CP-activated WASD neuronet approach to Asian population prediction with abundant experimental verification

Data fitting and prediction are important in many domains. As computing power improves, artificial intelligence fitting methods such as the WASD (weights and structure-determination) neuronet become more operable. Although the WASD neuronet has been applied to several other issues, its application on fitting data needs to be explored and discussed more specifically. This paper is committed to introducing the WASD-neuronet model activated by Chebyshev polynomials of class 1 for data fitting and to exploring its capability of data prediction. The learning–checking method and the concept of global minimum point are introduced to improve the prediction performance and extend the application of the WASD-neuronet model. Applying such a model to Asian population prediction substantiates its excellent performance. With numerical experiments validating the predicting performance and a final prediction based on historical data, this paper presents a reasonable tendency of Asian population.