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Smart city article details
| Title | Evaluation Of Low-Carbon Economic Development Level In Smart City Based On Ga-Bp Algorithm |
|---|---|
| ID_Doc | 24809 |
| Authors | Xu Z.; Li S.; Hong Y. |
| Year | 2021 |
| Published | Proceedings of 2021 8th IEEE International Conference on Behavioural and Social Computing, BESC 2021 |
| DOI | http://dx.doi.org/10.1109/BESC53957.2021.9635397 |
| Abstract | Aiming at the problem of poor convergence of GA-BP algorithm based on low carbon economy development level, this paper puts forward the evaluation method of low carbon economy development level. Estahllsh an index system including the main Influencing factors of smart city low-carbon economic development, normalize the index datal and analyze the development efficiency of low-carbon economy. The initial value and weight of BP neural network (BP) are optimized based on genetic algorithm (GA). The optimized BP neural network is used to obtain the optimal individual set through index Indtvtdual selection, crossover and mutation. It is used as the original weight and modified. The threshold is set to iteratively train the neural network, output the final result, and complete the evaluation of the development level of low-carbon economy in smart city. The experimental results show that the Mae values of the proposed method are only 0.102%, the evaluation accuracy is high, and the method can quickly complete the convergence, and the evaluation effect is good. © 2021 IEEE |
| Author Keywords | GA-BP algorithm; Low-carbon economy; Smart city |
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