APPLICATION OF ARTIFICIAL NEURAL NETWORK METHOD IN DATA REDUCTION OF PROXIMATE ANALYSIS OF RAW COAL TO POWER PLANT

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APPLICATION OF ARTIFICIAL NEURAL NETWORK METHOD IN DATA REDUCTION OF PROXIMATE ANALYSIS OF RAW COAL TO POWER PLANT

Thermal Power Generation Issue 4, Pages: 9-11(2000)

更新时间：2025-09-28

- APPLICATION OF ARTIFICIAL NEURAL NETWORK METHOD IN DATA REDUCTION OF PROXIMATE ANALYSIS OF RAW COAL TO POWER PLANT
- 作者机构：
  
  广东省电力试验研究所,广州,510600
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP18
- Published：2000
- 稿件说明：
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APPLICATION OF ARTIFICIAL NEURAL NETWORK METHOD IN DATA REDUCTION OF PROXIMATE ANALYSIS OF RAW COAL TO POWER PLANT[J]. Thermal Power Generation, 2000, (4): 9-11.
DOI：

APPLICATION OF ARTIFICIAL NEURAL NETWORK METHOD IN DATA REDUCTION OF PROXIMATE ANALYSIS OF RAW COAL TO POWER PLANT[J]. Thermal Power Generation, 2000, (4): 9-11. DOI：

摘要

应用人工神经网络方法处理湛江电厂入厂煤煤质分析数据，其对发热量的预测值９５．５％在国家标准允许误差３００Ｊ／ｇ以内。人工神经网络成功地应用于电厂用煤发热量的预测，说明它能够表征煤的发热量与工业分析各组分间的非线性关系。

Abstract

An artificial neural network method is used in data reduction of raw coal proximate analysis for Zhanjiang Power Plant

by which the predicted caloric value of 95% raw coal is below the allowable deviation（300 J/g）of the national standards. It is consiered that this method could represent the nonlinear relationship between heating value and compositions of proximate analysis of raw coal to power plant.

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