This paper presents an adaptive congestion control model in ATM networks at the user to network interface by using a diagonal recurrent neural network (DRNN) as an predictor.
提出一种在用户-网络接口处利用对角递归神经网络(DRNN)作为自适应预测器，实现AT M网络自适应拥塞控制的模型。
Based on the multiuser OFDM system model and the user fairness, this paper designed the objective function of the adaptive resource allocation problem.
通过对多用户OFDM系统模型的分析，结合对用户公平性的考虑，给出了该系统中自适应资源分配问题的目标函数。
PITA model supports dialogue independence, adaptive interfaces, application portability, controlled task and give user immediate feedback.
PITA模型支持对话独立性、界面自适应、应用的可移植性、任务的可控制性并能给用户及时的反馈。
The paper presents a framework of intelligent data mining based on the layer model. It consists of multi-layers of concepts, problem identifying lay er, task layer, adaptive layer and user layer.
在层次模型的基础上，提出了一个智能数据挖掘的开发框架，包括问题识别层、任务层、应用层和用户层等多层概念。
The paper presents a framework of intelligent data mining based on the layer model. It consists of multi-layers of concepts, problem identifying lay er, task layer, adaptive layer and user layer.
在层次模型的基础上，提出了一个智能数据挖掘的开发框架，包括问题识别层、任务层、应用层和用户层等多层概念。
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