Charted Depth Interpolation

• 발행기관: 한국항해항만학회
• 저자명: Shi Chaojian
• 간행물 정보: 『한국항해항만학회 학술대회논문집』2004 Asia Navigation Conference, 37~44쪽, 전체 8쪽
• 주제분류: 공학 > 해양공학
• 파일형태: PDF
• 발행일자: 2004.08.30

영문 초록

Continuous depth data are often required in applications of both onboard systems and maritime simulation. But data available are usually discrete and irregularly distributed. Based on the neuron network technique, methods of interpolation to the charted depth are suggested in this paper. Two algorithms based on Levenberg-Marquardt back-propaganda and radial-basis function networks are investigated respectively. A dynamic neuron network system is developed which satisfies both real time and mass processing applications. Using hyperbolic paraboloid and typical chart area, effectiveness of the algorithms is tested and error analysis presented. Special process in practical applications such as partition of lager areas, normalization and selection of depth contour data are also illustrated.

목차

1 Introduction

2 Neuron Network Approaches

3 Tests and Implementation Analysis

4 Conclusions

키워드

charted depth neuron network function approximation spatial interpolation