Open AccessPreferred Parking Space Recommendation Method Based on Multi-attribute Decision-making Algorithm
Author(s) -
Chen Fei,
Xiaolin Li
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1972/1/012067
Subject(s) - weighting , arbitrariness , preference , parking space , space (punctuation) , computer science , process (computing) , algorithm , data mining , absolute deviation , analytic hierarchy process , mathematical optimization , artificial intelligence , machine learning , mathematics , operations research , statistics , transport engineering , engineering , medicine , philosophy , linguistics , radiology , operating system
Based on a large parking lot with a large number of parking spaces and different parking space attributes, combined with the attributes of free parking spaces and the driver’s preference factors when choosing parking spaces, a preferred parking space recommendation method based on a multi-attribute decision-making algorithm is proposed. In the decision-making process, a new weighting method is proposed to avoid the shortcomings of subjective arbitrariness and ignoring subjective preferences, while reducing the deviation between the combined weight and the subjective and objective weights. Finally, the absolute deviation method is used to verify the new weighting method, the effectiveness of the algorithm will also be verified through examples.