Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 29, Pages: 1-8
Krishna Kumar Nagalingam1*, Savitha Ramasamy2 and Abdullah Al Mamun1
1 School of Electrical and Computer Engineering, [email protected]
2 Institute of Infocomm Research, [email protected]
*Author for correspondence
Krishna Kumar Nagalingam
School of Electrical and Computer Engineering,
Background/Objectives: To develop a universal method for wind force and moment coefficient prediction on marine vessels independent of ship types. The marine vessels’ equation of motion includes hydrodynamics forces, moments and environmental disturbances. One of the environmental forces and moment acting on the ship originate from wind and play a vital role in offshore operations. Till date, wind loads are determined by statistical and regression analysis. In this paper, an extreme learning machine is used as a technique to predict the wind force and moment coefficients. Findings: This approach is novel and is common for any ship shapes. The performance of the proposed method is much more accurate and simplified compared with the existing tools. The result matches precisely with the experimental data. Applications/ Improvement: This method shall be an effective tool in calculation of wind loads on marine structures which is extremely critical in marine operations and ship maneuvering and positioning.
Keywords: Extreme Learning Machine (ELM), Neural Network, Wind Force and Moment Coefficient
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