MULTIPLE LINEAR REGRESSION-ARTIFICIAL NEURON NETWORK MIXED MODEL, PREDICTING GENERATING ENERGY OF IDEAL GAS OF A PURE ORGANIC COMPOUND, CAPABLE OF FORMING AN ANN OUTPUTTING A STANDARD STATE ABSOLUTE ENTROPY BY RECEIVING A MOLECULAR DESCRIPTOR INCLUDED IN AN OPTIMUM MLRM

摘要

PURPOSE: A MLR(Multiple Linear Regression)-ANN(Artificial Neuron Network) mixed model, predicting generating energy of ideal gas of a pure organic compound, is provided to receive a molecular descriptor included in an optimum MLRM(Multiple Linear Regression Model) in order to form an ANN outputting a standard state absolute entropy, thereby improving prediction performance.;CONSTITUTION: Optimum molecule descriptors are extracted for an experimental data set. Experimental data is separated into a training set and a test set. An optimum MLRM for the training set is explored. If test performance about the test set satisfies standards, the optimum MLRM is decided. The optimum MLRM obtains a generating energy value of ideal gas through the explored MLRM for the experimental data set.;COPYRIGHT KIPO 2012