PLS:绩效学习系统
“Performance Learning Systems”通常缩写为PLS,以方便日常书写和使用。这一术语在教育及社会相关领域中被广泛采用,其核心概念是指一套旨在提升学习成效和培训效率的系统化方法。其中文翻译为“绩效学习系统”,强调通过科学评估和优化流程来实现教育与培训目标。
Performance Learning Systems具体释义
Performance Learning Systems的英文发音
例句
- Feature selection is very important in improving the performance of learning systems.
- 在机器学习的研究中,特征选择对于提高学习机器的性能和效率具有重要的意义。
- Internal model control system based on neural networks has high performance of self learning and adaptation. It can realize the forecasting control to nonlinear and time delay systems, and it is superior to the traditional control method.
- 基于神经网络的内模控制系统具有很强的自学习性和自适应性,对大滞后、非线性系统可实现预测控制,较传统控制方式有明显的优势。
- According to the requirements of aeroengine performance control, a new neural network called auto-tuning neurons and gradient descent learning method are presented. A multivariable decoupling control algorithm based on the auto-tuning neurons is used for aeroengine multivariable control systems in this paper.
- 根据航空发动机性能控制要求,通过分析自调整神经元及最速下降学习方法,研究了基于自调整神经元的航空发动机多变量自适应解耦控制系统。
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