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.

AR Dynamic Evolving Neuro-Fuzzy Inference System for Mortality Data / Piscopo, Gabriella. - 46:(2018), pp. 217-223. [10.1007/978-3-319-76002-5_18]

AR Dynamic Evolving Neuro-Fuzzy Inference System for Mortality Data

Piscopo, Gabriella
2018

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.
2018
978-3-319-76001-8
978-3-319-76002-5
AR Dynamic Evolving Neuro-Fuzzy Inference System for Mortality Data / Piscopo, Gabriella. - 46:(2018), pp. 217-223. [10.1007/978-3-319-76002-5_18]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/738005
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