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Magazine et Edition

Volume 224 (2022): Edition 1 (March 2022)

Volume 223 (2020): Edition 4 (December 2020)

Volume 222 (2020): Edition 3 (September 2020)

Volume 220-221 (2020): Edition 1-2 (June 2020)

Volume 219 (2019): Edition 4 (December 2019)

Volume 218 (2019): Edition 3 (September 2019)

Volume 217 (2019): Edition 2 (June 2019)

Volume 216 (2019): Edition 1 (March 2019)

Volume 215 (2018): Edition 4 (December 2018)

Volume 214 (2018): Edition 3 (September 2018)

Volume 213 (2018): Edition 2 (June 2018)

Volume 212 (2018): Edition 1 (March 2018)

Volume 211 (2017): Edition 4 (December 2017)

Volume 210 (2017): Edition 3 (September 2017)

Volume 209 (2017): Edition 2 (June 2017)

Volume 208 (2017): Edition 1 (March 2017)

Volume 207 (2016): Edition 4 (December 2016)

Volume 206 (2016): Edition 3 (September 2016)

Volume 205 (2016): Edition 2 (June 2016)

Volume 204 (2016): Edition 1 (March 2016)

Détails du magazine
Format
Magazine
eISSN
2720-4286
Première publication
30 Mar 2016
Période de publication
1 fois par an
Langues
Anglais

Chercher

Volume 224 (2022): Edition 1 (March 2022)

Détails du magazine
Format
Magazine
eISSN
2720-4286
Première publication
30 Mar 2016
Période de publication
1 fois par an
Langues
Anglais

Chercher

5 Articles
Accès libre

Impact of Starting Outlier Removal on Accuracy of Time Series Forecasting

Publié en ligne: 08 Mar 2022
Pages: 1 - 15

Résumé

Abstract

The presence of an outlier at the starting point of a univariate time series negatively influences the forecasting accuracy. The starting outlier is effectively removed only by making it equal to the second time point value. The forecasting accuracy is significantly improved after the removal. The favorable impact of the starting outlier removal on the time series forecasting accuracy is strong. It is the least favorable for time series with exponential rising. In the worst case of a time series, on average only 7 % to 11 % forecasts after the starting outlier removal are worse than they would be without the removal.

Mots clés

  • time series forecasting
  • outlier
  • ARIMA
  • forecasting accuracy
  • RMSE
  • MaxAE
Accès libre

The Analysis of the Strength of the Ship’s Hull After Running Aground

Publié en ligne: 08 Mar 2022
Pages: 16 - 27

Résumé

Abstract

The article presents a simulation of a ship running aground. It introduces the analytical description, as well as the methodology of carrying out strength calculations when creating engineering tasks related to the topic. It shows the state of stresses and deformations of the hull of a modern minehunter after a collision with the bottom for two immersion depths. Research and development opportunities for future considerations are highlighted in the conclusions.

Mots clés

  • Destroyer of mines
  • collision with the bottom
  • hull strength
  • finite element method
Accès libre

Arima Model Optimal Selection for Time Series Forecasting

Publié en ligne: 08 Mar 2022
Pages: 28 - 40

Résumé

Abstract

A fast-and-flexible method of ARIMA model optimal selection is suggested for univariate time series forecasting. The method allows obtaining as-highly-accurate-as-possible forecasts automatically. It is based on effectively finding lags by the autocorrelation function of a detrended time series, where the best-fitting polynomial trend is subtracted from the time series. The forecasting quality criteria are the root-mean-square error (RMSE) and the maximum absolute error (MaxAE) allowing to register information about the average inaccuracy and worst outlier. Thus, the ARIMA model optimal selection is performed by simultaneously minimizing RMSE and Max-AE, whereupon the minimum defines the best model. Otherwise, if the minimum does not exist, a combination of minimal-RMSE and minimal-MaxAE ARIMA models is used.

Mots clés

  • time series forecasting
  • ARIMA
  • model selection
  • forecasting horizon
  • seasonality
  • trend
Accès libre

The Assessment of Unmanned Vessel Operation in Heavy Traffic Areas. Case Study of the North Sea Crossing by Unmanned Surface Vessel Sea-Kit

Publié en ligne: 08 Mar 2022
Pages: 41 - 67

Résumé

Abstract

The continuous development of autonomous and unmanned technology is accelerating the adoption of unmanned vessels for various maritime operations. Despite the technological developments there is still a lack of clear regulatory and organizational frameworks for testing and exploiting the potential of unmanned surface vessels (USVs) in real-world maritime conditions. Such real-world testing becomes ever more complex when operating in multiple nations territorial waters. In May 2019 USV ‘Maxlimer’ crossed the North Sea from the United Kingdom to Belgium and back, carrying goods, to demonstrate the ability of unmanned surface vessels to interact with real marine traffic in an uncontrolled environment. The paper presents this mission in light of the current state of marine autonomy projects as well as the regulatory works conducted by various organizations worldwide.

