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Outline
To bridge the gap between AI technological breakthroughs and industrial value release in urban rail transit and foster new-quality productive forces as well as high-quality sustainable development, this paper studies AI implementation with the technical logic of "perception-decision-making-execution" and the connotation of new-quality productive forces, based on academic literature, patents and industry questionnaire data. It targets practical problems including fragmented AI implementation, lagging factor allocation and insufficient knowledge transformation, and puts forward a holistic AI implementation framework with three core innovations. The study concludes that a high-quality urban rail transit knowledge base is the top priority, data elements are the core of innovative factor allocation, and 1-to-N scenario expansion is the inevitable path for urban rail transit AI to translate technological breakthroughs into industrial value.
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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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