Contribution Modeling on Condition Evaluation of Asphalt Pavement Using Uncertainty Measurement and Entropy Theory

In view of the deficiency that traditional pavement performance evaluation index did not consider the influence of their difference on weight, the grade of the evaluation index also did not take into account intermediate state and the impact of uncertainty on the evaluation results, a determination method of pavement performance evaluation index weight based on entropy theory was developed. The unascertained measurement function of evaluation index was performed by left-half ladder distribution, and unascertained measurement matrix was obtained. The index weight was calculated by minimum entropy theory, and the practicability of this method was verified through a concrete example finally. The results show that there were different weights in different samples, which depended on index measurement function and were the overall characterization of comprehensive measurement of every index. The method which is based on the given weighting factor did not conform to the engineering facts. It was difficult to identify the importance of the pavement performance evaluation index in different samples. The balance of the various indexes is better to be considered in the proposed method, and the comprehensive situation of pavement performance is really reflected, which improves the evaluation of the reliability.

Being Uncertain in Chromatographic Calibration—Some Unobvious Details in Experimental Design

This is an introductory tutorial and review about the uncertainty problem in chromatographic calibration. It emphasizes some unobvious, but important details influencing errors in the calibration curve estimation, uncertainty in prediction, as well as the connections and dependences between them, all from various perspectives of uncertainty measurement. Nonuniform D-optimal designs coming from Fedorov theorem are computed and presented. As an example, all possible designs of 24 calibration samples (3–8, 4–6, 6–4, 8–3 and 12–2, both uniform and D-optimal) are compared in context of many optimality criteria. It can be concluded that there are only two independent (orthogonal, but slightly complex) trends in optimality of these designs. The conclusions are important, as the uniform designs with many concentrations are not the best choices, contrary to some intuitive perception. Nonuniform designs are visibly better alternative in most calibration cases.

Some results on fuzzy relations

Fuzzy relation is one of the main research contents of fuzzy set theory. This paper obtains some results on fuzzy relations by studying relationships between fuzzy relations and their uncertainty measurement. The concepts of equality, dependence, partial dependence and independence between fuzzy relations are first introduced. Then, uncertainty measurement for a fuzzy relation is investigated by using dependence between fuzzy relations. Moreover, the basic properties of uncertainty measurement are obtained. Next, effectiveness analysis is carried out. Finally, an application of the proposed measures in attribute reduction for heterogeneous data is given. These results will be helpful for understanding the essence of a fuzzy relation.

