AR Dynamic Evolving Neuro-Fuzzy Inference System for Mortality Data

2Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

Abstract

In this paper we implement an integrated autoregressive Dynamic Evolving Neuro-Fuzzy Inference System in the context of mortality projections and compare the results with the classical Lee Carter model. DENFIS is an adaptive intelligent system suitable for dynamic time series prediction, where the learning process is driven by an Evolving Cluster Method. The typical fuzzy rules of the neuro- fuzzy systems are updated during the learning process and adjusted according to the features of the data. This makes possible to capture the historical changes in the mortality evolution.

Cite

CITATION STYLE

APA

Piscopo, G. (2018). AR Dynamic Evolving Neuro-Fuzzy Inference System for Mortality Data. In Springer Series on Demographic Methods and Population Analysis (Vol. 46, pp. 217–223). Springer Science and Business Media B.V. https://doi.org/10.1007/978-3-319-76002-5_18

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free