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Jeffrey Tim Query, Evaristo Diz
Pág. 145 - 159
AbstractIn this study we examine the robustness of fit for a multivariate and an autoregressive integrated moving average model to a data sample time series type. The sample is a recurrent actuarial data set for a 10-year horizon. We utilize ...
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Yong Zhang, Xin Wang, Zongli Jiang, Junfeng Wei, Hiroyuki Enomoto and Tetsuo Ohata
Arctic glaciers comprise a small fraction of the world?s land ice area, but their ongoing mass loss currently represents a large cryospheric contribution to the sea level rise. In the Suntar-Khayata Mountains (SKMs) of northeastern Siberia, in situ measu...
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Jianzhao Liu, Liping Gao, Fenghui Yuan, Yuedong Guo and Xiaofeng Xu
Soil water shortage is a critical issue for the Southwest US (SWUS), the typical arid region that has experienced severe droughts over the past decades, primarily caused by climate change. However, it is still not quantitatively understood how soil water...
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Angel E. Muñoz-Zavala, Jorge E. Macías-Díaz, Daniel Alba-Cuéllar and José A. Guerrero-Díaz-de-León
This paper reviews the application of artificial neural network (ANN) models to time series prediction tasks. We begin by briefly introducing some basic concepts and terms related to time series analysis, and by outlining some of the most popular ANN arc...
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Dimitris Fotakis, Panagiotis Patsilinakos, Eleni Psaroudaki and Michalis Xefteris
In this work, we consider the problem of shape-based time-series clustering with the widely used Dynamic Time Warping (DTW) distance. We present a novel two-stage framework based on Sparse Gaussian Modeling. In the first stage, we apply Sparse Gaussian P...
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