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科学、准确的化纤能耗预测对化纤行业的健康发展,乃至对整个国民经济的发展均有十分重要的意义.本文根据我国2001年～2011年对苯二甲酸(PTA)、己内酰胺(CPL)、己二酸(AA)、丙烯腈(AN)、浆粕(CP)的消费量和化纤行业能源消耗量的历史数据,利用PASW/SPSS Statistics软件建立多元线性回归和多层感知器神经网络模型.2种模型预测结果均显示,至2015年,化纤行业吨产品能耗将比2010年下降25%以上,化纤行业能源消耗在1 750万吨标煤以下.
Scientific and accurate predictions of chemical fiber energy consumption are of great significance to the healthy development of the chemical fiber industry and even to the development of the entire national economy. According to the statistics of China’s PTA, CPL, (AA), acrylonitrile (AN), pulp (CP) consumption and chemical industry energy consumption history data, the use of PASW / SPSS Statistics software to establish multiple linear regression and multilayer perceptron neural network model. The forecast results of the two models show that by 2015, the energy consumption per ton of chemical fiber products in the chemical industry will drop by 25% or more compared with that in 2010, and the chemical fiber industry will consume less than 17.5 million tons of standard coal.