18results about How to "Implement automatic selection" patented technology

The embodiment of the application provides a kind of fog computing system, method, electronic equipment and storage medium, applied to fog computing technical field, server, receives the computing instruction sent by user;First computing request for executing target algorithm analysis task is sent to first fog computing device;First fog computing device, for receiving first computing request;According to the algorithm identification and the computing resource information required for executing target algorithm analysis task, it is judged whether itself can execute target algorithm analysis task, and the second computing request of fog computing task is generated and sent to second fog computing device;Second fog computing device, receives second computing request;According to the algorithm identification required for executing target algorithm analysis task, the algorithm required for executing target algorithm analysis task is obtained from server, and target algorithm analysis task is executed.The application can realize the automatic selection of fog computing device and the automatic deployment of fog computing task, and improve the utilization efficiency of resources in fog computing system.

The present invention belongs to the technical field of wind tunnel test control, and discloses a method for automatic range selection and fault tolerance of a total pressure sensor of a high-speed wind tunnel. The method issues test conditions through a wind tunnel operation management computer, and the wind tunnel core controller automatically selects a total pressure sensor of a suitable range according to the size of the target total pressure value, closes the electromagnetic on-off valve of the total pressure sensor gas circuit that is smaller than the suitable range, and opens the electromagnetic on-off valve of the total pressure sensor gas circuit of the suitable range and above. After the test starts, the wind tunnel core controller collects the readings of all the total pressure sensors of the opened range. If the difference between the measured value of the total pressure sensor of the maximum range and the measured value of the total pressure sensor of the selected range is greater than the set threshold, the wind tunnel core control software automatically uses the measured value of the total pressure sensor of a higher range as the total pressure control feedback value. The method realizes the automatic selection of the total pressure sensor range, reduces the workload of manual operation, avoids operational errors, and ensures the safe conduct of the wind tunnel test.

The invention discloses a current transformer on-site verification auxiliary wiring robot, which comprises a clamping jaw cylinder, a tensioning device and a pre-wiring line, and is characterized in that the upper part of the clamping jaw cylinder is provided with two clamping jaws capable of moving in opposite directions, the clamping jaws are respectively connected with an extension block, and the upper part of the extension block is provided with a semicircular gap; a mounting frame is connected to the upper portion of the clamping jaw air cylinder, a hexagonal sleeve is arranged on the upper portion of the mounting frame, a circular sleeve is welded to the lower portion of the hexagonal sleeve, a rotating sleeve is welded to the lower portion of the circular sleeve, and a through hole allowing the rotating sleeve to penetrate through is formed in the mounting frame. According to the invention, through integrated application of the magnetic device, the camera and other components, automatic selection and state monitoring of pre-wiring are realized. In the process, the magnetic device utilizes the electromagnet to adsorb the pre-connection wire, the camera is responsible for capturing the state information of the pre-connection wire, and through accurate control of the clamping jaw air cylinder, the advantage of accurate movement and positioning of the pre-connection wire is achieved.

The present application discloses a method, device and system for testing an operating system integrating multiple chips, belonging to the field of chip testing technology. The method includes: receiving input data from a user in a running panel of a test script; the test script is used to test multiple different chips with at least partially identical functional instructions; selecting a target chip for testing according to the input data; using the test script to test the operating system of the target chip using a target command parameter set. The present application establishes the same test script for multiple different chips with at least partially identical functional instructions, tests different chips by changing input data and command parameters, and realizes integrated testing of multiple chips with a single test process. Different chips can also interact with each other, and different command parameters can be tested by modifying the value of the command parameter. There is no need to write code for each command parameter test, which reduces code redundancy and improves test efficiency.

The application provides an information processing system. An information processing system, characterized by comprising: a processor; wherein the processor is configured to: receive information related to a health status from a user; parse the received information using a generative artificial intelligence model and generate a prompt word indicating that the generative artificial intelligence model parses the information to diagnose a possible disease name; query a database to determine the severity of the diagnosed disease name, and generate a prompt word indicating that the generative artificial intelligence model evaluates the severity based on the database.

