STUDY ON CHARACTERISTICS OF WASTE GASIFICATION BASED ON GREY RELATION ANALYSIS AND BP NEURAL NETWORK

LI Yan-ji1; LI Run-dong1; LI Ai-min2; ZHU Hong-zhen3; FENG Lei1; LIU Yao-xin11.Shenyang Institute of Aeronautical Engineering

doi:10.19666/j.rlfd.2008.05.004

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STUDY ON CHARACTERISTICS OF WASTE GASIFICATION BASED ON GREY RELATION ANALYSIS AND BP NEURAL NETWORK

更新时间：2025-09-28

- STUDY ON CHARACTERISTICS OF WASTE GASIFICATION BASED ON GREY RELATION ANALYSIS AND BP NEURAL NETWORK
- Thermal Power Generation Issue 5, Pages: 16-20(2008)
- 作者机构：
  
  1. 沈阳航空工业学院
  2. 大连理工大学
  3. 沈阳化工学院
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.2008.05.004
  CLC： X705
- Published：2008
- 稿件说明：
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LI Yan-ji1, LI Run-dong1, LI Ai-min2, et al. STUDY ON CHARACTERISTICS OF WASTE GASIFICATION BASED ON GREY RELATION ANALYSIS AND BP NEURAL NETWORK[J]. Thermal power generation, 2008, (5): 16-20.
DOI：

LI Yan-ji1, LI Run-dong1, LI Ai-min2, et al. STUDY ON CHARACTERISTICS OF WASTE GASIFICATION BASED ON GREY RELATION ANALYSIS AND BP NEURAL NETWORK[J]. Thermal power generation, 2008, (5): 16-20. DOI： 10.19666/j.rlfd.2008.05.004.

摘要

使用灰色关联分析

发现气化温度、物料特性(主要是挥发分和固定碳)和气化剂流量是影响有机固体废弃物气化产气组成和可燃气含量的主要因素

给出了影响因素对参考因素影响程度。采用3层改进BP神经网络建立了废弃物气化产气组分含量和产气热值的预测模型

模型预测与实测结果的最大相对误差分别为11%和2.8%

证明网络的预测效果较好。

Abstract

The grey relationship knowledge has been used in the study

it is discovered that the main factors affecting the produced gas composition and combustible gas content from organic solid waste gasification are the gasification temperature

the materials' property(mostly means volatile matter and fixed carbon)

and the flow rate of oxidant

the affecting degree of said factors upon reference factors being given.A prediction model for composition content and calorific value of the produced gas has been established by using three-layer perfection of the BP neural network.The maximal relative error between model prediction and the measured result is 11% and 2.0% respectively

proving that the prediction effect of the said network is better.

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