A Quantum Genetic SVM-based Model for Predicting Daily Circulation Visits to Senior Public Service Facilities

A Quantum Genetic SVM-based Model for Predicting Daily Circulation Visits to Senior Public Service Facilities. The model takes the senior public service facilities in Nankai District, Tianjin City, as a data example, and after examining various influencing factors, a number of quantitative feature data as input and the daily circulation of senior public service facilities as output target, on which the prediction model is successfully trained and obtained. The experiments show that under the guiding principle of constructing the prediction system with the whole close to the actual target, the corresponding short-term prediction system established by this method achieves better prediction effect, and the application of the system will effectively enhance the wisdom service level of the senior public service facilities.