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Intelligent control algorithm for ship dynamic positioning

Meng W., Sheng L. H., Qing M., Rong B. G.

Archives of Control Sciences

2014

Vol. 24, no. 4

479--497

Ship motion in the sea is a complex nonlinear kinematics. The hydrodynamic coefficients of ship model are very difficult to accurately determine. Establishing accurate mathematical model of ship motion is difficult because of changing random factors in the marine environment. Aiming at seeking a method of control to realize ship positioning, intelligent control algorithms are adopt utilizing operator's experience. Fuzzy controller and the neural network controller are respectively designed. Through simulations and experiments, intelligent control algorithm can deal with the complex nonlinear motion, and has good robustness. The ship dynamic positioning system with neural network control has high positioning accuracy and performance.

An automatic classification technique for indexing of soccer highlight using neural networks

Kim H. S., Yang Y. K.

Machine Graphics and Vision

2001

Vol. 10, No. 4

467-487

A method for automatic classification of offensive play patterns in soccer games has been developed using the neural networks technique. Back-propagation (BP) neural network techniques have been applied to obtain data that define the positions of bith a player and the ball on the ground. The offensive play patterns thet have been formulated from the group formations enable automatic indexing of the highlights of soccer games. Except from actual soccer games, including some from the1998 French World Cup, yielded 297 video clips which were categorized into the following five types of patterns: Left-Running are 60, Right-Running 74, Center-Running 72, Corner-Kick 39 and Free-Kick 52. Examination of the results shows the following rates of satisfactory pattern recognition: Left-Running comes to 91.7%, Right-Running 100%, Center-Running 87.5%, Corner-Kick 97.4% and Free-Kick 75%.