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The Application of Combination Forecasting Method in Total Power of Agriculture Machinery Based on RS

机译：基于卢比的农业机械总功率组合预测方法在农业机械总能中的应用

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Forecast of agriculture machinery total power is a complicated non-linear system, combination forecasting can take full advantage of known information, to improve prediction accuracy. The relative data model between forecast objective and forecast model, and knowledge system and decision table was established respectively by means of converting continuous attribute values into discrete attribute values. Then, the weight of combination forecast model was calculated according to estimating dependence and significance of attributes in rough set theory, from this, then constructed the combination forecasting model and conducted combination forecasting agriculture machinery total power in Heilongjiang province. The results showed that the forecast average error of combination forecast model is 3.13, which is lower than 3.71, 5.25 and 3.63 of quadratic curve model, GM(1, 1) and cubic exponent smooth model, and is also lower than 3.34 and 3.26 of the combinatorial forecast model based on the divergence coefficient method and Shapley value method.
机译：农业机械预测总功率是一个复杂的非线性系统，组合预测可以充分利用已知信息，提高预测准确性。通过将连续属性值转换为离散属性值，分别建立了预测目标和预测模型和知识系统和决策表之间的相对数据模型。然后，根据粗糙集理论中属性的估计依赖性和意义来计算组合预测模型的权重，从而构建了黑龙江省联合预测模型和在黑龙江省进行的组合预测农业机械总权力。结果表明，组合预测模型的预测平均误差为3.13，高于二次曲线模型的3.71,5.25和3.63，GM（1,1）和立方指数平滑模型，也低于3.34和3.26基于发散系数法和福利价值法的组合预测模型。

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