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The fierce competition in the commercial vehicle market is often determined by the changing customer demands, which in turn determines the market position and development direction of the enterprise. This paper proposes a commercial vehicle customer demand analysis method based on data mining technologies. By processing and analyzing customer data, the implicit customer demand characteristics are mined, a customer demand model is established to provide decision-making basis for enterprise customer demand analysis. This paper first introduces the importance and status quo of commercial vehicle customer demand analysis, then details the application of data mining technologies in customer demand analysis, including data preprocessing, data mining algorithm selection and customer demand model establishment. By processing and analyzing experimental data, this paper establishes a commercial vehicle customer demand model, verifies and optimizes the model. The experimental results show that the commercial vehicle customer demand analysis method proposed in this paper can accurately mine customer demand characteristics and provide more objective and scientific decision-making basis for enterprises. This method can be widely used in customer demand analysis and product design in the commercial vehicle market.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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