LSTM

An Analysis of Sustainable Strategies for Property Insurance Introduction In this paper, I developed an LSTM model with an accuracy of 85% to predict future natural disasters using natural disaster data in Florida and California of the past 30 years. Applied neural network, linear regression, and deep learning models to assess the relationship between natural disasters and property damage. Summary In recent years, homeowners and insurance companies have faced significant crises, necessitating the development of comprehensive solutions to meet the needs of all stakeholders involved in the insurance industry. This paper presents an innovative approach to property insurance by introducing an insurance company’s property allocation model based on deep learning and LSTM and a market investment model utilizing regression analysis, as well as a community conservation building model employing grey correlation analysis. These models provide valuable insights and correlation analyses for the property-casualty insurance sector, promoting a more sustainable industry. ...