Hydrological Time Series Forecasting Model Based on Embedded Index

ZHOU Jin-yu; WAN Ding-sheng; XIAO Yan

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Hydrological Time Series Forecasting Model Based on Embedded Index

更新时间：2026-09-04

- Hydrological Time Series Forecasting Model Based on Embedded Index
- Vol. 35, Issue 1, Pages: 118-123(2018)
- 作者机构：
  
  河海大学计算机与信息学院,江苏,南京,211100
- 作者简介：
- 基金信息：
- DOI：
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- Published：2018
- 稿件说明：
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周金玉, 万定生, 肖艳. 基于嵌入式索引的水文时间序列预测模型[J]. 微电子学与计算机, 2018, 35(1): 118-123.

ZHOU Jin-yu, WAN Ding-sheng, XIAO Yan. Hydrological Time Series Forecasting Model Based on Embedded Index[J]. 2018, 35(1): 118-123.
周金玉, 万定生, 肖艳. 基于嵌入式索引的水文时间序列预测模型[J]. 微电子学与计算机, 2018, 35(1): 118-123. DOI：

ZHOU Jin-yu, WAN Ding-sheng, XIAO Yan. Hydrological Time Series Forecasting Model Based on Embedded Index[J]. 2018, 35(1): 118-123. DOI：

摘要

提出了基于嵌入式索引的相似性搜索和LM算法改进的双隐含层BP神经网络的水文时间序列预测模型.利用相似性搜索从大量的历史数据中挖掘出相似的信息

去除掉历史数据中的冗余和错误信息

从而减少训练集的数量

提高预测准确性.

Abstract

In this paper

we propose a hydrological time series forecasting model based onembedded index similarity search and LM algorithm improved BP neural network.The similarity search is used to mine the similar information from a large number of historical data

which can eliminate the redundancy and error information in the historical data

so as to reduce the number of training sets and improve the prediction accuracy.

关键词

Keywords

references

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