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Keywords: neural network
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Proceedings Papers

Paper presented at the The 30th International Ocean and Polar Engineering Conference, October 11–16, 2020
Paper Number: ISOPE-I-20-1136
... energy power stations. machine learning energy conservation renewable energy artificial intelligence sustainability sustainable development neural network selection sea area site selection wave energy power station criteria weight china criteria water depth qingdao ocean energy...
Proceedings Papers

Paper presented at the The 30th International Ocean and Polar Engineering Conference, October 11–16, 2020
Paper Number: ISOPE-I-20-1150
... wind, air pressure, and precipitation, and the increase and decrease of water caused by seasonal climate factors. This is the main reason that restricts the accuracy of traditional water level prediction models. With the development of artificial intelligence, neural networks and fuzzy logic reasoning...
Proceedings Papers

Paper presented at the The 30th International Ocean and Polar Engineering Conference, October 11–16, 2020
Paper Number: ISOPE-I-20-1281
... approach to address these limitations. machine learning simulation monitoring system prediction assessment requirement artificial intelligence riser fatigue assessment input data sensor flexible riser life extension fatigue damage upstream oil & gas neural network seastate...
Proceedings Papers

Paper presented at the The 30th International Ocean and Polar Engineering Conference, October 11–16, 2020
Paper Number: ISOPE-I-20-1259
... ABSTRACT Artificial Neural Network (ANN) model is used to study the relationship between sea ice characteristics and natural factors such as climate, hydrology and marine environment during storms in open-water season in Waters off Mackenzie Delta. Meanwhile, the Simulating Waves Nearshore...
Proceedings Papers

Paper presented at the The 30th International Ocean and Polar Engineering Conference, October 11–16, 2020
Paper Number: ISOPE-I-20-1282
... between the ocean environment loads and the extreme values of 6 DoFs response. The predicted results indicated that the present LSTM neural network method could provide the higher accuracy with the lower computational cost. INTRODUCTION Due to their large operating area, high stability, and low cost...
Proceedings Papers

Paper presented at the The 30th International Ocean and Polar Engineering Conference, October 11–16, 2020
Paper Number: ISOPE-I-20-1229
... ABSTRACT Arctic climate is changing. Areas covered by sea ice are decreasing, while the number of vessels operating in ice infested water increases. This study offers a perspective of applying fully connected neural networks (NN) to predict vessels' speeds on a part of the Northern Sea Route...
Proceedings Papers

Paper presented at the The 30th International Ocean and Polar Engineering Conference, October 11–16, 2020
Paper Number: ISOPE-I-20-2199
... artificial intelligence models like support vector machines, radial basis function, genetic programming and group method of data handling. A prediction model of BP neural network is proposed for the pipeline scour depth in this paper, which weights and thresholds of the BP neural network were optimized by...
Proceedings Papers

Paper presented at the The 30th International Ocean and Polar Engineering Conference, October 11–16, 2020
Paper Number: ISOPE-I-20-1280
...-force prediction model is proposed, which makes full use of the efficient processing characteristics of Long Short-Term Memory Recurrent Neural Network (LSTM RNN) and Nonlinear Autoregressive Exogenous Feedback Neural Network (NARX FNN) for time series data processing. The relationship between the wave...
Proceedings Papers

Paper presented at the The 30th International Ocean and Polar Engineering Conference, October 11–16, 2020
Paper Number: ISOPE-I-20-2201
... neural network algorithm, and the nonlinear mapping relationship was established between the stress field and scour depth by training a large number of samples. Finally, through the MFC application program-Visual Studio, the visual software for identifying the scour state of jack-up's pile legs and boots...
Proceedings Papers

Paper presented at the The 30th International Ocean and Polar Engineering Conference, October 11–16, 2020
Paper Number: ISOPE-I-20-2140
... evidence space is constructed, and the initial diagnosis of the evidence space is carried out by using radial basis function neural network, and the preliminary diagnosis results of each evidence body are fused by the weighted evidence fusion theory. The diagnosis result shows that it has high reliability...
Proceedings Papers

