Optimizing Elevator Dispatching Strategy Based on Perceptron Algorithm
DOI: 10.23977/jaip.2022.050101 | Downloads: 11 | Views: 187
Wei Zhang 1, Ziyu Chen 1, Jiapeng Cai 1, Min Li 1, Yingying Li 1
1 Department of Electrical and Computer Engineering, Nanfang College, Guangzhou, 510900, China
Corresponding AuthorZiyu Chen
With the rapid development of high-rise buildings, the application of elevator is increasing day by day. In order to solve the problem of more reasonable and efficient operation of elevator in the peak of passenger flow, this paper identifies the characteristics of passenger flow by counting the number of up calls and down calls in a period of time, which provides a basis for the optimization of elevator scheduling and coordination control. In this thesis, the perceptron model in machine learning is used to realize the elevator traffic pattern recognition. Through the training of the existing data to construct the traffic pattern recognition model, and then through the recognition of the model to verify the test data, finally we can achieve the correct identification of the elevator traffic pattern.
KEYWORDSMachine learning, Perceptron, Pattern recognition
CITE THIS PAPER
Wei Zhang, Ziyu Chen, Jiapeng Cai, Min Li, Yingying Li, Optimizing Elevator Dispatching Strategy Based on Perceptron Algorithm. Journal of Artificial Intelligence Practice (2022) Vol. 5: 1-6. DOI: http://dx.doi.org/10.23977/jaip.2022.050101.
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