performs data interaction with the digital support module by using the communication module; through the assembly type module design, digital management and operation maintenance, the problems ubiquitous in the field of existing protection facilities can be effectively solved in a targeted mode, and the greening and beautifying effects on the environment can be achieved while physical protection is guaranteed. Modular production, convenient transportation, rapid installation and deployment and rapid disassembly can be achieved, the height, strength and perspectivity can be set according to the weather, season, pedestrian flow and other conditions of the implementation environment, and a protection scheme can be rapidly updated through the assembly type prefabricated modules.

The invention relates to an exoskeleton bionic power-assisted curve generation method for human body non-stationary motion. The synchronization and bionic capability of an ankle joint exoskeleton robot power-assisted curve for human body non-stationary motion is improved. The method comprises the following steps: acquiring direction angle data of a shank of a human body by using an inertial measurement unit, and taking the data as an independent variable of a power-assisted curve; designing a power-assisted curve model modeling method based on a double-Gaussian function to realize shape planning of a power-assisted curve; estimation of model parameters is realized by utilizing measurement data of the two inertial measurement units on the shank part and the instep part of the human body, and the similarity between an exoskeleton assistance curve and a human body biological moment curve is improved. According to the method, design is conducted from the two dimensions of the independent variable and the model of the power-assisted curve, the man-machine motion synchronization capacity of the power-assisted curve under the non-stable motion of the human body and the bionic capacity of the power-assisted curve and the biological moment curve of the human body are guaranteed respectively, and the exoskeleton robot can be promoted to be applied to complex and unstructured task scenes.

The invention provides a voice updating method and device for an intelligent voice air conditioner and the air conditioner, and the method comprises the steps that under the condition that a voice control function of the air conditioner is started, voice data of a user is obtained; and if the control instruction corresponding to the voice data is not recognized and a control instruction input by the user in a non-voice manner is received within a preset time length, binding the voice data with the control instruction input in the non-voice manner. According to the embodiment of the invention, under the condition that the control instruction corresponding to the voice data is not recognized and the control instruction of non-voice input is received in a short time, the voice data can be set as the voice data of the control instruction, and the updating of the voice data corresponding to the control instruction is realized, so that the coverage rate and the recognition accuracy of voice control are improved, and the user experience is improved. And the user experience is optimized.

The embodiment of the invention provides a memory device. The memory device includes a memory cell array including a plurality of memory cells and a plurality of redundant memory cells; the plurality of redundant memory cells are configured to repair a faulty memory cell among the plurality of memory cells; the fault address storage circuit is used for storing at least one first fault address corresponding to the first fault storage unit; a repair logic memory circuit including a plurality of first memory structures and a plurality of second memory structures; redundant addresses corresponding to a plurality of redundant storage units are stored in the plurality of first storage structures, and a first fault address is stored in the second storage structure; the repair logic storage circuit is configured to receive a first operation mode command, wherein the first operation mode command comprises at least one second fault address corresponding to a second fault storage unit; the second fault storage unit is different from the first fault storage unit; a second fail address is written to the second storage structure in response to the first mode of operation command.