Mots clés

  • Unmanned Surface Vessel
  • Autonomous Surface Vessel
  • marine autonomy
  • USV ‘SEA-KIT’
  • collision avoidance
Accès libre

Directions of Development of the Autonomous Unmanned Underwater Vehicles. A Review

Publié en ligne: 08 Mar 2022
Pages: 68 - 79

Résumé

Abstract

In the paper review of unmanned underwater vehicle (AUV) is presented. The description of main systems is depicted with focus on autonomous single vehicle as well as a swarm. As a consequence of development of AUV technology, research centers are focused on issues related to increasing the degree of their autonomy. Nowadays, mostly navigation and communication as well as high-efficient propeller systems are being developed. There are problems linking this issues. Their solutions includes development of new control laws containing algorithms to prevent collisions - for unmanned vehicles with elements of the underwater environment and for several underwater vehicles cooperating with each other in a swarm.

Mots clés

  • Unmanned Underwater Vehicles
  • Remotely Operated Vehicles
  • Autonomous Underwater
5 Articles
Accès libre

Impact of Starting Outlier Removal on Accuracy of Time Series Forecasting

Publié en ligne: 08 Mar 2022
Pages: 1 - 15

Résumé

Abstract

The presence of an outlier at the starting point of a univariate time series negatively influences the forecasting accuracy. The starting outlier is effectively removed only by making it equal to the second time point value. The forecasting accuracy is significantly improved after the removal. The favorable impact of the starting outlier removal on the time series forecasting accuracy is strong. It is the least favorable for time series with exponential rising. In the worst case of a time series, on average only 7 % to 11 % forecasts after the starting outlier removal are worse than they would be without the removal.

Mots clés

  • time series forecasting
  • outlier
  • ARIMA
  • forecasting accuracy
  • RMSE
  • MaxAE
Accès libre

The Analysis of the Strength of the Ship’s Hull After Running Aground

Publié en ligne: 08 Mar 2022
Pages: 16 - 27

Résumé

Abstract

The article presents a simulation of a ship running aground. It introduces the analytical description, as well as the methodology of carrying out strength calculations when creating engineering tasks related to the topic. It shows the state of stresses and deformations of the hull of a modern minehunter after a collision with the bottom for two immersion depths. Research and development opportunities for future considerations are highlighted in the conclusions.

Mots clés

  • Destroyer of mines
  • collision with the bottom
  • hull strength
  • finite element method
Accès libre

Arima Model Optimal Selection for Time Series Forecasting

Publié en ligne: 08 Mar 2022
Pages: 28 - 40

Résumé

Abstract

A fast-and-flexible method of ARIMA model optimal selection is suggested for univariate time series forecasting. The method allows obtaining as-highly-accurate-as-possible forecasts automatically. It is based on effectively finding lags by the autocorrelation function of a detrended time series, where the best-fitting polynomial trend is subtracted from the time series. The forecasting quality criteria are the root-mean-square error (RMSE) and the maximum absolute error (MaxAE) allowing to register information about the average inaccuracy and worst outlier. Thus, the ARIMA model optimal selection is performed by simultaneously minimizing RMSE and Max-AE, whereupon the minimum defines the best model. Otherwise, if the minimum does not exist, a combination of minimal-RMSE and minimal-MaxAE ARIMA models is used.

Mots clés

  • time series forecasting
  • ARIMA
  • model selection
  • forecasting horizon
  • seasonality
  • trend
Accès libre

The Assessment of Unmanned Vessel Operation in Heavy Traffic Areas. Case Study of the North Sea Crossing by Unmanned Surface Vessel Sea-Kit

Publié en ligne: 08 Mar 2022
Pages: 41 - 67

Résumé

Abstract

The continuous development of autonomous and unmanned technology is accelerating the adoption of unmanned vessels for various maritime operations. Despite the technological developments there is still a lack of clear regulatory and organizational frameworks for testing and exploiting the potential of unmanned surface vessels (USVs) in real-world maritime conditions. Such real-world testing becomes ever more complex when operating in multiple nations territorial waters. In May 2019 USV ‘Maxlimer’ crossed the North Sea from the United Kingdom to Belgium and back, carrying goods, to demonstrate the ability of unmanned surface vessels to interact with real marine traffic in an uncontrolled environment. The paper presents this mission in light of the current state of marine autonomy projects as well as the regulatory works conducted by various organizations worldwide.

Mots clés

  • Unmanned Surface Vessel
  • Autonomous Surface Vessel
  • marine autonomy
  • USV ‘SEA-KIT’
  • collision avoidance
Accès libre

Directions of Development of the Autonomous Unmanned Underwater Vehicles. A Review

Publié en ligne: 08 Mar 2022
Pages: 68 - 79

Résumé

Abstract

In the paper review of unmanned underwater vehicle (AUV) is presented. The description of main systems is depicted with focus on autonomous single vehicle as well as a swarm. As a consequence of development of AUV technology, research centers are focused on issues related to increasing the degree of their autonomy. Nowadays, mostly navigation and communication as well as high-efficient propeller systems are being developed. There are problems linking this issues. Their solutions includes development of new control laws containing algorithms to prevent collisions - for unmanned vehicles with elements of the underwater environment and for several underwater vehicles cooperating with each other in a swarm.

Mots clés

  • Unmanned Underwater Vehicles
  • Remotely Operated Vehicles
  • Autonomous Underwater

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