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Background. Organic development is one of the evolutionary development models for cities, and it can facilitate cities to continually adapt to their surroundings and therefore adjust their development. Former research is mostly focused on cities and environmental changes, and research on the organic development of cities in various conditions is rather scarce. Purpose. By creating an evaluation index system for organic cities, this paper has established a multifactor evaluation model and improved the evaluation methodologies for organic cities. Methods. The authors have come up with a method that combines PCA and CNN, established an optimized model to calculate the organic cities, verified the accuracy of the evaluation index system for organic cities, and finally concluded that urban organic development is mostly associated with the aspects of the natural environment, economic basis, land use, and population scale of the city. Case Study. In addition, the examples of Bishan District, Chongqing, and Jiangyin, Jiangsu Province, are simulated and compared, and an accurate prediction for the organic development of small cities in China is given. Conclusion. The evaluation index system for organic cities devised by this paper can be applied effectively to evaluate the organic city of cities, and the neural network prediction model for organic cities designed by this paper can provide references for further research on organic cities.

A Study on the Small Organic Cities in China Combining PCA and CNN