Fuzzy-Driven Optimization and Smart Evaluation of Ecological Environment Art Design

In the context of increasingly severe ecological and environmental problems, ecological and environmental art design must take into account both aesthetics and sustainable development. This paper constructs an ecological and environmental art design optimization and intelligent evaluation framework based on fuzzy algorithms, adopts a multi-objective optimization method based on fuzzy logic, and works together through fuzzy optimization, intelligent evaluation, and feedback correction modules. The experimental results show that in urban park design, the aesthetics of the fuzzy optimization model is improved from 0.45 to 0.85, the convergence speed is 280 iterations, and the running time is 12.5 seconds. It is superior to traditional algorithms in terms of multi-objective optimization accuracy. The study proves that the model can effectively deal with the uncertainty in the design, achieve multi-objective balanced optimization, and provide a new scientific method for ecological and environmental art design.