Evaluation algorithm of coastal city ecological civilization development level based on improved BP neural network.

Area of Science:

• Environmental Science
• Urban Planning
• Artificial Intelligence

Background:

• Ecological civilization is crucial for sustainable development in coastal urban areas.
• Accurate evaluation methods are needed to guide development strategies.
• Existing methods may not fully capture the complexities of ecological development in coastal cities.

Purpose of the Study:

• To develop and validate an improved BP neural network algorithm for evaluating ecological civilization in coastal cities.
• To construct a comprehensive evaluation index system for ecological civilization.
• To identify specific urban areas requiring enhanced ecological development.

Main Methods:

• An improved BP neural network model was developed for evaluation.
• An evaluation index system was constructed for coastal cities.
• Data from 30 Chinese cities were standardized and used as input.
• Entropy and coefficient of variation were employed for evaluation.
• The model underwent 5000 training iterations achieving high accuracy (near 10^-7).

Main Results:

• The algorithm successfully evaluated the ecological civilization development level of 30 Chinese coastal cities.
• Cities with low ecological civilization levels and limited per capita cultivated land were identified.
• The model demonstrated high precision and reliability in its assessments.

Conclusions:

• The improved BP neural network provides an effective tool for assessing coastal city ecological civilization.
• Identifying areas with ecological deficits allows for targeted interventions.
• The study offers actionable countermeasures and suggestions for enhancing ecological civilization in coastal urban environments.