RBF Neural Network Prediction Modeling and Implementation

I need to develop MATLAB code to address RBF neural network prediction challenges. This project involves implementing RBF neural networks for forecasting applications using MATLAB's neural network toolkit. The implementation will focus on selecting optimal RBF network architectures, training methodologies, and applying the model for future data predictions. Key technical aspects include radial basis function center selection using k-means clustering, Gaussian activation functions implementation, and weight optimization through least squares methods. Using MATLAB's neural network functions like newrbe for exact design or newgrnn for generalized regression networks, I will configure hidden layer parameters and train the network with appropriate spread constants. The coding approach will involve data normalization, network training with iterative error minimization, and validation using mean squared error metrics. Through systematic MATLAB programming, I will develop a robust prediction model that handles nonlinear relationships in temporal data sequences.