用过渡金属元素的原子半径、价电子数、主量子数、d电子数和f电子数等为人工神经网络的输入值，用已知的二元连续固溶系相图液相线和固相线的实测数据为输出值训练人工神经网络．并用其对未知二元连续固溶系的液相线和固相线进行计算机预报．若干二元系计算结果与实测结果相当接近．
Using the atomic radii, principle quantum number of valance shells, the number of d-electrons and f-electrons as the inputs of artificial neural network and trained by known data of liquidus and solidus curves, the liquidus or solidus curves of the binary alloy systems of transition metals with continuous solid solutions can be predicted correctly.
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