当前位置: X-MOL 学术Inf. Process. Manag. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Information representation of blockchain technology: Risk evaluation of investment by personalized quantifier with cubic spline interpolation
Information Processing & Management ( IF 8.6 ) Pub Date : 2021-03-15 , DOI: 10.1016/j.ipm.2021.102571
Zhi Wen , Huchang Liao , Ali Emrouznejad

With the applications of blockchain technology in various fields, the research on blockchain has attracted much attention. Different from the researches focusing on specific applications of blockchain technology in a certain field, this study devotes to capturing the attitudes of investors regarding different risk criteria in blockchain technology investment decision making. We use personalized quantifiers to extract investors’ preferences on each risk evaluation criterion. At present, the personalized quantifier that can reflect individual attitudes and behavior intentions have been fitted by various functions, but there are still limitations. In this regard, this paper introduces a cubic spline interpolation function to fit the personalized quantifier, and addresses the consistency of the personalized quantifier in the ordered weighted averaging aggregation. Moreover, we employ a qualitative information representation model called probabilistic linguistic term sets to express decision-makers' evaluations on each criterion. We give a case study to illustrate the usability of the proposed personalized quantifier in blockchain risk evaluation. The comparative analysis with other four types of personalized quantifiers shows that our proposed personalized quantifier with cubic spline interpolation has ideal geometric characteristics in terms of smooth curve and high fitting accuracy, thus having strong applicability. Further, we show that this method is relatively easy to operate.



中文翻译:

区块链技术的信息表示:利用三次样条插值的个性化量词进行投资的风险评估

随着区块链技术在各个领域的应用,对区块链的研究备受关注。与专注于区块链技术在特定领域的特定应用的研究不同,本研究致力于捕捉投资者对区块链技术投资决策中不同风险标准的态度。我们使用个性化的量词来提取每种风险评估标准上的投资者偏好。当前,可以反映个人态度和行为意图的个性化量词已被各种功能所采用,但是仍然存在局限性。在这方面,本文介绍了三次样条插值函数以适合个性化量词,并解决了有序加权平均聚合中个性化量词的一致性。此外,我们采用定性信息表示模型(称为概率语言术语集)来表达决策者对每个标准的评估。我们通过案例研究来说明拟议的个性化量词在区块链风险评估中的可用性。与其他四种类型的个性化量词的比较分析表明,我们提出的具有三次样条插值的个性化量词在平滑曲线和高拟合精度方面具有理想的几何特征,因此具有很强的适用性。此外,我们表明该方法相对易于操作。我们采用定性的信息表示模型(称为概率语言术语集)来表达决策者对每个标准的评估。我们通过案例研究来说明拟议的个性化量词在区块链风险评估中的可用性。与其他四种类型的个性化量词的比较分析表明,我们提出的具有三次样条插值的个性化量词在平滑曲线和高拟合精度方面具有理想的几何特征,因此具有很强的适用性。此外,我们表明该方法相对易于操作。我们采用定性的信息表示模型(称为概率语言术语集)来表达决策者对每个标准的评估。我们通过案例研究来说明拟议的个性化量词在区块链风险评估中的可用性。与其他四种类型的个性化量词的比较分析表明,我们提出的具有三次样条插值的个性化量词在平滑曲线和高拟合精度方面具有理想的几何特征,因此具有很强的适用性。此外,我们表明该方法相对易于操作。与其他四种类型的个性化量词的比较分析表明,我们提出的具有三次样条插值的个性化量词在平滑曲线和高拟合精度方面具有理想的几何特征,因此具有很强的适用性。此外,我们表明该方法相对易于操作。与其他四种类型的个性化量词的比较分析表明,我们提出的具有三次样条插值的个性化量词在平滑曲线和高拟合精度方面具有理想的几何特征,因此具有很强的适用性。此外,我们表明该方法相对易于操作。

更新日期:2021-03-15
down
wechat
bug