PENGARUH UNCERTAINTY TERHADAP KEBIJAKAN TRADE CREDIT PERUSAHAAN INDONESIA

<p><em> </em><strong><em>ABSTRACT :</em></strong><strong><em> </em></strong><em>Uncertainty seems to be the root of prolonged recession period problem and it increases researcher concern regarding its effect to the economy. During high uncertainty period, information is not clear and affect firm’s decision maker regarding their investment, capital structure and also trade credit policy. In this paper, we aim to find the effect of uncertainty to firm’s trade credit policy. Uncertainty is argued to increase firm’s credit risk and thus, firm should adjust their trade credit policy to survive. Our sample includes non-financial listed firms in Indonesia Stock Exchange (IDX), with observation period from 2006 Q1 to 2019 Q4. The financial data used to construct the variables are obtained from the S&amp;P Capital IQ database. The methodology used is fixed effect panel data regression. This study utilized uncertainty measurement developed by </em>Ahir et al. (2018)<em>, that is the world uncertainty index (WUI). Using total of 12,773 firm-quarter observations, our result show that uncertainty indeed caused firms to adjust their trade credit policy. Uncertainty caused higher cost of capital, as consequences firms decide to tighten their credit policy to its customer and decrease their payables to the supplier as precautionary to avoid future financial distress. </em></p><p><strong><em>Keywords: </em></strong><em> </em><em>Uncertainty, trade credit policy, receivable days, payable days</em></p><p> </p><p><strong>ABSTRAK :</strong><strong> </strong>Ketidakpastian dianggap menjadi akar dari masalah periode resesi yang panjang dan hal ini meningkatkan kekhawatiran dari para peneliti mengenai efeknya terhadap ekonomi. Pada keadaan ketidakpastian yang tinggi, informasi menjadi tidak jelas dan mempengaruhi pengambil keputusan didalam perusahaan mengenai kebijakan investasi, struktur modal dan juga kredit dagang. Pada penelitian ini, kami bertujuan untuk menemukan efek dari ketidakpastian pada kebijakan kredit dagang perusahaan. Ketidakpastian dikatakan dapat meningkatkan resiko kredit perusahaan dan sehingga, perusahaan perlu menyesuaikan kebijakan kredit dagang mereka untuk dapat bertahan. Sampel penelitian ini termasuk perusahaan non keuangan yang terdaftar pada bursa efek Indonesia (BEI), dengan periode observasi dari 2006 kuartal 1 hingga 2019 kuartal 4. Data keuangan yang digunakan untuk membentuk variabel pebelitian diambil dari <em>the S&amp;P Capital IQ database. </em>Metodologi yang digunakan adalah regresi data panel <em>fixed effect</em>. Penelitian ini menggunakan ukuran ketidakpastian yang dikembangkan oleh Ahir et al.(2018), yaitu <em>the world uncertainty index (WUI)</em>. Dengan menggunakan total observasi sebanyak 12.773 perusahaan-kuartal, hasil yang didapatkan menunjukkan bahwa ketidakpastian mennyebabkan perusahaan untuk melakukan penyesuaian pada kebijakan kredit dagangnya. Ketidakpastian meningkatkan biaya modal dan sebagai akibatnya perusahaan memutuskan untuk memperketat kebijkan kredit kepada pembeli dan menurunkan hutang dagangnya pada pemasok sebagai tindakan berhati-hati untuk menghindari kesulitan keuangan dimasa depan.</p><p><strong>Kata Kunci:</strong> Ketidakpastian, kebijakan kredit dagang, <em>receivable days, payable days</em></p><strong></strong>

Feature selection for incomplete set-valued data

Set-valued data is a significant kind of data, such as data obtained from different search engines, market data, patients’ symptoms and behaviours. An information system (IS) based on incomplete set-valued data is called an incomplete set-valued information system (ISVIS), which generalized model of a single-valued incomplete information system. This paper gives feature selection for an ISVIS by means of uncertainty measurement. Firstly, the similarity degree between two information values on a given feature of an ISVIS is proposed. Then, the tolerance relation on the object set with respect to a given feature subset in an ISVIS is obtained. Next, λ-reduction in an ISVIS is presented. What’s more, connections between the proposed feature selection and uncertainty measurement are exhibited. Lastly, feature selection algorithms based on λ-discernibility matrix, λ-information granulation, λ-information entropy and λ-significance in an ISVIS are provided. In order to better prove the practical significance of the provided algorithms, a numerical experiment is carried out, and experiment results show the number of features and average size of features by each feature selection algorithm.

Measuring the Uncertainty in the Original and Negation of Evidence Using Belief Entropy for Conflict Data Fusion

Dempster-Shafer (DS) evidence theory is widely used in various fields of uncertain information processing, but it may produce counterintuitive results when dealing with conflicting data. Therefore, this paper proposes a new data fusion method which combines the Deng entropy and the negation of basic probability assignment (BPA). In this method, the uncertain degree in the original BPA and the negation of BPA are considered simultaneously. The degree of uncertainty of BPA and negation of BPA is measured by the Deng entropy, and the two uncertain measurement results are integrated as the final uncertainty degree of the evidence. This new method can not only deal with the data fusion of conflicting evidence, but it can also obtain more uncertain information through the negation of BPA, which is of great help to improve the accuracy of information processing and to reduce the loss of information. We apply it to numerical examples and fault diagnosis experiments to verify the effectiveness and superiority of the method. In addition, some open issues existing in current work, such as the limitations of the Dempster–Shafer theory (DST) under the open world assumption and the necessary properties of uncertainty measurement methods, are also discussed in this paper.