将学习矢量量化神经网络集成在基于实例推理的故障诊断方法中，减小了实例搜索空间，提高了实例检索效率。
The learning vector quantization neural network has been integrated successfully with the case-based reasoning approach to reduce the case indexing space and to enhance the indexing efficiency.
针对基于实例的产品方案设计问题，提出了一种半自动的、具有自学习功能的实例修改策略。
Aiming at the problem of case-based preliminary product design, this paper presents a semi-automatic case revisal strategy that has a self-learning capability.
仍然有些算法很容易就可以被归入好几个类别，好比学习矢量量化，它既是受启发于神经网络的方法，又是基于实例的方法。
There are still algorithms that could just as easily fit into multiple categories like Learning Vector Quantization that is both a neural network inspired method and an instance-based method.
文中探讨了一种用于提取模糊规则的RBF神经网络结构，提出了基于此网路结构的模糊隶属度函数学习算法，最后给出了用于验证该算法有效性的仿真实例。
The learning algorithm of membership function based on the RBF Neural Network is discussed and an example is given to demonstrate the validity of this algorithm.
本文阐述了网格技术的概念及其体系结构，提出了教育网格系统的构成，最后讨论了一个基于网格技术的远程教学实例———远程沉浸学习。
In this paper, we discuss the grid technology concept and its system structure, and put forward the constitution of education grid system.
本文阐述了网格技术的概念及体系结构，提出了教育网格系统的构成，最后讨论了一个基于网格技术的远程教学实例——远程沉浸学习。
In this paper, we discuss the concept of grid technology and its system structure, and put forward the constitution of education grid system.
实验数据表明，基于机器学习的编译自动调优技术对已知实例能得到比手工调优更好的性能，而对未知实例的预测能力也能达到跟手工调优接近的水平。
The experimental results show that, automatic compiler tuning can get better performance than the manual tuning in the training cases and in the new cases, they get close performance.
实验数据表明，基于机器学习的编译自动调优技术对已知实例能得到比手工调优更好的性能，而对未知实例的预测能力也能达到跟手工调优接近的水平。
The experimental results show that, automatic compiler tuning can get better performance than the manual tuning in the training cases and in the new cases, they get close performance.
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