Time Series Analysis and Optimization of the Prediction Model of Agricultural Insurance Loss Ratio
Author
Abstract
Suggested Citation
DOI: 10.22004/ag.econ.347961
Download full text from publisher
References listed on IDEAS
- Richman, Ronald, 2021. "AI in actuarial science – a review of recent advances – part 2," Annals of Actuarial Science, Cambridge University Press, vol. 15(2), pages 230-258, July.
- Zhong, Ling & Nie, Jiajia & Yue, Xiaohang & Jin, Minyue, 2023. "Optimal design of agricultural insurance subsidies under the risk of extreme weather," International Journal of Production Economics, Elsevier, vol. 263(C).
- Ania Cravero & Sebastián Pardo & Patricio Galeas & Julio López Fenner & Mónica Caniupán, 2022. "Data Type and Data Sources for Agricultural Big Data and Machine Learning," Sustainability, MDPI, vol. 14(23), pages 1-37, December.
- Richman, Ronald, 2021. "AI in actuarial science – a review of recent advances – part 1," Annals of Actuarial Science, Cambridge University Press, vol. 15(2), pages 207-229, July.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Aleksandar Arandjelovi'c & Julia Eisenberg, 2024. "Reinsurance with neural networks," Papers 2408.06168, arXiv.org.
- Jamotton, Charlotte & Hainaut, Donatien, 2024. "Latent Dirichlet Allocation for structured insurance data," LIDAM Discussion Papers ISBA 2024008, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Katrien Antonio & Christophe Dutang & Andreas Tsanakas, 2021. "Editorial," Post-Print hal-04748464, HAL.
- Yu Wang, Muhammad Asraf bin Abdullah, Josephine Yau Tan Hwang, 2024. "Time Series Analysis and Optimization of the Prediction Model of Agricultural Insurance Loss Ratio," Research on World Agricultural Economy, Nan Yang Academy of Sciences Pte Ltd (NASS), vol. 5(4), November.
- Francesca Perla & Salvatore Scognamiglio, 2023. "Locally-coherent multi-population mortality modelling via neural networks," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 46(1), pages 157-176, June.
- Hung-Tsung Hsiao & Chou-Wen Wang & I.-Chien Liu & Ko-Lun Kung, 2024. "Mortality improvement neural-network models with autoregressive effects," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 49(2), pages 363-383, April.
- Corsaro, Stefania & Marino, Zelda & Scognamiglio, Salvatore, 2024. "Quantile mortality modelling of multiple populations via neural networks," Insurance: Mathematics and Economics, Elsevier, vol. 116(C), pages 114-133.
- Yang Qiao & Chou-Wen Wang & Wenjun Zhu, 2024. "Machine learning in long-term mortality forecasting," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 49(2), pages 340-362, April.
- Benjamin Avanzi & Greg Taylor & Melantha Wang & Bernard Wong, 2023. "Machine Learning with High-Cardinality Categorical Features in Actuarial Applications," Papers 2301.12710, arXiv.org.
- Mingyu Hu & Fujin Yi & Hong Zhou & Feier Yan, 2024. "The More the Better? Reconsidering the Welfare Effect of Crop Insurance Premium Subsidy," Agriculture, MDPI, vol. 14(11), pages 1-19, November.
- Shuangxi Miao & Shuyu Wang & Chunyan Huang & Xiaohong Xia & Lingling Sang & Jianxi Huang & Han Liu & Zheng Zhang & Junxiao Zhang & Xu Huang & Fei Gao, 2023. "A Big Data Grided Organization and Management Method for Cropland Quality Evaluation," Land, MDPI, vol. 12(10), pages 1-20, October.
- Meijun Zhu & Kengcheng Zheng & Baoliu Liu & Fang Jin, 2024. "Can Agricultural Support and Protection Subsidy Policies Promote High-Quality Development of Grain Industry? A Case Study of China," Agriculture, MDPI, vol. 14(10), pages 1-22, September.
- Fabián Santos & Nicole Acosta, 2023. "An Approach Based on Web Scraping and Denoising Encoders to Curate Food Security Datasets," Agriculture, MDPI, vol. 13(5), pages 1-19, May.
More about this item
Keywords
Agricultural Finance; Demand and Price Analysis;Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:reowae:347961. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: http://www.nassg.org/ .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.