首页> 外文会议>IEEE Conference on Computational Intelligence for Financial Engineering Economics >A new approach for time series prediction using ensembles of ANFIS models with interval type-2 and type-1 fuzzy integrators
【24h】

A new approach for time series prediction using ensembles of ANFIS models with interval type-2 and type-1 fuzzy integrators

机译:一种使用区间为2型和1型模糊积分器的ANFIS模型的集合进行时间序列预测的新方法

获取原文

摘要

This paper describes an architecture for Ensembles of ANFIS (adaptive network based fuzzy inference system), with integrators of type-1 FLS and interval type-2 FLS (Fuzzy Logic System), with emphasis on its application to the prediction of chaotic time series, where the goal is to minimize the prediction error. The time series that was considered is the Mackey-Glass. The methods used for the integration of the ensembles of ANFIS are: Integration by average, the integration by weighted average, integration by type-1 FLS and integration by interval type-2 FLS. The performance obtained with this architecture overcomes several standard statistical approaches and neural network models reported in the literature by various researchers. In the experiments we changed the type of membership functions and the desired goal error, thereby increasing the complexity of the training.
机译:本文介绍了一种ANFIS(基于自适应网络的模糊推理系统)集成的体系结构,其中集成了类型为1 FLS和间隔类型为2 FLS(模糊逻辑系统)的积分器,着重介绍了其在混沌时间序列预测中的应用,目标是最大程度地减少预测误差。所考虑的时间序列是Mackey-Glass。用于对ANFIS集合进行积分的方法有:平均积分,加权平均值积分,1型FLS积分和间隔2型FLS积分。通过这种架构获得的性能克服了各种研究人员在文献中报道的几种标准统计方法和神经网络模型。在实验中,我们更改了隶属函数的类型和所需的目标误差,从而增加了训练的复杂性。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

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