This paper proposes a text classification method based on Cloud Theory and neural network structure decision tree.
提出一种基于云理论和神经网络构造决策树的文本分类方法。
Empirical results show that genetic programming model is more advantageous than traditional statistical models, neural network models and decision tree models in prediction accuracy and robustness.
检验结果表明，该模型在预测精度、实用价值和鲁棒性方面都优于传统的统计模型、神经网络模型和决策树模型。
It adopts cloud neural network to study the cloud mapping relationship between variables, so as to generate cloud decision tree.
运用云神经网络学习变量间的云映射关系，从中生成云决策树。
This paper presents a new method of text categorization based on the CHI value theory, RBF Neural Network and decision tree.
该文根据CH I值原理、基于R BF神经网络和决策树原理，提出了一种文本分类的新方法。
Aiming at a system with multi-dimensional output, the construction method of a tree - structure neural network is adopted, and its physical meaning is explained.
针对具有多维输出信息的系统，采用了一种树形神经网络的构造方法，并解释了其物理意义。
And based on the reliability theory, we use the fault tree to analyse and determine the equipment condition, and use BP neural network to diagnose equipment in condition-based maintenance.
并采用了基于可靠性理论的故障树思想对设备故障情况进行分析和判断，在设备状态检修的方式方法上采用了BP神经网络进行设备的故障状态诊断。
In this paper, a new approach is set forth that integrating both decision tree incremental learning and neural network global learning. Through theory analysis, it's indicated th…
为解决该问题，本文采用了决策树增量学习法和神经网络完全学习相结合的方法。
In this paper, a new approach is set forth that integrating both decision tree incremental learning and neural network global learning. Through theory analysis, it's indicated th…
为解决该问题，本文采用了决策树增量学习法和神经网络完全学习相结合的方法。
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