首页> 外国专利> A fuzzy-neural network system and a learning method therein

A fuzzy-neural network system and a learning method therein

机译:模糊神经网络系统及其学习方法

摘要

PURPOSE: To provide a fuzzy neural network device which is capable of obtaining an output value even for incomplete input data containing an unknown value in an input parameter and performing learning by using even incomplete learning data. ;CONSTITUTION: This device is provided with an input layer 1 outputting the value of an input parameter, membership layers 2 and 3 which is formed by dividing the ranges of the values which the input parameter can take, into plural areas defin the membership function of every area and outputs the membership value of each area in accordance with the output value from the input layer 1 for every input parameter, a rule layer 4 constructing a prescribed rule by the certain areas cooperating with each other between different input parameters and outputting the adaptability for the rule, an output layer 5 outputting the value of an output parameter in accordance with the output value from the rule layer 4 and a membership value setting means 6 setting the membership value corresponding to the unknown value to a prescribed value when a part of the input parameter has an unknown value.;COPYRIGHT: (C)1996,JPO
机译:目的:提供一种模糊神经网络设备,该设备即使对于输入参数中包含未知值的不完整输入数据也能够获得输出值,并且甚至可以使用不完整的学习数据进行学习。 ;组成:该设备具有输入层1和输出层3,该输入层1输出输入参数的值,隶属层2和3通过将输入参数可取的值的范围划分为多个区域来定义其隶属函数每个区域,并根据每个输入参数的输入层1的输出值,输出每个区域的隶属度值;规则层4通过在不同输入参数之间相互协作的特定区域构造规定规则,并输出适应性对于该规则,输出层5根据来自规则层4的输出值输出输出参数的值,并且隶属值设置装置6在当一部分被分配时将与未知值相对应的隶属值设置为规定值。输入参数的值未知。; COPYRIGHT:(C)1996,JPO

著录项

  • 公开/公告号EP0743604B1

    专利类型

  • 公开/公告日2000-06-21

    原文格式PDF

  • 申请/专利权人 SHARP KK;

    申请/专利号EP19960102112

  • 发明设计人 MATSUOKA TERUHIKO;ARAMAKI TAKASHI;

    申请日1996-02-13

  • 分类号G06F15/80;

  • 国家 EP

  • 入库时间 2022-08-22 01:48:47

相似文献

  • 专利
  • 外文文献
  • 中文文献
获取专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号