Unlock instant, AI-driven research and patent intelligence for your innovation.
Multi-objective optimization method and device, equipment and medium
What is Al technical title?
Al technical title is built by PatSnap Al team. It summarizes the technical point description of the patent document.
A multi-objective optimization and objective technology, applied in multi-objective optimization, neural learning methods, design optimization/simulation, etc., can solve problems such as optimization problems that do not consider the multi-objective of the hybrid control system, and achieve reasonable control effects
Pending Publication Date: 2022-04-29
SOUTH UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA
View PDF0 Cites 0 Cited by
Summary
Abstract
Description
Claims
Application Information
AI Technical Summary
This helps you quickly interpret patents by identifying the three key elements:
Problems solved by technology
Method used
Benefits of technology
Problems solved by technology
Existing methods often only consider the design of the hybrid control system with fuel consumption as a single objective, and do not consider the multi-objective optimization problem of the hybrid control system
Method used
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more
Image
Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
Click on the blue label to locate the original text in one second.
Reading with bidirectional positioning of images and text.
Smart Image
Examples
Experimental program
Comparison scheme
Effect test
example 1
[0096] Example 1, specifically, the design of the power control system of a hybrid electric vehicle usually needs to consider some parameters and rules. Specifically, the parameter definitions are shown in Table 1.
[0097] Table 1
[0098]
[0099] The specific rules of hybrid power control are as follows:
[0104] Rule 5: If the internal combustion engine is on and the speed is between V1 and V2, do action 2.
...
example 2
[0133] Example 2, refer to Figure 7 , the method in Example 2 includes:
[0134] Population initialization, specifically, random initialization generates 100 individuals satisfying the constraints and the upper and lower bounds, that is, the initial solution set.
[0135] Judging whether the number of iterations of the current population cycle satisfies the preset condition: specifically, the preset condition is that the number of iterations of the current population cycle is 1, 5, 10, 15 until the end of the cycle, and the total number of iterations of the population cycle can be 100.
[0136] When the preset conditions are not met, the initial solution set is crossed and mutated to obtain the initial offspring and the target preference solution set is updated according to the initial offspring.
[0137] When the preset conditions are met, the offspring is generated based on the generative confrontation network, and the preference offspring is obtained, and the target prefe...
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More
PUM
Login to View More
Abstract
The invention discloses a multi-objective optimization method, apparatus and device, and a medium. The method comprises the steps of obtaining a population and a preset optimization objective; initializing the population according to a preset optimization target to obtain an initial solution set; obtaining a preset reference coefficient, and performing preference classification on the initial solution set according to the preset reference coefficient to obtain a first preference solution set and a first non-preference solution set; training a preset generative adversarial network according to the first preference solution set and the first non-preference solution set to obtain a first preference filial generation; and performing environment selection according to the initial solution set and the first preference filial generation to obtain a target preference solution set. According to the multi-objective optimization method obtained by introducing expert knowledge and the generative adversarial network, the problem of multi-objective optimization is effectively solved. Particularly, in the face of the multi-objective optimization problem in the hybridpower controlsystem, the multi-objective optimization is effectively realized, so that the control of the hybridpower controlsystem is more reasonable.
Description
technical field [0001] The present invention relates to the field of computer technology, in particular to a multi-objective optimization method, device, equipment and medium. Background technique [0002] In industrial production and life, many problems are composed of multiple goals that conflict and influence each other. People often encounter optimization problems that make multiple objectives as optimal as possible in a given area at the same time, that is, multi-objective optimization problems. In the design of hybridpower controlsystem, the designer's main goal is to reduce fuel consumption. However, in addition to fuel consumption, factors such as driving experience, noise, vibration and harshness also need to be considered. Existing methods often only consider the design of the hybrid control system with fuel consumption as a single objective, and do not consider the multi-objective optimization problem of the hybrid control system. Contents of the invention ...
Claims
the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More
Application Information
Patent Timeline
Application Date:The date an application was filed.
Publication Date:The date a patent or application was officially published.
First Publication Date:The earliest publication date of a patent with the same application number.
Issue Date:Publication date of the patent grant document.
PCT Entry Date:The Entry date of PCT National Phase.
Estimated Expiry Date:The statutory expiry date of a patent right according to the Patent Law, and it is the longest term of protection that the patent right can achieve without the termination of the patent right due to other reasons(Term extension factor has been taken into account ).
Invalid Date:Actual expiry date is based on effective date or publication date of legal transaction data of invalid patent.
Login to View More 
Login to View More