使用带波形函数的Elman神经网络进行区域经济预测
Huade Liang1, Huilin Zeng1, Xiaojuan Dong1
1Guangzhou Nanyang Polytechnic College, Guangdong, China.
PloS one
|March 7, 2024
概括
本研究引入了一个带有波形函数的Elman神经网络,用于准确预测广东省的国内生产总值 (GDP). 该模型实现了高精度,超越竞争对手,并通过大数据集证明了效率.
科学领域:
- 经济学 经济学 经济学
- 人工智能的人工智能
- 时间序列分析时间序列分析
背景情况:
- 广东省领导中国经济,需要准确的国内生产总值 (GDP) 预测,以确保持续的高质量增长.
- 现有的预测模型可能缺乏动态区域经济分析所需的精度.
研究的目的:
- 开发和验证广东地区经济的新型预测模型.
- 用先进的计算技术提高经济预测的准确性和效率.
主要方法:
- 实现一个集成的Elman神经网络和用于GDP预测的波形函数.
- 与现有模型进行比较分析,以评估预测的准确性和精度.
- 评估模型的可扩展性和大数据集的性能.
主要成果:
- 提出的带有波形函数的Elman神经网络实现了0.971.97的预测准确度.
- 与竞争方法相比,该模型显示出更高的精度和更低的误差.
- 对教育的投资被认为是区域经济发展的重要积极推动力.
结论:
- 波形波段增强的Elman神经网络对于区域经济预测非常有效,可以适应各种场景.
- 该模型提供了更好的预测准确性和培训效率,特别是在大规模数据集.
- 波形函数提供了一种具有成本效益的方法,可以提高神经网络的性能,而不会增加架构复杂性.
相关概念视频
Econometric Views (EViews)
144
Econometric Views, often stylized as EViews, is a package that merges statistical analysis with econometric studies. It is designed to provide tools for time series analysis, forecasting, and econometric model simulation. The software originated from MicroTSP software and has evolved significantly since its inception in 1981. The history of EViews is marked by a continuous effort to enhance its computational speed and user interface. It was initially developed for large computing systems but...
144
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
54
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
54
End Point Prediction: Gran Plot
324
A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
For potentiometric titration, the Gran plot is created by plotting...
324


