In the actual operation task, the workload of the oceanaut is mainly mental workload. For the oceanaut, too high or too low mental workload will significantly reduce work efficiency and even lead to major safety accidents. Classification of mental workload of the oceanaut in operational task research is one of the key problem in operational task research. However, the traditional mechanism modeling method is complex, computational complexity and low accuracy. In this paper, machine learning method got used to the model. Based-on Electroencephalograph (EEG) data collected from the simulation experiment of the operating manipulator, multiclass support vector machine(MSVM) was used to train the samples, and the optimal training sample size was selected. The parameters of the model were optimized by grid search mixed with particle-swarm optimization algorithm (GSPSO) to obtain the optimal classification of oceanauts mental workload. As the research results showed that the method could accurately classify the mental workload of oceanauts.Furthermore, GSPSO-MSVM in the classification of oceanauts mental workload had the advantage over K-nearest neighbors(KNN), BP neural network(BP), random forest(RF) and support vector machines(SVM).
- Downloaded 212 times
- Download rankings, all-time:
- Site-wide: 178,743
- In scientific communication and education: 894
- Year to date:
- Site-wide: 41,022
- Since beginning of last month:
- Site-wide: 159,232
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!