Deep learning simulation consolidation method based on cloud computing

Abstract

The invention discloses a deep learning simulation consolidation method based on cloud computing, and belongs the deep learning field. The deep learning simulation consolidation method based on cloudcomputing Includes that an error model is set through an error between a data set similar to a simulation environment and ideal data; the precision and the operation sensitivity of the actual operation of the deep learning object can be improved; in the actual fine adjustment correction process, a difference node and a mutual capacitance correction ring outside the difference node are arranged; the determination range of the next operation data point can be continuously reduced; the precision of the next operation data point is effectively improved; meanwhile, the judgment difficulty of the next operation data point can also be reduced; the method improves the overall operation efficiency of the deep learning object, enlarges the depth of the simulation environment and reduces the difference between the simulation environment and the actual operation environment through the difference between the ideal data and the data set which is obviously different from the simulation environment,and improves the comprehensiveness of deep learning of the deep learning object.

Description

technical field [0001] The present invention relates to the field of deep learning, and more specifically, to a method for simulating and consolidating deep learning based on cloud computing. Background technique [0002] Deep learning (DL, Deep Learning) is a new research direction in the field of machine learning (ML, Machine Learning). It is introduced into machine learning to make it closer to the original goal-artificial intelligence (AI, Artificial Intelligence). [0003] Deep learning is to learn the internal laws and representation levels of sample data. The information obtained during the learning process is of great help to the interpretation of data such as text, images and sounds. Its ultimate goal is to enable machines to have the ability to analyze and learn like humans, and to be able to recognize data such as text, images, and sounds. Deep learning is a complex machine learning algorithm that has achieved results in speech and image recognition that far exce...

AI Technical Summary

Problems solved by technology

[0005] The existing deep learning simulation is only to obtain relevant data in a simulated environment, and use the relevant data as the basis for the actual operation of the deep learning object in the later stage. However, the data obtained by deep learning is obtained under the ideal environment of the simulation, and the data sheet Ideally, when the deep learning object is operated out of the simulated environment, there will be some situations that do not appear in the simulated environment or are similar but different from the simulated environment, resulting in a certain gap between the final actual operating data and the ideal data. The error affects the subsequent actual operation efficiency, sensitivity and accuracy of deep learning objects

Images