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Articles by Wisnu Wardhana
Total Records ( 3 ) for Wisnu Wardhana
  Endang Widjiati , Eko Budi Djatmiko , Wisnu Wardhana and Wirawan
  Analysing characteristics of propeller cavitation noise is necessary in relation with the identification of noise signature in conjunction with both surface ship and submarine operations. Since, the noise signature is determined by propeller, flow and machinery noise then any vessel that has certain propeller, hull shape and machines will have a peculiar signature. The propeller cavitation noise can be generated by means of experiment performed in a cavitation tunnel. This study reports some results of the noise characterization experiment conducted in the Cavitation Tunnel available at the Indonesian Hydrodynamic Laboratory, Surabaya, Indonesia. Two B-series propeller models, i.e., 4 and 7-blade were studied in the experiment. Time-Frequency distribution, namely Wigner-Ville Distribution (WVD) is applied to observe the characteristics of the cavitation noise. Results show that the WVD can differentiate whether the propeller cavitation noise is generated either by the 4 or 7-blade propeller. In this study, three different kinds of categories in the appearance of cavitation are distinguished, i.e., when the propeller does not experience cavitation, if only hub and tip vortex cavitation develop and when various cavitations occur simultaneously.
  Wimala L. Dhanistha , Herman Pratikno and Wisnu Wardhana
 

Indonesia is an archipelagic country a more reliable transportation is a type of sea transportation. One of the obstacles in transportation is that 38% of the causes of marine accidents are high-wave natural disasters caused by wind speeds. The higher the wind speed, the higher the wave will occur. Artificial neural networks are artificial intelligence that can be used to predict high waves. These neural networking advantages can be used for nonlinear systems. Neural networks can be used as high-wave predictors to predict the wave height of the last few hours to come.

  Wimala L. Dhanistha , Wisnu Wardhana and Mufidatul Islamiyah
  Sea transportation is a mainstay transportation in Indonesia, it is because Indonesia consists of thousands of islands, so that, to connect between islands, sea transportation is needed. Waves are very closely related to the sea, waves that are negative that is waves that can endanger shipping. One of the factors causing sea accidents is natural disasters, namely high waves. To minimize accidents due to high waves, wave predictions can be made in the hours to come using the neural network algorithm. Neural network was chosen because of its advantages in processing system input-output data even though the system is nonlinear. The advantage is that the neural network is chosen as a wave height predictor algorithm. ANFIS is an algorithm for the development of a combination of neural networks and fuzzy artificial intelligence. The ability of ANFIS to predict wave heights is no less good with neural networks, it is because ANFIS is a combination of neural network and fuzzy. It is hoped that by doing this research it can compare which algorithm is better in predicting wave heights.
 
 
 
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