Research on insurance model based on different mathematical models and algorithms
DOI:
https://doi.org/10.54097/pzvwz117Keywords:
ARIMA, AGNES, Entropy Weight Method, Risk Assessment.Abstract
This article presents a risk assessment and prediction model for specific areas using the ARIMA model, entropy weight method, and AGNES algorithm. The model assists insurers in determining coverage and adjusting premiums based on economic losses predicted by the ARIMA model. It also aids real estate companies in deciding whether to develop in certain areas. The ERM model considers human, weather, and geographical factors to assess risks and predict potential property damage caused by extreme weather. The AGNES algorithm clusters similar samples to identify regions with higher risks. This helps real estate companies make informed decisions about development projects. The entropy weight method is used to adjust insurance premiums by calculating changes in regional risk coefficients. Continuous monitoring and analysis of risk coefficients improve risk assessment accuracy and enable reasonable premium adjustments.
Downloads
References
Clarke, Ben, et al. "Extreme weather impacts of climate change: an attribution perspective." Environmental Research: Climate 1.1 (2022): 012001.
Nica, Aurelia, Adina Popescu, and Daniela-Cristina Ibanescu. "Human influence on the climate system." Curr Trends Nat Sci 8.15 (2019): 209 - 215.
Bouwer L M. Observed and projected impacts from extreme weather events: implications for loss and damage [J]. Loss and damage from climate change: Concepts, methods and policy options, 2019: 63 - 82.
Clarke B, Otto F, Stuart-Smith R, et al. Extreme weather impacts of climate change: an attribution perspective [J]. Environmental Research: Climate, 2022, 1 (1): 012001.
Weil hammer V, Schmid J, Mittermeier I, et al. Extreme weather events in europe and their health consequences–A systematic review [J]. International Journal of Hygiene and Environmental Health, 2021, 233: 113688.
Prokop’eva E L. The modern Russian insurance market: Problems and potential for development[J]. Finansy i kredit= Finance and Credit, 2019, 25 (1): 177 - 195.
Morozova S A, Rostov A A. Development of economic and mathematical models of dynamics and analysis of insurance markets in the regions of the Volga federal district [J]. Вестник Самарского университета. Экономика и управление, 2023, 14 (1): 192 - 201.
Hohl R, Jiang Z, Vu M T, et al. Using a regional climate model to develop index-based drought insurance for sovereign disaster risk transfer[J]. Agricultural Finance Review, 2020, 81 (1): 151 - 168.
Awe O, Okeyinka A, Fatokun J O. An alternative algorithm for ARIMA model selection[C]//2020 international conference in mathematics, computer engineering and computer science (ICMCECS). IEEE, 2020: 1 - 4.
Benvenuto D, Giovanetti M, Vassallo L, et al. Application of the ARIMA model on the COVID-2019 epidemic dataset [J]. Data in brief, 2020, 29: 105340.
Khan S, Alghulaiakh H. ARIMA model for accurate time series stocks forecasting [J]. International Journal of Advanced Computer Science and Applications, 2020, 11 (7).
Zhu Y, Tian D, Yan F. Effectiveness of entropy weight method in decision-making [J]. Mathematical Problems in Engineering, 2020, 2020: 1 - 5.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Highlights in Science, Engineering and Technology

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.







