本文详细分析和研究了传统的优化理论、人工智能和神经网络在FMS优化控制中应用的适应性及各自的特点。
This paper surveys the application of classical optimization theory, artificial intelligent and neural network to FMS's control.
综述了人工神经网络在材料性能识别、预测及工艺优化方面应用的新进展，指出了存在的问题。
The new development of application of Artificial Neural Networks on materials properties prediction and process parameters optimization is reviewed. The existing problems are indicated.
通过本文的研究表明，将人工神经网络延伸应用于商品住宅价格的预测具有一定的可行性、可靠性及实用性。
Through the research of this paper it shows that artificial neural network (ANN) theory application in commodity housing price is not only feasible but also reliable and practical.
应用人工神经网络分别建立了震级与地表断裂长度及活断层长度的关系，一定程度上提高了由断裂或断层长度预测震级的可靠性。
In this paper, the Artificial Neural Networks are applied to construct separately the relationships between magnitude and surficial fracture length and between magnitude and active fault length.
本文分析了人工神经网络的特点及模型，以及其在普通硅酸铝纤维寿命预测中的应用。
In this paper, the characteristic and models of artificial neural networks are analyzed. The application of artificial neural networks in the lifespan forecast of ceramic fiber are also discussed.
首先介绍从信号幅度、相位、频率及功率谱等特性中提取的三种特征参数，应用这三种参数采用人工神经网络对模拟调制信号进行了识别。
Three features parameters derived from the instantaneous amplitude, instantaneous phase, instantaneous frequency and power spectrum of analogue modulated signals are presented in this article.
首先介绍从信号幅度、相位、频率及功率谱等特性中提取的三种特征参数，应用这三种参数采用人工神经网络对模拟调制信号进行了识别。
Three features parameters derived from the instantaneous amplitude, instantaneous phase, instantaneous frequency and power spectrum of analogue modulated signals are presented in this article.
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