Simple Degree-of-Freedom Modeling of the Random Fluctuation Arising in Human–Bicycle Balance
| Autor: | Yoshikazu Yamanaka, Katsutoshi Yoshida, Keishi Sato |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Stochastic modelling Gaussian Probability density function 02 engineering and technology lcsh:Technology Measure (mathematics) lcsh:Chemistry Physics::Fluid Dynamics symbols.namesake 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering probability density function General Materials Science Statistical physics lcsh:QH301-705.5 Instrumentation stochastic model Statistical hypothesis testing Mathematics human–bicycle balance Fluid Flow and Transfer Processes Series (mathematics) particle swarm optimization lcsh:T Angular displacement Process Chemistry and Technology General Engineering Particle swarm optimization 020207 software engineering lcsh:QC1-999 Computer Science Applications lcsh:Biology (General) lcsh:QD1-999 lcsh:TA1-2040 symbols identification lcsh:Engineering (General). Civil engineering (General) lcsh:Physics |
| Zdroj: | Applied Sciences Volume 9 Issue 10 Applied Sciences, Vol 9, Iss 10, p 2154 (2019) |
| ISSN: | 2076-3417 |
| DOI: | 10.3390/app9102154 |
| Popis: | In this study, we propose a new simple degree-of-freedom fluctuation model that accurately reproduces the probability density functions (PDFs) of human&ndash bicycle balance motions as simply as possible. First, we measure the time series of the roll angular displacement and velocity of human&ndash bicycle balance motions and construct their PDFs. Next, using these PDFs as training data, we identify the model parameters by means of particle swarm optimization in particular, we minimize the Kolmogorov&ndash Smirnov distance between the human PDFs from the participants and the PDFs simulated by our model. The resulting PDF fitnesses were over 98.7 % for all participants, indicating that our simulated PDFs were in close agreement with human PDFs. Furthermore, the Kolmogorov&ndash Smirnov statistical hypothesis testing was applied to the resulting human&ndash bicycle fluctuation model, showing that the measured time responses were much better supported by our model than the Gaussian distribution. |
| Databáze: | OpenAIRE |
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