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中文摘要：
为副产品煤气容器水平和自备发电厂气体供应上的预言和调整的一个最佳的方法被建议。这个工作基于 Hodrick-Prescott 过滤器， Elman 神经网络和最少的广场支持向量机器抚养 HP-ENN-LSSVM 模特儿。根据预言，然后，最佳的调整过程由一个新奇推理方法来了在经济操作在安全地区和自备发电厂锅炉以内支撑煤气容器，并且也阻止相反的副产品气体排放和设备旅行。用实际生产数据的实验证明建议方法完成高精确的预言和最佳的副产品气体分发，它为副产品气体的合理安排提供显著指导。
英文摘要：
An optimal method for prediction and adjustment on byproduct gasholder level and self-provided power plant gas supply was proposed.This work raises the HP-ENN-LSSVM model based on the Hodrick-Prescott filter,Elman neural network and least squares support vector machines.Then,according to the prediction,the optimal adjustment process came up by a novel reasoning method to sustain the gasholder within safety zone and the self-provided power plant boilers in economic operation,and prevent unfavorable byproduct gas emission and equipment trip as well.The experiments using the practical production data show that the proposed method achieves high accurate predictions and the optimal byproduct gas distribution,which provides a remarkable guidance for reasonable scheduling of byproduct gas.
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