Restaurant Photovoltaic Environment Optimization and Clustering Method--based on PNN

In order to explore the impact of the restaurant dining environment on customer satisfaction, this paper conducts research on two aspects of restaurant decoration design and the indoor environment by processing measured data. In this paper, the canteen of XX University is taken as the research object, and specific indicators are determined according to the restaurant design and indoor environment. The indicators conduct the satisfaction questionnaire, and the results are presented in satisfaction values. Through fuzzy C-mean clustering (FCM) clustering results, probabilistic neural network (PNN) training data and verification numbers are selected. The results show that when the decoration colour is cheerful, the air temperature is 23°C, and the noise is below 60dB, the customer’s satisfaction is exemplary.