Quotation determination method and device, equipment and storage medium
A technology for determining methods and algorithms, applied in the field of electric power, can solve problems such as unsuitable bidding strategies, poor practicability, roughness, etc., and achieve the effect of maximizing market revenue
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Embodiment 1
[0027] figure 1 It is a flow chart of a quotation determination method provided in Embodiment 1 of the present invention. This embodiment is applicable to the situation of performing quotation simulation on target resources. The method can be executed by a quotation determination device, which can use software and / or implemented in a hardware manner, the apparatus may be configured in a terminal device. Specifically include the following steps:
[0028] S110. Obtain the measured state parameter and the measured resource parameter of the target resource.
[0029] Wherein, for example, the target resource may be a hardware device, such as an ultrasonic device, or an energy material, such as steel, or a food product, such as milk.
[0030] The reinforcement learning algorithm consists of five parts, which are agent, state parameter, action parameter, reward parameter and environment. The agent will make corresponding actions according to the input state parameters, and the en...
Embodiment 2
[0047] figure 2 It is a flow chart of a quotation determination method provided in Embodiment 2 of the present invention, and the technical solution of this embodiment is further refined on the basis of the foregoing embodiments. Optionally, the target quotation model is trained based on a deep reinforcement learning algorithm, including: obtaining sample state parameters and sample resource parameters of the target resource, and inputting the sample state parameters and sample resource parameters into the initial quotation model; wherein , the sample resource parameter includes at least one sample quotation coefficient; determine the sample data according to the output result of the initial quotation model, and save the sample data in the experience playback pool; wherein, the sample data includes the initial quotation model output the predicted revenue; according to the preset training frequency, based on the sample data stored in the experience playback pool, determine the c...
Embodiment 3
[0075] image 3 It is a flow chart of a quotation determination method provided in Embodiment 3 of the present invention, and the technical solution of this embodiment is further refined on the basis of the foregoing embodiments. Optionally, determine the next sample state parameter according to the current sample quotation coefficient provided by different resource objects based on the current sample state parameter; wherein, the resource object includes a resource object corresponding to the initial quotation model; according to the following This state parameter determines the standard return corresponding to the current sample state parameter.
[0076] The specific implementation steps of this embodiment include:
[0077] S310. Obtain sample state parameters and sample resource parameters of the target resource, and input the initial sample state parameters and sample resource parameters into the initial quotation model.
[0078] S320. Determine sample data according to ...
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