{"title":"莼菜漂移扩散的多模块双向反馈法","authors":"Hui Sheng, Jianmeng Li, Qimao Wang, Bin Zou, Lijian Shi, Mingming Xu, Shanwei Liu, Jianhua Wan, Zhe Zeng, Yanlong Chen","doi":"10.1007/s13131-023-2165-y","DOIUrl":null,"url":null,"abstract":"<p>The outbreak of <i>Ulva</i> in the Yellow Sea has seriously affected marine ecology and economic activities. Therefore, effective prediction of the distribution of <i>Ulva</i> is of great significance for disaster prevention and reduction. However, the prediction method of <i>Ulva</i> is mainly based on numerical simulation. There are two problems with these methods. First is that the initial distribution of <i>Ulva</i> is simulated using independent pixel-level particles. Besides, the influence of <i>Ulva</i> growth and diffusion on the drift is not considered. Therefore, this paper proposes a multi-module with a two-way feedback method (MTF) to solve the above problems. The main contributions of our approach are summarized as follows. First, the initialization module, the generation and elimination module, and the drive module are composed in our way. Second, we proposed an initialization method using rectangle objects to simulate the <i>Ulva</i> distribution extracted from remote sensing images. Thirdly, the drift and diffusion mechanism of the <i>Ulva</i> is considered to realize the two-way feedback between the generation and elimination module and the drive module. The results of our experiments show that the MTF performs better than the traditional method in predicting the drift and diffusion of <i>Ulva</i>. The code is already publicly available at https://github.com/UPCGIT/A-multi-module-with-a-two-way-feedback-method-for-Ulva-drift-diffusion.</p>","PeriodicalId":6922,"journal":{"name":"Acta Oceanologica Sinica","volume":"44 1","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A multi-module with a two-way feedback method for Ulva drift-diffusion\",\"authors\":\"Hui Sheng, Jianmeng Li, Qimao Wang, Bin Zou, Lijian Shi, Mingming Xu, Shanwei Liu, Jianhua Wan, Zhe Zeng, Yanlong Chen\",\"doi\":\"10.1007/s13131-023-2165-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The outbreak of <i>Ulva</i> in the Yellow Sea has seriously affected marine ecology and economic activities. Therefore, effective prediction of the distribution of <i>Ulva</i> is of great significance for disaster prevention and reduction. However, the prediction method of <i>Ulva</i> is mainly based on numerical simulation. There are two problems with these methods. First is that the initial distribution of <i>Ulva</i> is simulated using independent pixel-level particles. Besides, the influence of <i>Ulva</i> growth and diffusion on the drift is not considered. Therefore, this paper proposes a multi-module with a two-way feedback method (MTF) to solve the above problems. The main contributions of our approach are summarized as follows. First, the initialization module, the generation and elimination module, and the drive module are composed in our way. Second, we proposed an initialization method using rectangle objects to simulate the <i>Ulva</i> distribution extracted from remote sensing images. Thirdly, the drift and diffusion mechanism of the <i>Ulva</i> is considered to realize the two-way feedback between the generation and elimination module and the drive module. The results of our experiments show that the MTF performs better than the traditional method in predicting the drift and diffusion of <i>Ulva</i>. The code is already publicly available at https://github.com/UPCGIT/A-multi-module-with-a-two-way-feedback-method-for-Ulva-drift-diffusion.</p>\",\"PeriodicalId\":6922,\"journal\":{\"name\":\"Acta Oceanologica Sinica\",\"volume\":\"44 1\",\"pages\":\"\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2024-03-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta Oceanologica Sinica\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1007/s13131-023-2165-y\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"OCEANOGRAPHY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Oceanologica Sinica","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s13131-023-2165-y","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"OCEANOGRAPHY","Score":null,"Total":0}
A multi-module with a two-way feedback method for Ulva drift-diffusion
The outbreak of Ulva in the Yellow Sea has seriously affected marine ecology and economic activities. Therefore, effective prediction of the distribution of Ulva is of great significance for disaster prevention and reduction. However, the prediction method of Ulva is mainly based on numerical simulation. There are two problems with these methods. First is that the initial distribution of Ulva is simulated using independent pixel-level particles. Besides, the influence of Ulva growth and diffusion on the drift is not considered. Therefore, this paper proposes a multi-module with a two-way feedback method (MTF) to solve the above problems. The main contributions of our approach are summarized as follows. First, the initialization module, the generation and elimination module, and the drive module are composed in our way. Second, we proposed an initialization method using rectangle objects to simulate the Ulva distribution extracted from remote sensing images. Thirdly, the drift and diffusion mechanism of the Ulva is considered to realize the two-way feedback between the generation and elimination module and the drive module. The results of our experiments show that the MTF performs better than the traditional method in predicting the drift and diffusion of Ulva. The code is already publicly available at https://github.com/UPCGIT/A-multi-module-with-a-two-way-feedback-method-for-Ulva-drift-diffusion.
期刊介绍:
Founded in 1982, Acta Oceanologica Sinica is the official bi-monthly journal of the Chinese Society of Oceanography. It seeks to provide a forum for research papers in the field of oceanography from all over the world. In working to advance scholarly communication it has made the fast publication of high-quality research papers within this field its primary goal.
The journal encourages submissions from all branches of oceanography, including marine physics, marine chemistry, marine geology, marine biology, marine hydrology, marine meteorology, ocean engineering, marine remote sensing and marine environment sciences.
It publishes original research papers, review articles as well as research notes covering the whole spectrum of oceanography. Special issues emanating from related conferences and meetings are also considered. All papers are subject to peer review and are published online at SpringerLink.