Drivability evaluation model using principal component analysis and optimized extreme learning machine
| Autor: | Yi Fei Ma, Wei Huang, Hai Jiang Liu |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Computer science Mechanical Engineering media_common.quotation_subject Aerospace Engineering Particle swarm optimization 02 engineering and technology Reliability engineering 020901 industrial engineering & automation Mechanics of Materials Control system Automotive Engineering Principal component analysis Evaluation methods 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing General Materials Science Quality (business) Extreme learning machine media_common |
| Zdroj: | Journal of Vibration and Control. 25:2274-2281 |
| ISSN: | 1741-2986 1077-5463 |
| DOI: | 10.1177/1077546319852487 |
| Popis: | The accuracy of the evaluation method is essential to optimize the control system and improve a vehicle’s drivability quality. This study aimed at exploring a more effective drivability evaluation method and a drivability evaluation model was proposed on the basis of principal component analysis and optimization of an extreme learning machine. The drivability evaluation model was built using an extreme learning machine. The input of the model was determined by the principal component analysis method, and the optimal number of neurons in the hidden layer of the drivability evaluation model was obtained by a particle swarm optimization algorithm. The experimental results show that considering the evaluation index coupling factors can improve the prediction accuracy of the evaluation model. The R correlation between the score predicted by the drivability evaluation model proposed in this paper and the actual score reached 0.979, and the predicted pass rate also reached 95%, which indicate the model was more accurate and stable than others. The evaluation model can be extended to fuel economy and handling stability. It also has theoretical guidance and application value in practical problems. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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