Application Practice of Fully Connected Neural Network Based on Nadam Optimizer for f-CaO Prediction in Cement Clinker
Abstract This article establishes a data-driven model for predicting f-CaO in clinker using a fully connected neural network based on the TensorFlow+Keras deep learning framework. The model is trained with the Nadam optimizer, showing better robustness compared to SGD (Stochastic Gradient Descent). Furthermore, this article introduces the implementation method for real-time prediction of f-CaO content … Read more