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在以回采工作面为基本单元对煤炭资源条件定量评价的基础上，借助S曲线确定了时间因素对煤炭开采成本、售价等经济指标的影响，采用模糊数学、人工神经元网络、稳健回归等多种方法建立了开采指标与资源条件间的关系模型，实现了开采指标的实时、动态预测.对测算煤炭资源资产价值与级差收益的理论、方法与模型进行了探讨.运用VB开发了整个评价预测系统，实现了评价、预测和决策一体化、动态化与实时化，并通过实例说明了该系统的应用.
Based on the quantitative evaluation of the coal resource conditions with the mining face as the basic unit, the influence of time factor on the economic indicators such as coal mining cost and selling price was determined by means of the S curve. Fuzzy mathematics, artificial neural network, Regression and other methods to establish the relationship between mining indicators and resource conditions model to achieve a real-time prediction of mining indicators.Calculation of coal resources, asset value and differential income theory, methods and models were discussed using VB developed The whole evaluation and prediction system realizes the integration, dynamic and real-time evaluation, prediction and decision-making, and illustrates the application of the system through examples.