The invention discloses a lithium battery residual service life prediction method based on an MFO-SVM model, and relates to the technical field of lithium battery residual service life prediction.The method comprises the steps that 1, data collection is conducted, and a lithium battery is subjected to repeated charging and discharging experiments at the room temperature of 24 DEG C; 2, characteristic parameter selection: starting from the monitorable performance parameters, namely indirect performance parameters, extracting multi-aspect external characteristic parameters such as voltage and current from the parameters as indirect health factors for evaluating the performance degradation of the battery; step 3, an MFO-SVR prediction model is constructed; and 4, checking and evaluating the constructed MFO-SVR prediction model. The method has the advantages that the potential relationship between the characteristic parameters capable of representing the lithium ion battery RUL and the lithium ion battery RUL is deeply excavated, and four indirect health factors capable of representing the performance degradation of the battery are relatively comprehensively extracted from a battery discharge characteristic curve and a charging process; and the capacity is used as the output, so that the operability is high.

The application provides a kind of magnetic resonance image automatic scanning planning method, system, medium and terminal, the present application will be collected with multimodal prior image spatial alignment of localization image;Three-dimensional features are extracted from the spatial alignment of localization image and multimodal prior image respectively, and the three-dimensional features are associated and matched, and the fusion features are obtained by fusion;Finally, based on the fusion features, the positioning center, the positioning frame and the recommended coil are calculated.The present application solves the technical problems of existing medical image scanning planning technology, such as complex multimodal data, low automation, insufficient efficiency and accuracy, low data utilization, etc.Through efficient processing of multimodal feature data and automatic planning of the whole image scanning process, the positioning point and the positioning frame are automatically selected, and the coil suitable for the patient is recommended.

The invention discloses a two-wheeled vehicle fast and slow charging compatible charging method and device based on user preferences, and the method comprises the steps: setting battery coding information in a battery, thereby rapidly determining whether the battery supports fast charging or not based on the battery coding information, directly carrying out slow charging under the condition that fast charging cannot be carried out, and improving the charging efficiency. And when it is determined that fast charging can be carried out, user preference information can be determined through the cloud, and the charging mode can be automatically determined according to the user preference information. According to the embodiment of the invention, the automatic selection of the charging mode can be realized, and the charging experience of a user can be improved to a certain extent.

The invention discloses an intelligent network attack detection method based on traffic analysis and electronic equipment. The method comprises the following steps: acquiring traffic data in a network; a pre-trained automatic encoder AE is constructed, the automatic encoder AE comprises an encoder module, a potential space and a decoder module, the encoder module adopts two layers of long short-term memory networks, and a Dropout layer is inserted between the two layers of long short-term memory networks and is used for receiving input traffic data and performing data compression and feature extraction to obtain key traffic features; and the potential space adopts a bidirectional gating circulation unit to carry out key traffic feature classification, and outputs a detection result indicating whether the traffic data has an abnormal traffic type or not through a decoder module. According to the method, the important traffic characteristics in the traffic can be fully extracted, and the problems of low detection rate and high false alarm rate caused by solving the problem of data imbalance by using a sampling technology are avoided while data dimension reduction is completed.

The application discloses a two-wheeled vehicle fast and slow charging compatible charging method and device, equipment and medium. The battery code information in the battery is read and judged, so that it can be quickly determined whether the battery supports fast charging. Then, when the fast charging is not supported, the peak charging current information of the battery is used to quickly determine the charging current to complete the slow charging. In the case of reading the battery code information, the charging current is quickly determined according to the battery code information, and the charging is started. The embodiment of the application can realize automatic selection of the charging mode, and can improve the charging experience of the user to a certain extent.

This invention relates to the field of liquid crystal display technology, and more particularly to an intelligent driving method and system for liquid crystal displays. The method includes the following steps: recording the current decay waveform of the source driver charging the pixel capacitor during pixel charging; calculating the charging time constant based on the current decay waveform; calculating the current pixel capacitance value using the charging time constant and the transistor on-resistance; converting the current pixel capacitance value into an orientation angle corresponding to the pixel orientation state; comparing the current orientation angle with the target orientation angle corresponding to the pre-acquired target grayscale, and calculating the orientation angle deviation; and using a driving sequence containing multiple voltage pulses based on the orientation angle deviation. This invention achieves closed-loop precise driving based on pixel state feedback by deriving the pixel capacitance from the current decay and converting it into the pixel orientation state, overcoming the problem of long-term open-loop blind driving in liquid crystal displays.

