煤发热量

以格林函数为激活函数的RBF网络是通用逼近器，它可以逼近任意多元连续函数，具有处理非线性关系的强大潜能，可以快速、准确地预测煤发热量。

The RBF Network with the Green function as the active function is a universal approximator in that it can approximate arbitrarily well any multivariate continuous function . It has the potential of dealing with the nonlinear relationship and can forecast the calorific value of coal quickly and exactly .

通过采用恒温式热量计测定煤发热量的试验，得出影响测定结果准确度的主要因素是热容量、内筒中的水量、室温与外筒间温差的结论。

Though the experiment determining calorific value of coal by constant temperature calorimeter , it comes to the conclusion that there are three main factors influencing accuracy , the thermal capacity , water capacity in the inner-canister , temperature difference between the room and the outer-canister .

基于MATLAB的煤发热量计算

Calculation of Calorific Value of Coal Based on MATLAB

利用EXCEL进行煤发热量的快速回归分析

Using EXCEL Method to Make Regression Analysis of Coal Calorific Power

该项目主要是按用户要求，根据LED单管的发光亮度和波长对LED进行分选，从而提高LED单管亮度和波长的一致性，进而提高LED产品的质量和档次。带微计算机的煤发热量测量仪

The research task achieves on-line measurement of LED 's wavelength and light intensity and also including automatic separation of LED according to user 's request in order to improve the quality of LED . A Microprocessor-Based Calorimeter for Measuring the Heat Output of the Coals

带微计算机的煤发热量测量仪

A Microprocessor-Based Calorimeter for Measuring the Heat Output of the Coals

煤发热量测量不确定度评定的探讨

The Measurement Uncertainty in Determination of Calorific Value of Coal

煤发热量计算的基准统一问题

Calculation of Coal 's Calorific Value on Same Basis

杏花矿洗混煤发热量回归方程的建立带微计算机的煤发热量测量仪

Establishment of Tropic Equation for the Quality of Heat of Washed-coal in Xinghua Coal Mine

西山煤发热量与工业分析指标的相关性和回归方程

Regression Equation on the Correlativity Between Calorific Value and Approximate Analysis Indexes of Xishan Coal

分析了煤发热量与工业分析指标之间的相关性，建立了数学模型。

A mathematics model are established after analyzing the correlativity between calorific value and indexes of approximate analysis .

同时，本文也给出了在没有任何工业参数已知的情况下通过建立BP神经网络计算煤种发热量的方法。

At the same time , the method is given which is used to calculate the heat of coal by building BP Neural Networks although the technological parameters are unknown .

仿真结果表明，该辨识方法的辨识误差在1.5%以内，具有良好的辨识精度，在速度上也优于单独的RBF辨识算法，可以应用于热力系统煤种发热量在线辨识。

Simulation results show that the identification error is within 1.5 % , which is sufficient for coal combustion systems . Also , the method is faster than a simple radial basis fuction network so it can be applied to online coal LHV identification for combustion systems .

水煤浆发热量测定方法的研究

Study on the Heating Value Determination Method of Coal Water Slurry

入炉煤低位发热量变化对机组经济性的影响

Effect of changing of coal low heat value on economy of generating unit

经验公式对全国煤实测发热量的检验

Identifying and appraising of coal calorific experience formula

三煤种配煤发热量的分析研究

Analytical Study of Heat Quantity of Three-type-coal Combination

煤应用基低位发热量回归方程的推导

Deduce of Regression Equation for Applied Lower Calorific Value

煤的弹筒发热量不确定度的评定

Evaluation on Indeterminacy of Bomb Calorific Value for Coal

电站锅炉入炉煤元素分析和发热量的软测量实时监测技术

Real time identification technique for ultimate analysis and calorific value of burning coal in Utility Boiler

通过锅炉本体以及空气预热器的能量平衡分析，采用灰分校正技术，实现了入炉煤元素分析和发热量的实时监测。

Checks ash content of coal using energy balance of boiler and air preheater ; and consequently realizes the real time monitoring of ultimate analysis and net calorific value of the coal .

本文采用BP神经网络描述混煤与单煤特性之间的关系，建立了混煤发热量、挥发分、灰分、硫分和灰熔点的预测模型。

In this thesis , back-propagation ( BP ) neural network is adopted to determine the relations between qualities of the blended coal and its components . Models are established for predicting blended coal 's heating value , volatile content , ash content , sulfur content and ash melting point .