Paper presented at the The 30th International Ocean and Polar Engineering Conference, October 11–16, 2020
Paper Number: ISOPE-I-20-3249
... experimental conditions. The database was organized, cleaned, and analyzed. Model tests related to the floating units larger than standard size LNG carriers or LNG fueled vessels were selected. Then, the selected target data had been used for the artificial neural network to predict the model test results from...
Proceedings Papers

Paper presented at the The 29th International Ocean and Polar Engineering Conference, June 16–21, 2019
Paper Number: ISOPE-I-19-465
... Research on the Speed Optimization Model Based on BP Neural Network and Genetic Algorithm (GA) Hui Lin, Shunhuai Chen, Liang Luo, Zimin Wang, Yuhong Zeng Wuhan University Of Technology Wuhan,China ABSTRACT In this paper, a larger number of data was adopted, which is collected during the operation...
Proceedings Papers

Paper presented at the The 29th International Ocean and Polar Engineering Conference, June 16–21, 2019
Paper Number: ISOPE-I-19-364
... multiple neural networks learning from the maritime fusion data (Borkowski, 2017). For all the above related studies, high-quality AIS data set is the necessary prerequisite. The quality of the AIS data depends on the AIS equipment and AIS message receiver base station (Lapinski and Isenor, 2011). However...
Proceedings Papers

Paper presented at the The 29th International Ocean and Polar Engineering Conference, June 16–21, 2019
Paper Number: ISOPE-I-19-499
... some bad sea conditions. significant value artificial intelligence sea condition machine learning htf method amplitude lstm method neural network sea state deep learning heave time series four-level sea condition estimation calculation lstm model pitch motion follow eq ship...
Proceedings Papers

Paper presented at the The 29th International Ocean and Polar Engineering Conference, June 16–21, 2019
Paper Number: ISOPE-I-19-602
... ABSTRACT Gas kicks are often encountered during drilling the oil & gas formations. This paper proposes a data-driven method by employing machine learning for real-time detection of gas kicks. Firstly, logging data is recorded and compiled for gas cases. Secondly, artificial neural network...
Proceedings Papers

Paper presented at the The 29th International Ocean and Polar Engineering Conference, June 16–21, 2019
Paper Number: ISOPE-I-19-557
... methods to discuss and compare with the resistance performance of monohull and multi-hull. The primary predicted values and parametric conditions for a minimum drag should be acquired by Taguchi's method first. Then, we applied a neural network to construct the nonlinear metamodel and genetic algorithm to...
Proceedings Papers

Paper presented at the The 29th International Ocean and Polar Engineering Conference, June 16–21, 2019
Paper Number: ISOPE-I-19-633
... becoming the main method for targets detection and recognition recently, which consists of image deep feature extraction and target recognition and location based on deep neural network. At present, the existing commonly used target detection and recognition algorithms based on deep learning region...
Proceedings Papers

Paper presented at the The 29th International Ocean and Polar Engineering Conference, June 16–21, 2019
Paper Number: ISOPE-I-19-575
... ABSTRACT In the present study, a 168 hrs-forecast wave model is developed to predict significant wave heights at four stations, Japan, using the Group Method of Data Handling (GMDH). The GMDH is one of machine learning (like artificial neural network) and has an advantage of the convenience...
Proceedings Papers

Paper presented at the The 29th International Ocean and Polar Engineering Conference, June 16–21, 2019
Paper Number: ISOPE-I-19-219
...: Kriging; Integrity Management; Performance monitoring; Flexible Pipeline; CAPEX optimization; Supervised Learning; Fatigue NOMENCLATURE ANN: Artificial Neural Network BRGM: Bureau de Recherche Geologique et Minière CAPEX: Capital Expenditure CPM: Condition Performance Monitoring FEA: Finite Element...
Proceedings Papers

Paper presented at the The 29th International Ocean and Polar Engineering Conference, June 16–21, 2019
Paper Number: ISOPE-I-19-304
... neural network time series artificial neural network failure mode asset and portfolio management wind energy artificial intelligence wind turbine offshore wind turbine asset management model weather model machine learning renewable energy reliability weather data weather condition...

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