On-line prediction of escaping fish from catching net by neural network and circular approximation

Toshiaki Yoshida; Hidekazu Suzuki; Mamoru Minami; Yasushi Mae

doi:10.1109/SICE.2006.315377

On-line prediction of escaping fish from catching net by neural network and circular approximation

Toshiaki Yoshida, Hidekazu Suzuki, Mamoru Minami, Yasushi Mae

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

This paper presents a method to predict a fish motion by Neural Network (N.N.) with on-line learning. We assume the motion trajectory of a fish swimming in a pool be approximated by circles with time varying radius and center position. We try to improve prediction accuracy of a fish motion by using N.N. whose inputs are radii and angular velocities in previous three control-times and outputs are radius and angular velocity in the following control period. Using radius and angular velocity obtained by circular approximation, we confirmed that the proposed N.N. prediction system can maintain good prediction performances under the proposed on-line learning process.

Original language	English
Title of host publication	2006 SICE-ICASE International Joint Conference
Pages	5120-5125
Number of pages	6
DOIs	https://doi.org/10.1109/SICE.2006.315377
Publication status	Published - 2006
Externally published	Yes
Event	2006 SICE-ICASE International Joint Conference - Busan, Korea, Republic of Duration: Oct 18 2006 → Oct 21 2006

Publication series

Name	2006 SICE-ICASE International Joint Conference

Other

Other	2006 SICE-ICASE International Joint Conference
Country	Korea, Republic of
City	Busan
Period	10/18/06 → 10/21/06

Keywords

Back propagation
Gazing-GA
Neural network
Prediction

ASJC Scopus subject areas

Computer Science Applications
Control and Systems Engineering
Electrical and Electronic Engineering

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On-line prediction of escaping fish from catching net by neural network and circular approximation. / Yoshida, Toshiaki; Suzuki, Hidekazu; Minami, Mamoru; Mae, Yasushi.

2006 SICE-ICASE International Joint Conference. 2006. p. 5120-5125 4108687 (2006 SICE-ICASE International Joint Conference).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yoshida, T, Suzuki, H, Minami, M & Mae, Y 2006, On-line prediction of escaping fish from catching net by neural network and circular approximation. in 2006 SICE-ICASE International Joint Conference., 4108687, 2006 SICE-ICASE International Joint Conference, pp. 5120-5125, 2006 SICE-ICASE International Joint Conference, Busan, Korea, Republic of, 10/18/06. https://doi.org/10.1109/SICE.2006.315377

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abstract = "This paper presents a method to predict a fish motion by Neural Network (N.N.) with on-line learning. We assume the motion trajectory of a fish swimming in a pool be approximated by circles with time varying radius and center position. We try to improve prediction accuracy of a fish motion by using N.N. whose inputs are radii and angular velocities in previous three control-times and outputs are radius and angular velocity in the following control period. Using radius and angular velocity obtained by circular approximation, we confirmed that the proposed N.N. prediction system can maintain good prediction performances under the proposed on-line learning process.",

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N2 - This paper presents a method to predict a fish motion by Neural Network (N.N.) with on-line learning. We assume the motion trajectory of a fish swimming in a pool be approximated by circles with time varying radius and center position. We try to improve prediction accuracy of a fish motion by using N.N. whose inputs are radii and angular velocities in previous three control-times and outputs are radius and angular velocity in the following control period. Using radius and angular velocity obtained by circular approximation, we confirmed that the proposed N.N. prediction system can maintain good prediction performances under the proposed on-line learning process.

AB - This paper presents a method to predict a fish motion by Neural Network (N.N.) with on-line learning. We assume the motion trajectory of a fish swimming in a pool be approximated by circles with time varying radius and center position. We try to improve prediction accuracy of a fish motion by using N.N. whose inputs are radii and angular velocities in previous three control-times and outputs are radius and angular velocity in the following control period. Using radius and angular velocity obtained by circular approximation, we confirmed that the proposed N.N. prediction system can maintain good prediction performances under the proposed on-line learning process.

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KW - Gazing-GA

KW - Neural network

KW - Prediction

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On-line prediction of escaping fish from catching net by neural network and circular approximation

Abstract

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Keywords

ASJC Scopus subject areas

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