Downloads provided by UsageCounts
Terrestrial vessel automatic identification system (AIS) data was collected around Ålesund, Norway in 2020, from multiple receiving stations with unsynchronized clocks. Features are 'mmsi', 'imo', 'length', 'latitude', 'longitude', 'sog', 'cog', 'true_heading', 'datetime UTC', 'navigational status', and 'message number'. Compact parquet files can be turned into data frames with python's pandas library. Data is irregularly sampled because of the navigational status. The preprocessing script for training the machine learning models can be found here. There you will find gathered dozen of trainable models and hundreds of datasets. Visit this website for more information about the data. If you have additional questions, please find our information in the links below: Luka Grgičević Ottar Laurits Osen
ship, corrupted, data, terrestrial, irregulary sampled, AIS, hystorical, vessel, series, missing, time
ship, corrupted, data, terrestrial, irregulary sampled, AIS, hystorical, vessel, series, missing, time
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 97 | |
| downloads | 46 |

Views provided by UsageCounts
Downloads provided by UsageCounts