A GMDH-type neural network with multi-filter feature selection for the prediction of transition temperatures of bent-core liquid crystals

Abstract

The QSPR study on transition temperatures of five-ring bent-core LCs was performed using GMDH-type neural networks. A novel multi-filter approach, which combines chi square ranking, v-WSH and GMDH algorithm was used for the selection of descriptors.