An AI Estimator of Electric Contract Capacity for CATV System Based on QNN Model

In this paper, an AI estimator of electric contract capacity for community antenna television system (CATV) based on quantum neural network (QNN) is proposed. This intelligent estimator not only can make CATV company have a good planning on the development of TV network system and power demand, but also can greatly reduce the company´s running cost. In this AI estimator, the neural model was used to execute the estimation of power demand. Due to the powerful learning capability of neural network, the nonlinear and complex relationships between power demand and its possible influencing factors could be automatically developed. Thus, such a well-trained neural model could be employed into the electricity demand estimation with high accuracy.