Institute of Physical Education, Ludong University, Yantai, Shandong 264025, China.
J Environ Public Health. 2022 Aug 25;2022:6486707. doi: 10.1155/2022/6486707. eCollection 2022.
In the process of volleyball players' mental health training, there exists the problem of low parameter accuracy. In order to further improve the accuracy of mental health training methods, based on artificial intelligence calculation, the neural network and long and short-term memory network were used to analyze the model. Estimation algorithm was used to describe the data, and finally, the optimization model was obtained to describe the feasibility study of mental health. In addition, the relevant data were used to verify and analyze the model. The research shows that in the time update curve, with the increase of the model state, the corresponding curve on the whole first presents a fluctuating trend of different degrees. The increase of model state will make the corresponding time value gradually tend to flat. The fluctuation of the corresponding time index is obvious. Indicators corresponding to the status update curve show an obvious linear change trend with the increase in time, and the overall linear characteristics are obvious. This shows that when time is constant, the relationship between the corresponding parameter and the state value conforms to the linear law. The corresponding state index gradually increases and eventually tends to be stable. Through the analysis, it can be seen that the proportion of different indicators under the effect of artificial intelligence and the calculation results are different. The parameters show an obvious linear variation trend, indicating that the corresponding model parameters can well reflect the data changes. Finally, the accuracy of the model is verified by the method of experimental comparison. The relevant research results can provide a new model and a method for volleyball players' mental health training.
在排球运动员心理健康训练的过程中，存在参数精度低的问题。为了进一步提高心理健康训练方法的准确性，基于人工智能计算，使用神经网络和长短时记忆网络对模型进行分析。使用估计算法来描述数据，最终获得优化模型，以描述心理健康的可行性研究。此外，使用相关数据对模型进行验证和分析。研究表明，在时间更新曲线上，随着模型状态的增加，相应的曲线整体上首先呈现出不同程度的波动趋势。模型状态的增加会使相应的时间值逐渐趋于平稳。相应时间指标的波动明显。与状态更新曲线对应的指标随着时间的增加呈现出明显的线性变化趋势，整体线性特征明显。这表明，在时间不变的情况下，相应参数与状态值之间的关系符合线性规律。相应的状态指标逐渐增加，最终趋于稳定。通过分析可以看出，人工智能作用下不同指标的比例和计算结果不同。参数呈现出明显的线性变化趋势，表明相应的模型参数能够很好地反映数据变化。最后，通过实验对比的方法验证了模型的准确性。相关研究结果可为排球运动员心理健康训练提供新的模型和方法。
