Applying rough sets theory to production scheduling solves the difficult problem of rules discovery for production scheduling through the successful schedule rules found in history data.
把变精度粗集应用于生产调度中，在历史调度数据中发现成功的调度规则解决了生产调度中的规则获取难题。
Finally, the SVR model is used to predict multiple sets of data. And the predicted parameters values are loaded to reservoir model and are compared with actual historical production data.
最后，运用该模型对多组实际测试数据进行预测，并把预测所得到参数值反馈给油藏模型，将模拟产生的生产数据与油藏历史生产数据相比较。
However, in most case, it can meet production requirements without large data sets for a specific application.
然而，在大多数情况下，对一个具体应用来说，并不需要如此庞大的数据就能满足生产方面的要求。
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