Forecast of traffic accidents based on components extraction and an autoregressive neural network with levenberg-marquardt

Lida Barba, Nibaldo Rodríguez

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

Resumen

In this paper is proposed an improved one-step-ahead strategy for traffic accidents and injured forecast in Concepción, Chile, from year 2000 to 2012 with a weekly sample period. This strategy is based on the extraction and estimation of components of a time series, the Hankel matrix is used to map the time series, the Singular Value Decomposition(SVD) extracts the singular values and the orthogonal matrix, and the components are forecasted with an Autoregressive Neural Network (ANN) based on Levenberg-Marquardt (LM) algorithm. The forecast accuracy of this proposed strategy are compared with the conventional process, SVD-ANN-LM achieved aMAPE of 1.9% for the time series Accidents, and a MAPE of 2.8% for the time series Injured, in front of 14.3% and 21.1% that were obtained with the conventional process.

Idioma originalInglés
Título de la publicación alojadaMining Intelligence and Knowledge Exploration - 2nd International Conference, MIKE 2014, Proceedings
EditoresRajendra Prasath, Philip O’Reilly, Thangairulappan Kathirvalavakumar
EditorialSpringer Verlag
Páginas82-90
Número de páginas9
ISBN (versión digital)9783319138169
DOI
EstadoPublicada - 2014
Publicado de forma externa
Evento2nd International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2014 - Cork, Irlanda
Duración: 10 dic. 201412 dic. 2014

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen8891
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia2nd International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2014
País/TerritorioIrlanda
CiudadCork
Período10/12/1412/12/14

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