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造纸废水资源化利用的经济效益多指标度量算法 被引量:1

Multi Index Measurement Algorithm for Economic Benefits of Papermaking Wastewater Resource Utilization
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摘要 设计了造纸废水资源化利用的经济效益多指标度量算法。根据药剂消耗成本、电量消耗成本、人工成本,核算造纸废水资源化利用的经济成本效益。采用正态分布模型,拟合资源化利用经济效益数据的正态分布的概率密度函数,并基于直接经济效益与间接经济效益,构建废水资源化利用成本的动态回收效益度量函数。通过分析替代化肥与替代电力的资源化利用过程中气体排放情况,量化水资源化利用的环境社会经济效益指标。进一步,通过分析环境经济效益影响潜值、环境经济效益影响分数的变化趋势,实现经济效益的多指标度量。通过实验分析可知,在A~H等不同的环境下,J、Q的环境影响分数度量结果与实际结果完全一致,经济效益度量结果较为准确,对于提升造纸企业的经济性价值具有重要意义。 In this paper,a multi index economic benefit measurement algorithm for the resource utilization of papermaking wastewater was designed.Calculate the economic cost-effectiveness of the resource utilization of papermaking wastewater based on the consumption costs of chemicals,electricity,and labor.Using a normal distribution model,fit the probability density function of the normal distribution of economic benefits data for resource utilization,and establish a dynamic recovery benefit measurement function for wastewater resource utilization cost based on direct and indirect economic benefits.Analyze the gas emissions during the resource utilization process of replacing fertilizers and electricity,measure the environmental and social economic benefits indicators of water resource utilization,and achieve multi index measurement of economic benefits by analyzing the changes in the potential impact of environmental economic benefits and the impact score of environmental economic benefits.Through experimental analysis,it can be concluded that in different environments such as A~H,the environmental impact score measurement results of J and Q are completely consistent with the actual results,and the economic benefit measurement results are relatively accurate,which plays an important role in enhancing the economic value of papermaking enterprises.
作者 刘金鹿 王展 LIU Jinlu;WANG Zhan(Shaanxi Technical College of Finance&Economics,Xianyang 712000,China)
出处 《造纸科学与技术》 2025年第8期31-34,共4页 Paper Science And Technology
基金 陕西财经职业技术学院横向科研项目(2024HX12)。
关键词 造纸废水 资源化利用 多指标 度量算法 papermaking wastewater resource utilization multiple indicators measurement algorithm
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