Method for simulating automatic landing of aircraft based on DQN and related equipment
An automatic landing and aircraft technology, applied in the field of deep learning, can solve problems such as inability to perform effectively, unable to discover structure/knowledge, unable to achieve interactive scene reward training goals, etc., to achieve the effect of improving efficiency
Pending Publication Date: 2019-07-23
PING AN TECH (SHENZHEN) CO LTD
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Problems solved by technology
When simulating the interactive scene of the aircraft landing, the use of supervised learning cannot be carried out effectively, and the general unsupervised learning cannot discover the hidden structure / knowledge from a bunch of unlabeled samples, and cannot reach the interactive scene To obtain the maximum "reward" in order to achieve the purpose of the training target
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[0051] Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various forms, and should not be construed as being limited to the examples set forth herein; on the contrary, the provision of these embodiments makes the present disclosure more comprehensive and complete, and fully conveys the concept of the example embodiments To those skilled in the art. The described features, structures or characteristics can be combined in one or more embodiments in any suitable way. In the following description, many specific details are provided to give a sufficient understanding of the embodiments of the present disclosure. However, those skilled in the art will realize that the technical solutions of the present disclosure can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. can be used. In other cases, the known technical solution...
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The invention discloses a method for simulating automatic landing of an aircraft based on DQN and related equipment, and relates to the field of deep learning. The method comprises the following steps: acquiring the current state st of a simulated aircraft for each time slice t; determining an action at to be performed by the simulated aircraft in a current state st based on the DQN; controlling the simulated aircraft to execute the action at, and determining the state st+1 after the simulated aircraft executes the action at; and determining whether the simulated aircraft lands successfully ornot based on the matching result of the state st+1 and a preset target state. The method for simulating automatic landing of the aircraft based on DQN and related equipment improves the efficiency ofsimulating automatic landing of the aircraft.
Description
Technical field [0001] The present invention relates to the field of deep learning, in particular to a method and related equipment for simulating the automatic landing of an aircraft based on DQN. Background technique [0002] In the automatic simulation landing process of an aircraft, a machine learning model is generally used to perform the simulation process. When simulating the interactive scene of the aircraft landing, the use of supervised learning cannot be effectively carried out, and general unsupervised learning cannot find hidden structure / knowledge from a bunch of unlabeled samples, and cannot reach the interactive scene. In order to achieve the goal of training, the greatest "reward" must be obtained. Summary of the invention [0003] Based on this, in order to solve the technical problem of how to simulate aircraft automatic landing more efficiently in related technologies, the present invention provides a method and related equipment for simulating aircraft automa...
Claims
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CPCG05D1/101Y02T90/00
Inventor 于凤英王健宗
Owner PING AN TECH (SHENZHEN) CO LTD