Model one was selected as the optimum model based on validation parameters which were found to be significant with correlation coefficient (R2) of 0.980921, adjusted correlation coefficient (R2 adj) value of 0.97547 and Cross validation coefficient (Q2cv) value of 0.965244.
In each hidden layer, number of neurons has been varied to determine the optimum model based on minimum value of RMSE.
In such cases, the optimum classification model based on LMNN is worth investigating for future study.
A mathematical model based on "competing processes" successfully predicts optimum voltage in individual patients.
Markov model based policies are not proven globally optimum for stationary Markovian workload.
Surprisingly, the model based on the baseline features converged to an optimum, possibly a local optimum in the first 30 iterations of the training, and reported a worthless performance when evaluating the testing set.
EM algorithm is a kind of the maximum likelihood estimation schemes that calculates local optimum parameters of a stochastic model based on given initial parameters.
In this study, a new model based on adaptive neuro-fuzzy inference system (ANFIS) for optimum well placement is proposed.
The development of an empirical scaled-Gaussian model based on the initial optimization data was then implemented to predict the optimum point for the system.
Develop a model based on theory.
