7results about How to "Reduce memory" patented technology

The application discloses a kind of SF6 circuit breaker fault prediction method and system considering the effect of breaking arc, collect breaking arc data and SF6 gas decomposition product content after breaking, in the process of operation and after fault, establish circuit breaker historical breaking data set, build cumulative arc energy-SF6 gas decomposition product content relationship model, obtain the SF6 gas decomposition product content corresponding to different breaking times, breaking current;Establish SF6 gas decomposition product content historical operation data set;Build SF6 gas decomposition product content prediction model based on LSTM, obtain the prediction result of SF6 gas decomposition product content;Establish SF6 gas decomposition product content historical fault data set, build SF6 circuit breaker fault diagnosis model;The prediction result of SF6 gas decomposition product is as the input of SF6 circuit breaker fault diagnosis model, obtains fault diagnosis result, realizes the fault prediction of SF6 circuit breaker.

The application provides a lead compound discovery method, device, equipment and storage medium, comprising: obtaining a meta-learning model with initial parameters; obtaining activity data of a target target point and a plurality of historical target points, dividing the activity data of the first target point to obtain a training set and an original test set corresponding to the first target point, in the meta-learning method, for any one of the plurality of original test samples, selecting a training sample corresponding to the original test sample from the plurality of training samples, and mixing the original test sample and the training sample corresponding to the original test sample to obtain a mixed processing result; optimizing the initial parameters according to the mixed processing result of all first target points to obtain first parameters; and determining a lead compound for the target target point according to the first parameters, the meta-learning model and the activity data of the target target point, so that the determined lead compound has higher accuracy.

The application relates to the technical field of file storage management, and discloses a file storage management system of a cloud storage system, which comprises an access adaptation module, a metadata module, a slice version module, a deterministic mapping module, a container management module and a persistence control module. The deterministic mapping module performs stateless calculation based on a file identifier and a data block index number to generate a target container identifier and a virtual slot number. The container management module constructs a buffer container in the memory, ignores the discreteness of the virtual slot, and writes data blocks into a data storage area in a compact appending mode. The persistence control module drives effective data to be written into a disk according to a comparison result of a global version identifier and a historical version. The application eliminates the metadata bottleneck through deterministic routing, converts random I / O into sequential I / O through memory compact reorganization, and solves concurrent conflicts based on a lock-free mechanism, thereby significantly improving the throughput and expansibility of the storage system.

This application proposes a speech decoding processing method, apparatus, electronic device, and storage medium. When a blank decoding candidate exists among all decoding candidates corresponding to the current audio acoustic output of an audio recognition system, the method determines whether the current audio acoustic output is a blank output. If it cannot be determined that the current audio acoustic output is blank, this application does not employ a language model where each node has a self-jumping arc for self-jumping. Instead, it creates a new activation arc for self-jumping on the active node with blank decoding candidates in a pre-defined language decoding network, and adds blank decoding candidate information as a label to the activation arc. Based on the activation arc label, the path label of the active node is determined, thereby reducing the memory usage of the self-jumping arc portion. Based on this, this application reduces the memory and computing power requirements of speech recognition, mitigating the limitations of speech recognition technology in practical applications.

The invention provides a multi-table connection processing method of a database and a related product. The multi-table connection processing method comprises the following steps: acquiring a plurality of tables to be connected; constructing a heap sorting structure; ranking the row data of the plurality of tables to be connected by using a heap ranking structure, and respectively forming candidate result subsets by using the row data with the same connection key value; and determining the candidate result subsets meeting a multi-table connection condition to obtain a multi-table connection result. According to the multi-table connection processing method, the memory and I / O consumption is reduced, the execution efficiency of large-scale data and complex query is remarkably improved, the optimization requirement of the connection sequence is eliminated, the query planning time is remarkably shortened, and the CPU and memory overhead is reduced.

The invention discloses a three-dimensional geologic structure modeling method and system based on SH-LDM and a medium, and relates to the technical field of deep learning and geologic modeling crossing, and the three-dimensional geologic structure modeling method based on SH-LDM mainly comprises the steps: carrying out the preprocessing of original data, and obtaining a training data set and a test data set; training the multi-branch self-encoding network by using the first-stage loss function, and training the multi-condition diffusion network by using the second-stage loss function; and according to soft data and hard data of a real scene, utilizing the trained multi-branch self-encoding network and the multi-condition diffusion network to obtain a three-dimensional geologic structure generation image. By implementing the SH-LDM-based three-dimensional geologic structure modeling method and system and the medium provided by the invention, high-precision and efficient modeling of a complex non-stationary underground structure can be realized.

The invention relates to the technical field of scene rendering, in particular to a scene rendering method and device, electronic equipment and a target vehicle. Building a target scene model corresponding to the target vehicle; based on a vehicle machine screen corresponding to the target vehicle, constructing a target texture image corresponding to the target scene model and a target flow velocity image corresponding to the target texture image; and based on the target texture image and the target flow velocity image, rendering the color and transparency corresponding to each fragment in the target scene model to obtain a rendered background model. The overhead of the internal memory and the video memory of the in-vehicle infotainment device is greatly reduced, reliable material support is provided for subsequent real-time dynamic flow calculation, and the visual effect and the in-vehicle infotainment device operation efficiency are both considered. At least 120 frames of consecutive sequence frame materials are not required. And meanwhile, the lightweight computational logic conforms to the performance limitation of the vehicle GPU, and the dynamic visual effect and the rendering frame rate stability are both considered.