A common problem in software faults prediction is the presence of noise in the data. Neural Networks are robust and have a good noise tolerance.
软件失效预测中的一个普遍的问题是数据中存在噪声，而神经网络具有鲁棒性并对噪声有很强的抑制能力。
As part of this effort, artificial neural networks, implemented in software are being combined with chemical sensor arrays and spectrometers for use in prototype electronic noses.
作为这种努力的一部分，将由软件来完成的人造神经网络与用于原型电子鼻中的化学传感器阵列和分光计结合在一起。
With ASPEN PLUS software, the paper simulates the quench system by neural networks, constructs the NN model to complete the simple simulation and calculation of the quench system.
以aspenPLUS软件为平台，用神经网络对急冷系统进行了严格模拟，建立了神经网络模型，可用于急冷系统简单的模拟计算。
The text proposed the temperature compensation with the artificial neural networks to it the software compensation technology.
提出和研究了用人工神经网络对其进行温度补偿的软件补偿技术。
Mainly it discusses two problems: software instruments of viscosity and flash point using neural networks and operation optimization on the atmospheric and vacuum towers using NLJ method.
主要探讨了两个方面的问题：采用神经网络建立各个侧线粘度和闪点的软测量仪表以及采用NLJ方法实现常减压塔的操作优化。
A practical developing software of neural network supporting many kinds of neural networks is designed. The software is general technical engineering people oriented and with graphic user interface.
设计了一种实用的面向普通工程技术人员，图形化用户界面，支持多种神经网络网型的神经网络开发软件。
It is friendly interface with the functions of editing, format transformation, data load, and so on. The software also supports parallel computing of BP algorithm in neural networks and FFT.
它不仅是一个友好的人机界面和具有编辑、格式转化、数据加载等多种功能，而且支持并行计算，如多层BP神经网络及FFT算法。
With parallel technology having become more matured, the neural networks' design process of hardware and software combination is getting more importance in these days.
随着并行技术的日益成熟，在并行集群上以软硬件相结合的方式设计神经网络的重要性也不断提高。
Completing projects in industry automation, computer software, motor control, micro controller application systems, fuzzy control, neural networks and control, and other advanced control techniques.
该系承担过多个工业自动化控制、计算机软件工程、单片机应用系统网络工程、大型灯光工程和音响工程方面的科研项目和实际工程项目。
Completing projects in industry automation, computer software, motor control, micro controller application systems, fuzzy control, neural networks and control, and other advanced control techniques.
该系承担过多个工业自动化控制、计算机软件工程、单片机应用系统网络工程、大型灯光工程和音响工程方面的科研项目和实际工程项目。
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