{"title":"基于混沌博弈算法的射频功率晶体管超参数优化 GPR 模型","authors":"Zhiwei Gao, Tao Zhou, Giovanni Crupi, Jialin Cai","doi":"10.1002/jnm.3259","DOIUrl":null,"url":null,"abstract":"<p>In this paper, a new frequency domain behavior model for radio frequency (RF) power transistors based on a hyper-parameter optimized Gaussian process regression (GPR) method is presented. The chaos game optimization (CGO) algorithm is used to optimize GPR hyperparameters, resulting in the CGO-GPR model. The basic theory as well as the details of the modeling process are presented. Validation of the model is conducted using a 10-watt GaN power transistor. Compared to the standard GPR model, the proposed model achieved a significant improvement. Furthermore, the comparison with the particle swarm optimization (PSO) based GPR model (PSO-GPR) showed that the proposed model allows achieving superior performance, thereby confirming the effectiveness of the developed modeling technique.</p>","PeriodicalId":50300,"journal":{"name":"International Journal of Numerical Modelling-Electronic Networks Devices and Fields","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Hyper-parameter optimized GPR model based on chaos game algorithm for RF power transistors\",\"authors\":\"Zhiwei Gao, Tao Zhou, Giovanni Crupi, Jialin Cai\",\"doi\":\"10.1002/jnm.3259\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In this paper, a new frequency domain behavior model for radio frequency (RF) power transistors based on a hyper-parameter optimized Gaussian process regression (GPR) method is presented. The chaos game optimization (CGO) algorithm is used to optimize GPR hyperparameters, resulting in the CGO-GPR model. The basic theory as well as the details of the modeling process are presented. Validation of the model is conducted using a 10-watt GaN power transistor. Compared to the standard GPR model, the proposed model achieved a significant improvement. Furthermore, the comparison with the particle swarm optimization (PSO) based GPR model (PSO-GPR) showed that the proposed model allows achieving superior performance, thereby confirming the effectiveness of the developed modeling technique.</p>\",\"PeriodicalId\":50300,\"journal\":{\"name\":\"International Journal of Numerical Modelling-Electronic Networks Devices and Fields\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2024-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Numerical Modelling-Electronic Networks Devices and Fields\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/jnm.3259\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Numerical Modelling-Electronic Networks Devices and Fields","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/jnm.3259","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Hyper-parameter optimized GPR model based on chaos game algorithm for RF power transistors
In this paper, a new frequency domain behavior model for radio frequency (RF) power transistors based on a hyper-parameter optimized Gaussian process regression (GPR) method is presented. The chaos game optimization (CGO) algorithm is used to optimize GPR hyperparameters, resulting in the CGO-GPR model. The basic theory as well as the details of the modeling process are presented. Validation of the model is conducted using a 10-watt GaN power transistor. Compared to the standard GPR model, the proposed model achieved a significant improvement. Furthermore, the comparison with the particle swarm optimization (PSO) based GPR model (PSO-GPR) showed that the proposed model allows achieving superior performance, thereby confirming the effectiveness of the developed modeling technique.
期刊介绍：
Prediction through modelling forms the basis of engineering design. The computational power at the fingertips of the professional engineer is increasing enormously and techniques for computer simulation are changing rapidly. Engineers need models which relate to their design area and which are adaptable to new design concepts. They also need efficient and friendly ways of presenting, viewing and transmitting the data associated with their models.
The International Journal of Numerical Modelling: Electronic Networks, Devices and Fields provides a communication vehicle for numerical modelling methods and data preparation methods associated with electrical and electronic circuits and fields. It concentrates on numerical modelling rather than abstract numerical mathematics.
Contributions on numerical modelling will cover the entire subject of electrical and electronic engineering. They will range from electrical distribution networks to integrated circuits on VLSI design, and from static electric and magnetic fields through microwaves to optical design. They will also include the use of electrical networks as a modelling medium.
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