Abstract: A material design support apparatus for supporting optimization of a design condition for a material, the material design support apparatus including: a design condition setting unit configured to set a range of a design condition for a material; a required characteristic setting unit configured to set a range of a required characteristic of the material; an exhaustive prediction point generation unit configured to generate a plurality of exhaustive prediction points within the range of the design condition; a prediction unit configured to input the exhaustive prediction points into a trained model in which a correspondence between a design condition for the material and a characteristic value of the material is learned, thereby to predict a characteristic value of the material; and a design condition adjustment unit configured to adjust a range of the design condition for the material in which a plurality of exhaustive prediction points are subsequently generated.

Abstract: Model setting step sets a trained model acquired by machine learning of a correspondence relationship between an explanatory variable including information related to a material composition or a manufacturing condition of a target material, and an objective variable including information related to the material characteristics of the target material, and prediction step inputs an explanatory variable related to a target material whose material characteristics is to be predicted to the trained model set in the model setting step, and outputs an objective variable related to information of the explanatory variable, so as to predict the material characteristics of the target material to be predicted based on the objective variable.

Abstract: Model setting step sets a trained model acquired by machine learning of a correspondence relationship between an explanatory variable including information related to a material composition or a manufacturing condition of a target material, and an objective variable including information related to the material characteristics of the target material, and prediction step inputs an explanatory variable related to a target material whose material characteristics is to be predicted to the trained model set in the model setting step, and outputs an objective variable related to information of the explanatory variable, so as to predict the material characteristics of the target material to be predicted based on the objective variable.