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| 基于修剪技术分级学习的动态模糊神经网络算法研究* | |
| 引用本文： | 张德丰,周灵,孙亚民,马子龙. 基于修剪技术分级学习的动态模糊神经网络算法研究*[J]. 计算机应用研究, 2011, 28(1): 124-126. DOI: 10.3969/j.issn.1001-3695.2011.01.034 |
| 作者姓名： | 张德丰 周灵 孙亚民 马子龙 |
| 作者单位： | 1. 佛山科学技术学院,计算机系,广东,佛山,528000 2. 南京理工大学,计算机科学与技术学院,南京,210094 3. 哈尔滨工业大学,电子工程系,哈尔滨,150001 |
| 基金项目： | 广东省自然科学基金资助项目（9151040701000002） |
| 摘 要： | 在D-FNN中采用了修剪技术，可以检测到不活跃的模糊规则并加以剔除，从而获得更为紧凑的结构。在D-FNN中，前提参数是在学习过程中自适应地进行调整。由于分级学习策略的应用，大大提高了学习的有效性，加之参数调整只限于线性参数，没有迭代学习，因而学习速度很快，这使得本算法应用于实时学习和控制成为可能。最后针对实际案例进行了仿真分析，验证了该算法的有效性和高效性。 |
| 关 键 词： | 动态模糊神经网络；修剪技术；模糊规则；分级学习 |
Research on graduation learning dynamic fuzzy neural network algorithm based on pruning technique |
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| ZHANG De-feng,ZHOU Ling,SUN Ya-min,MA Zi-long. Research on graduation learning dynamic fuzzy neural network algorithm based on pruning technique[J]. Application Research of Computers, 2011, 28(1): 124-126. DOI: 10.3969/j.issn.1001-3695.2011.01.034 | |
| Authors: | ZHANG De-feng ZHOU Ling SUN Ya-min MA Zi-long |
| Affiliation: | (1.Dept. of Computer Science, Foshan University, Foshan Guangdong 528000, China;2.School of Computer Science & Technology, Nanjing University of Science & Technology, Nanjing 210094, China;3.Dept. of Electrical Engineering, Harbin Institute of Technology, Harbin 150001, China) |
| Abstract: | Using a pruning technique can detect non-active fuzzy rules and to be eliminated and the availability of more compact structure in the D-FNN,in the premise parameters are in the process of adaptive learning to adjust. The way the application of learning strategies, greatly improved the effectiveness of learning.Combined with linear parameter,limited parameter adjustment,there was no iterative learning, and thus learning very fast,which made the algorithm used in real-time learning and control with the possi... |
| Keywords: | D-FNN pruning technology fuzzy rule graduation learning |
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