| 1. | Recognition of handwritten digital by using decision tree based on hiberarchy decomposition
基于层次分解决策树的手写体数字识别 |
| 2. | Hierarchical method : create a hierarchical decomposition of the set of data objects .
层次的方法：对给定数据对象集合进行层次分解。 |
| 3. | This paper uses the hierarchy analysis method to deal with multi - class problem by producing multi - level decision tree
本文采用基于层次分解的方法通过产生多层决策树来处理多类问题。 |
| 4. | In the skeleton decomposition and representation , an efficient skeleton decomposition and vectorization method is presented
在骨架分解和表示方面，论文提出了一种高效的骨架层次分解以及矢量化算法。 |
| 5. | Compared with the single decision tree , the decision tree based on hierarchy analysis has more advantages when dealing with the multi - class problem
与传统的单一决策树比较，基于层次分解的决策树在处理多类问题时有更多的优势。 |
| 6. | Based on weights analysis of feedforward neural networks , a hierarchic decomposition neural networks method for solving this problem is provided
基于前馈神经网络的权重分析，提出一种基于神经网络的结构优化层次分解方法，较好地解决了这一问题。 |
| 7. | For shape optimization of truss structure , the design variables are separated into two kinds of bar sectional size and nodal position by multilevel decomposition optimization method
对于桁架结构形状优化，应用层次分解优化方法，将设计变量分成杆件截面积和节点位置两类变量。 |
| 8. | Firstly , by the classification of customers , and the tree structure alike layered decomposition of customer demands , the problems of the transformation of customer demands is solved based on the thoughts and methods of qfd . the house of quality is reconstructed for the customer customization
通过对客户对象及其类别划分的研究，以及对客户需求的树形层次分解，用qfd的思想和方法，通过重构质量屋rhoq有效地解决了定制客户的需求转化问题。 |
| 9. | The implementation of decomposition optimization and the integration analysis of msc / nastran in optimization shorten the computing time of optimization , decrease the work intensity of designer and improve optimization efficiency greatly . furthermore , visualization is realized by setting the menu into patran
层次分解优化方法的实现和msc / nastran在优化中的集成分析，缩短了优化计算时间，降低了工程设计人员的工作强度，大大提高了优化设计效率。 |
| 10. | First find out the best combination for the multi - class problem through enumeration . then analyse and compare the result between id3 algorithm and hierarchy analysis algorithm from the rule number , the precondition number and the accuracy . at last point out the two algorithms " advantage and disadvantage so as to help us solve the multi - class problem better and establish theory basis for further research of decision tree based on hierarchy analysis
本文在visualc + +软件开发平台及id3算法的基础上，提出了基于层次分解思想的决策树，通过枚举法找出多类问题中的最优组合并加以分析，进而与id3算法产生的决策树从规则数、准确率等方面进行比较和分析，指出两者的优缺点，从而为解决类别较多的分类问题提供了有益的帮助，同时也为层次分解决策树的进一步研究奠定了理论基础。 |
