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Authors: Tianhao Tang and Tianzhen Wang

Affiliation: Institute of Electrical & Control Engineering, Shanghai Maritime University, China

Keyword(s): Nonlinear time series model, adaptive predictor, artificial neural networks, data mining.

Related Ontology Subjects/Areas/Topics: Informatics in Control, Automation and Robotics ; Signal Processing, Sensors, Systems Modeling and Control ; System Identification ; Time Series and System Modeling

Abstract: This paper presents a new multiple dimension predictive model based on the diagonal recurrent neural networks (PDRNN) with a combined learning algorithm. This method can be used to predict not only values, but also some points in the multi-dimension space. And also its applications in data mining will be discussed in the paper. Some analysis results show the significant improvement to ship route prediction using the PDRNN model in database of geographic information system (GIS).

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Paper citation in several formats:
Tang, T. and Wang, T. (2005). ANN-BASED MULTIPLE DIMENSION PREDICTOR FOR SHIP ROUTE PREDICTION. In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO; ISBN 972-8865-31-7; ISSN 2184-2809, SciTePress, pages 52-59. DOI: 10.5220/0001168200520059

@conference{icinco05,
author={Tianhao Tang. and Tianzhen Wang.},
title={ANN-BASED MULTIPLE DIMENSION PREDICTOR FOR SHIP ROUTE PREDICTION},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO},
year={2005},
pages={52-59},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001168200520059},
isbn={972-8865-31-7},
issn={2184-2809},
}

TY - CONF

JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO
TI - ANN-BASED MULTIPLE DIMENSION PREDICTOR FOR SHIP ROUTE PREDICTION
SN - 972-8865-31-7
IS - 2184-2809
AU - Tang, T.
AU - Wang, T.
PY - 2005
SP - 52
EP - 59
DO - 10.5220/0001168200520059
PB - SciTePress