This invention discloses an automated scanning, acquisition, and processing device for in-situ core logging data, relating to the field of oil and gas geological exploration technology. It includes: a sampling and analysis platform; a support device horizontally fixed to the sampling and analysis platform, on which a core is placed; a positioning and analysis device fixed to the sampling and analysis platform, located behind the support device and in contact with the top of the core; a protective cover fixedly connected to the rear wall of the sampling and analysis platform, located above the core, with a through-hole in the middle and multiple white light tube groups on the inner walls of the front and rear sides; and an equidistant sampling device fixed to the top of the protective cover, corresponding to the positioning and analysis device. This invention integrates sampling, scanning, and analysis, achieving efficient acquisition and accurate processing of core logging data, and improving the reliability of geological modeling.

The invention discloses a seismic data interpretation method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring an original seismic data volume, and performing coherent slicing processing on the original seismic data volume to obtain coherent body slices of a target layer; performing azimuth search on the coherent body slice of the target layer to obtain at least one target coherent azimuth; obtaining a target fracture orientation from the target coherent orientation, and rotating the target fracture orientation to obtain a sensitive orientation; and performing seismic data interpretation on the seismic data volume of the sensitive orientation to obtain a seismic interpretation result of the sensitive orientation. According to the technical scheme, automatic selection of the sensitive orientation and seismic data interpretation of the sensitive orientation are realized, and compared with a seismic interpretation result of an original orientation, the seismic interpretation result of the sensitive orientation can effectively improve the construction and fracture identification precision.

The application discloses a video synthetic aperture radar imaging and tracking integrated method, and mainly solves the problems of low imaging automation degree and large calculation amount in the prior art.The implementation scheme is as follows: reading SAR echo data containing N segments of synthetic apertures and setting an imaging grid; projecting and imaging the first two segments of echo data; preliminarily detecting on the image to obtain a target initial state set; performing inter-frame state transition on the targets in the initial state set to obtain a total target state set; setting an imaging region of interest according to the total target state set; performing value function accumulation and backtracking function updating on the second frame of image; performing target value function accumulation and backtracking function updating on the images of the remaining frame numbers according to the region of interest; and performing target track backtracking.The application reduces the calculation amount of video synthetic aperture radar imaging, improves the overall efficiency of video synthetic aperture radar target detection, and can be used for detecting ground moving targets by various airborne radars.

The invention provides a visual language model zero sample classification method based on Lasso regularization dynamic integration. The visual language model zero sample classification method specifically comprises the following steps: S1, constructing a model pool comprising a plurality of pre-trained visual encoders; step S2, in a training stage, adaptively screening out a model subset which contributes significantly to a current task from the model pool by using the sparse characteristic of Lasso regularization, and learning the weight of the model subset; s3, introducing a dynamic regularization coefficient lambda adjustment mechanism based on verification loss to balance the complexity and generalization ability of the model; and S4, in a reasoning stage, performing weighted fusion on the prediction result of the selected model by using the sparse weight obtained by training to obtain a final classification result. According to the method, the accuracy and robustness of the visual language model in the zero sample classification task can be effectively improved.

The invention discloses a fast and slow charging compatible charging method, device and equipment for a two-wheeled vehicle and a medium, whether a battery supports fast charging or not can be quickly confirmed by reading and judging battery code information set in the battery, and then the battery can be quickly charged when the battery does not support fast charging. According to the method, the charging current is quickly confirmed to finish slow charging by using the peak charging current information of the battery, and the charging current is quickly confirmed according to the battery coding information under the condition that the battery coding information is read, and charging is started. According to the embodiment of the invention, automatic selection of the charging mode can be realized, and the charging experience of a user can be improved to a certain extent.

The invention discloses a model training and information query method and device, equipment, a medium and a product, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining a sample feature vector corresponding to a sample inquiry statement, and inputting the sample feature vector into a to-be-trained model; determining the prediction correlation between the sample feature vector and each candidate knowledge base by using the to-be-trained model, and training the to-be-trained model according to the prediction correlation and the standard correlation between the sample feature vector and each candidate knowledge base to generate a knowledge base prediction model; wherein the knowledge base prediction model is used for predicting a related target knowledge base according to the current inquiry statement of the user, and the target knowledge base is used for carrying out information query according to the current inquiry statement. According to the invention, the effect of automatically selecting the related knowledge base according to the inquiry statement can be realized, the time required for information inquiry is greatly saved, and the user experience is ensured.