提出一种基于过程神经网络的木材生长轮密度长期预测方法。
A long-term forecast method of timber growth ring density based on process neural network was proposed in this paper.
应用表明，算法简化了过程神经网络的计算复杂度，提高了网络学习效率和对实际问题求解的适应性。
The application shows that the algorithms simplify the computing complexity of process neural networks, and raise the efficiency of the network learning and the adaptability to real problem resolving.
仿真结果表明，该系统响应快，无超调，比传统的加工过程神经网络自适应控制具有更好的控制效果。
Simulation results show that the designed system is of fast response, non-overshoot and it is more effective than the conventional adaptive control of machining process based on neural network.
该文在考虑过程神经网络对时间聚合运算的复杂性的基础上，提出了一种基于函数正交基展开的学习算法。
In consideration of the complexity of the aggregation operation of time in process neural networks, a new learning algorithm based on function orthogonal basis expansion is proposed.
针对输入和输出均为时变函数或过程的实际系统建模和仿真问题，提出一种输入和输出均为时变函数的反馈过程神经网络模型。
In order to model and simulate systems with time-varying functions or processes, a feedback process neural network model with time-varying input and output functions is proposed.
针对复杂钢坯加热过程，提出了一种免疫克隆进化模糊神经网络（ICE-FNN）控制算法。首先根据现场样本数据建立过程神经网络模型；
The immune clone evolutionary(ICE) algorithm is presented to optimize the parameters of the fuzzy neural network(FNN) controller for the complex billet heating process.
而今我们有了电脑病毒，神经网络，生物圈二号，基因治疗法以及智能卡——所有这些人工构造的产品，联接起了机械与生物过程。
We now have computer viruses, neural networks, Biosphere 2, gene therapy, and smart CARDS — all humanly constructed artifacts that bind mechanical and biological processes.
在培训过程中，神经网络输入。
人工神经网络技术在冶金过程终点预报应用方面具有广阔的应用前景。
There is the better application prospect for the application of artificial neural network in end-point prediction for the whole ferrous metallurgy process.
动态图形模拟器是从属于集成环境，并受之驱动的专用模拟器，它实现了神经网络动态变化过程的模拟。
The dynamic graphical simulator which realizes the dynamic procedure simulation of artificial neural network is driven by and belongs to this environment.
作为神经网络控制的基本单元，采用不同学习规则的神经元控制器，对神经元的学习过程将产生不同的影响。
As the basic unit of Neural Network, Neural Controllers with different learning rules will result in different control effects for the learning process of synaptic weights.
为表达过程时变的特点，引入时间参数作为神经网络的一个输入量。
The time parameter is also imported into the neural network to give the time-varying characteristic of the process.
为了实现过程状态模型的智能输出，运用人工神经网络实现自动推理的功能；
In order to achieve intelligent process state model output, the use of artificial neural networks for automatic reasoning capabilities.
为模拟这一过程，开发了压裂设计神经网络专家系统。
For this, nerve network expert system is developed for fracturing design to simulate this process.
在控制过程中CMAC神经网络控制器经过不断学习，最终在控制系统中发挥主要控制作用。
During the control process after the unceasing learning of CMAC neural network controller, this controller would finally play main role in the control system.
探讨了故障预报技术的应用及其数值预测方法，给出了神经网络模型在预测过程中的算法。
The fault forecasting technique and the numerical forecasting method are studied. An algorithm is given for the neural network in the course of forecasting.
硝酸生产过程优化问题的建模采用人工神经网络完成。
The nitric acid production process optimization question modeling uses the artificial neural network to complete.
针对丙酮精制过程的特点，提出一种基于神经网络的丙酮产品质量分类挖掘方法。
Considering the features of acetone refining process, a strategy of neural network based data mining for product quality classification is proposed.
通过对控制系统的过程模拟，提出一种模糊神经网络最优控制方案。
An optimal control scheme based on fuzzy neural network is proposed through simulating the process of the control system.
在这个过程中，应用了决策树归纳学习的优化原则，使得生成的决策树能最简洁、准确地描述神经网络学到的知识。
In the process of constructing tree, three optimization principles are adopted to concisely and accurately describe the knowledge that the networks have learned.
在电热镦粗过程中，采用神经网络和虚拟仪器相结合的方式，创建了加热电流预报的虚拟仪器。
Taking the course of the electric upsetting as an example, combining Neural Network with virtual instrument, we has put forward a virtual instrument about prediction of heating current.
针对传统神经网络用于复杂过程系统的控制时难于收敛的问题，文章提出了基于混合建模的模块化的神经网络模型。
Against difficult convergence problem when the traditional neural networks are applied to complex process system, a hybrid expert neural networks model is brought forward.
然后给出了一个具体的拟合算法实例，探讨了神经网络参数对于学习过程及拟合结果的影响；
Then, an example of the fitting arithmetic is given, and the infection by the neural network parameter on the fitting result is researched.
根据该理论，学习过程就是由随机信息源产生的输入信号驱动神经网络参数不断修改的过程；
The learning process of a neural network is considered the process in which neural network variables are changed with a time series of input signals generated from a stochastic information source.
最后，介绍了多层神经网络模型在丝杠螺纹磨削过程的预测与控制中的应用。
The application of multi-layer neural networks in the prediction and control of lead-screw grinding is discussed.
在神经网络自学习过程中，引入了自适应学习速率和误差批处理法，加快了学习速度。
In the training process, the adaptive learning rate and error batch-mode process are introduced to accelerate the training rate.
本文研究了连续神经网络在学习过程中结构摄动情况下网络的动态特性。
In this paper, the dynamic behaviors of continuous neural networks under structural variations in learning process are studied.
本文研究了连续神经网络在学习过程中结构摄动情况下网络的动态特性。
In this paper, the dynamic behaviors of continuous neural networks under structural variations in learning process are studied.
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