基于SOM 网络的透析充分性指标评估模型的研究
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基于SOM 网络的透析充分性指标评估模型的研究
高臣杰1,2,张梅1,2
基金项目:高等学校博士学科点专项科研基金资助课题(200805611070);华南理工大学中央高校基本科研业务费(2009zm0273)
作者简介:高臣杰,(1986-),女,硕士研究生,模式识别与智能系统。
通信联系人:张梅,(1977-),女,副教授,数据信息处理、智能控制、机器人.
(1. 华南理工大学自动化科学与工程学院,广州 510640;2. 精密电子制造装备教育部工程研究中心,广州 510640)
摘要:针对腹膜透析治疗评价的主观性和不确定性,本研究提出了基于自组织映射(SOM)
神经网络的透析充分性指标评估模型。该模型基于SOM 的聚类理论,采用覆盖初始权值化方法,将众多专家对各项指标重要程度的打分矩阵聚类,每一类所对应的SOM 网络权重反映了本类专家对评价指标重要程度的综合权重。此方法不仅有效地减少了数据处理和分析的工作量,而且降低了主观因素对结论可能产生的影响。实验结果表明基于SOM 网络的评估模型是可靠的,具有一定的实用性。
关键词:神经网络;透析充分性;自组织映射(SOM);指标权重;评估
中图分类号:TP183;R459.5􀀀
Research of Dialysis Adequacy Index Evaluation Model Based on SOM
Gao Chenjie1,2, Zhang Mei1,2
(1. College of automatic science and engineering, South China University of Technology,GuangZhou 510640;2. Engineering Research Centre for Precision Electronic Manufacturing Equipments of Ministry, GuangZhou 510640)
Abstract: Based on self-organizing maps (SOM), this paper proposes a dialysis adequacy index evaluation model to deal with the subjectivity and uncertainty of the peritoneal dialysis evaluation. This model is based on SOM clustering theory and adopts a covering initialization theory to cluster the marking matrix given by experts where each cluster is corresponding to the
comprehensive weight about the evaluation index. This scheme not only efficiently reduces the load of data processing and analysis, but also decreases the influences caused by subjective factor.
Experimental results show that the dialysis adequacy index evaluation model based on SOM is reliable and effective.
Keywords: neural network; dialysis adequacy; self-organization map(SOM); the weight of dialysis adequacy index; evaluation