Prediction of elastic compressibility of rock material with soft computing techniques
The relevance vector machine is evaluated for estimation of rock compressibility based on physical properties. An iteration strategy is proposed to optimize the hyper-parameters of the relevance vector machine. The parameter effect is demonstrated on the performance of the relevance vector machine. The adaptive relevance vector machine is compared to the artificial neural networks and the support vector machine in the estimation.
soft computing relevance vector machine artificial neural network support vector machine mechanical parameter porous material