Airborne equipment data storage method and system based on machine learning
A data storage system and machine learning technology, applied in machine learning, neural learning methods, electrical and digital data processing, etc., can solve the problems of long file management time, affecting high-speed storage, and data writing time that cannot be ignored. The effect of file management time
Pending Publication Date: 2021-11-02
湖南博匠信息科技有限公司
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Problems solved by technology
However, solid-state storage data systems based on such media generally have a difficult problem that affects high-speed storage: file management takes too long
The time overhead of these file management operations is not negligible relative to the data write time, and usually significantly reduces the data write rate
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[0048] The present invention will be described in detail below in conjunction with the accompanying drawings and embodiments. The following experimental examples and examples are used to further illustrate but not limit the present invention.
[0049] see figure 2 , the present invention provides a kind of airborne equipment data storage method based on machine learning, comprises the following steps:
[0050] Step S10, data preprocessing, processing the data to be stored and hardware resources to generate a label data group, the label data group includes a plurality of components, and each component is a vector signal representing a kind of data;
[0051] Step S20, storing data processing, including an input layer, multiple hidden layers and an output layer;
[0052] The input layer, the signal of the input layer is the label data group generated after the preprocessing in step S10, denoted as X;
[0053] Preferably, in this embodiment, the tag data group includes nine ty...
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The invention provides an airborne equipment data storage method based on machine learning, and the method comprises the following steps: S10, data preprocessing, wherein to-be-stored data and hardware resources are processed to generate a tag data group; S20, storage data processing, wherein an input layer, a plurality of hidden layers and an output layer are included, the plurality of hidden layers are used for extracting statistical characteristics in data through supervised data layer-by-layer training and nonlinear transformation, and establishing a mapping relation from a bottom-layer signal to a high-layer data storage method, and the output layer uses the output result of the last hidden layer as the input of the model of the output layer, and finally outputs data Y; and S30, data storage, wherein airborne equipment data storage is executed according to a method within Y. Compared with the prior art, the airborne equipment data storage method based on machine learning provided by the invention can realize efficient storage of airborne equipment data. The invention further provides an airborne equipment data storage system based on machine learning.
Description
technical field [0001] The present invention relates to the technical fields of artificial intelligence and data storage, in particular to a method and system for storing airborne equipment data based on machine learning. Background technique [0002] Airborne equipment has a high data rate, which can reach hundreds of Mbps or even Gbps in many applications. Such a high data rate has far exceeded the current wireless data transmission rate between air and ground, so airborne equipment requires an onboard data storage system in many applications. [0003] NAND Flash has many excellent characteristics such as small size, light weight, low power consumption, high storage density, fast data access speed, and good shock resistance. It is widely used in data storage fields with high performance requirements such as aerospace. However, solid-state storage data systems based on such media generally have a difficult problem that affects high-speed storage: file management takes too ...
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IPC IPC(8): G06F16/172G06K9/62G06N3/08G06N20/00
CPCG06F16/172G06N3/08G06N20/00G06F18/24
Inventor 田海山洪琳琅
Owner 湖南博匠信息科技有限公司