The first excited 2⁺ energy states of nuclei give much substantial information related to the nuclear structure. All excited states of nuclei are shown regularities in spin, parity, and energy, including these levels. In the even–even nuclei, the first excited state is generally 2⁺, and the energy values of them increase as the closed shells are approached. The nuclei’s excited levels can be investigated using theoretical nuclear models, such as the nuclear shell model. In the present study, we have used artificial neural networks to determine the energies of the first 2⁺ states in the even–even nuclei in the nuclidic chart as a function of Z and N numbers for the first time. According to the results, the method is convenient for this goal. One can confidently use the method for predicting the first 2⁺ state energy values whose experimental values do not exist in the literature.

原子核的第一个激发2 ⁺能态给出了许多与核结构有关的重要信息。核的所有激发态都显示出自旋，奇偶校验和能量的规律性，包括这些能级。在偶-偶核中，第一个激发态通常为2 ⁺，并且随着接近封闭壳层，它们的能量值增加。可以使用理论核模型（例如核壳模型）研究核的激发能级。在本研究中，我们已使用人工神经网络确定Z值和N值在核图中偶偶核中前2 ⁺个态的能量。第一次的数字。根据结果​​，该方法对于实现该目标是方便的。可以放心地使用该方法预测文献中不存在实验值的前2 ⁺状态能值。