In this paper we propose a dynamic evolving neuro-fuzzy inference system (DENFIS) to forecast mortality. DENFIS is an adaptive intelligent system suitable for dynamic time series prediction. An Evolving Cluster Method (ECM) drives the learning process. The typical fuzzy rules of the neurofuzzy systems are updated during the learning process and adjusted according to the features of the data. This makes possible to capture the changes in the mortality evolution at the basis of the so called longevity risk.

Dynamic Evolving Neuro-Fuzzy Inference System for Mortality Prediction / Piscopo, Gabriella. - In: INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH AND APPLICATIONS. - ISSN 2248-9622. - 07:03(2017), pp. 26-29. [10.9790/9622-0703062629]

Dynamic Evolving Neuro-Fuzzy Inference System for Mortality Prediction

Piscopo, Gabriella
2017

Abstract

In this paper we propose a dynamic evolving neuro-fuzzy inference system (DENFIS) to forecast mortality. DENFIS is an adaptive intelligent system suitable for dynamic time series prediction. An Evolving Cluster Method (ECM) drives the learning process. The typical fuzzy rules of the neurofuzzy systems are updated during the learning process and adjusted according to the features of the data. This makes possible to capture the changes in the mortality evolution at the basis of the so called longevity risk.
2017
Dynamic Evolving Neuro-Fuzzy Inference System for Mortality Prediction / Piscopo, Gabriella. - In: INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH AND APPLICATIONS. - ISSN 2248-9622. - 07:03(2017), pp. 26-29. [10.9790/9622-0703062629]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/695111
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