Evolving sparsely connected neural networks for multi-step ahead forecasting
Time Series Forecasting (TSF) is an important tool to sup- port decision making. Artificial Neural Networks (ANN) are innate candidates for TSF due to advantages such as nonlin- ear learning and noise tolerance. However, the search for the best ANN is a complex task that highly affects the forecast-...
Main Author: | |
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Other Authors: | , , |
Format: | conferencePaper |
Language: | eng |
Published: |
2011
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Subjects: | |
Online Access: | http://hdl.handle.net/1822/14848 |
Country: | Portugal |
Oai: | oai:repositorium.sdum.uminho.pt:1822/14848 |