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Site selection of LNG terminal based on cloud matter element model and principal component analysis

机译:基于云物质元模型和主成分分析的液化天然气接收站选址

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With the development of liquefied natural gas(LNG) port, as one of the crucial LNG port sitting process, the LNG terminal site’s condition assessment method has always received attention from experts, scholars concern more and more about the method’s practicality and reliability. In the traditional condition assessment method, due to the characteristics of the complex and extensive factors in the comprehensive assessment of the LNG terminal site, the assessment system is not comprehensive enough, or the assessment is too complex, the indexes are not easy to quantify, such problems are emerging. In view of the above reasons, the principal component analysis(PCA) method is used to transform the multi-indicators that affect the comparison of terminal sites into a few comprehensive indicators. A comprehensive evaluation model of the LNG terminal site based on cloud matter element theory and subjective and objective comprehensive weighting method was constructed. By the subjective and objective comprehensive weighting method, the comprehensive weight of each index is determined and the LNG terminal site comprehensive assessment standard cloud element model is constructed with the combination of cloud model and matter-element theory. The cloud matter-element correlation function is established to determine the degree of association between the matter element to be evaluated and the standard cloud matter element model. In order to eliminate random errors and improve the credibility of the results, the algorithm is used for multiple calculations and analysis to achieve the purpose of simultaneously giving the evaluation results and coefficients of credible degree. Finally, the reliability and rationality of the method are verified by an example.
机译:随着液化天然气(LNG)港口的发展,作为关键的LNG港口就座过程之一,LNG码头现场状态评估方法一直受到专家的关注,学者们对该方法的实用性和可靠性越来越关注。在传统的状态评估方法中,由于对LNG接收站进行综合评估的复杂性和广泛性的特点,评估体系不够全面,或者评估过于复杂,指标难以量化,这样的问题正在出现。鉴于上述原因,采用主成分分析(PCA)方法将影响终端站点比较的多指标转化为几个综合指标。基于云物元理论和主客观综合加权法,建立了LNG接收站综合评价模型。通过主客观综合加权方法,确定各项指标的综合权重,结合云模型和物元理论,构建了LNG接收站综合评价标准云元模型。建立云物质元素相关函数,以确定要评估的物质元素与标准云物质元素模型之间的关联度。为了消除随机误差,提高结果的可信度,该算法被用于多次计算和分析,以达到同时给出评估结果和可信度系数的目的。最后通过实例验证了该方法的可靠性和合理性。

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