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EVALUATION ON VARIOUS FORECASTING MODELS USING ARTIFICIAL NEURAL NETWORKS (ANN)

机译:基于人工神经网络(ANN)的各种预测模型的评估

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摘要

Forecasting is the process of estimating or predicting the future. In recent years there is a widespread of interest in establishing a forecasting method that based on phenomenological description and computerized model. Various forecasting techniques have been developed using probabilistic, statistics, simulation or artificial intelligence. The focus of this paper is to review examples of forecasting model using Artificial Neural Networks (ANN). The accuracy of the models was also compared with Power Model. Box-Jenkins approach and Multiple Loglinear Regression. This paper also include a summary on various forecasting models using ANN. Through this study, it was found that forecasting model using ANN approach yield better results than other techniques.
机译:预测是估计或预测未来的过程。近年来,建立一种基于现象学描述和计算机模型的预测方法引起了广泛的兴趣。已经使用概率,统计,模拟或人工智能开发了各种预测技术。本文的重点是回顾使用人工神经网络(ANN)的预测模型的示例。模型的准确性也与功率模型进行了比较。 Box-Jenkins方法和多元对数线性回归。本文还总结了使用人工神经网络的各种预测模型。通过这项研究,发现使用ANN方法的预测模型比其他技术产生更好的结果。

著录项

  • 来源
    《》|2003年|p.291-299|共9页
  • 会议地点 Loughborough(GB)
  • 作者单位

    Faculty of Civil Engineering, Universiti Teknologi Malaysia, 81310 UTM Skudai, Johor, Malaysia;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 建筑科学;
  • 关键词

  • 入库时间 2022-08-26 13:56:35

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