Sichuan University

About: Sichuan University is a education organization based out in Chengdu, China. It is known for research contribution in the topics: Catalysis & Population. The organization has 107623 authors who have published 102844 publications receiving 1612131 citations. The organization is also known as: Sìchuān Dàxué.

An Efficient Mono-Component Polymeric Intumescent Flame Retardant for Polypropylene: Preparation and Application

Abstract: We found in our previous study that ethylenediamine- or ethanolamine-modified ammonium polyphosphates could be used alone as an intumescent flame retardant for polypropylene (PP), but their flame-retardant efficiency was not very high. In this present work, a novel highly-efficient mono-component polymeric intumescent flame retardant, piperazine-modified ammonium polyphosphate (PA-APP) was prepared. The oxygen index value of PP containing 22 wt % of PA-APP reached 31.2%, which increased by 58.4% compared with that of PP with equal amount of APP, and the vertical burning test (UL-94) could pass V-0 rating. Cone calorimeter (CC) results indicated that PP/PA-APP composite exhibited superior performance compared with PP/APP composite. For PP containing 25 wt % of PA-APP, fire growth rate (FGR) and smoke production rate (SPR) peak were reduced by 86.4% and 78.2%, respectively, compared with PP blended with 25 wt % APP. The relevant flame-retardant mechanism of PA-APP was investigated by Fourier transform infra...

Consistency-based risk assessment with probabilistic linguistic preference relation

Abstract: Display Omitted Propose the probabilistic linguistic preference relation (PLPR).Discuss the consistency of PLPR from the perspective of digraph.Present the consistency and acceptable consistency measures of PLPR.Establish an optimization model to improve the consistency of PLPR.Apply the proposed method to risk assessment. In recent years, the Belt and Road has aroused great attention of international society. It not only produces opportunities for China but also brings challenges: when Chinese investors invest to other countries, they will analyze the present situation of alternative countries and then assess the investment risk of these countries. Hence, how to assess the risk level of alternative countries correctly is pivotal. Moreover, affected by many factors such as decision makers (DMs) lacking of knowledge and the complexity of decision making problems, the DMs usually cannot use precise numbers to describe their preference information. Therefore, the use of linguistic variables is practical. As a type of linguistic term set, the probabilistic linguistic term set (PLTS) can reflect different importance degrees or weights of all possible evaluation values of a specific object. Whats more, when the DMs use linguistic variables to express their judgements, they sometimes cannot give their evaluation values for attributes directly. In such a case, the DMs usually provide their judgements by pairwise comparison of alternatives. In this paper, we introduce the concept of probabilistic linguistic preference relation (PLPR) to present the DMs preferences. The additive consistency of the PLPR is discussed from the perspective of the preference relation graph. Then, the consistency index of the PLPR is defined to measure the consistency. We also introduce the acceptable consistency of the PLPR. Moreover, as for the unacceptable consistent PLPR, an automatic optimization method is proposed to improve its consistency until acceptable. Once all the PLPRs are of acceptable consistency, we directly use the aggregation operators to obtain the comprehensive preference values of alternatives and then rank the alternatives according to the derived preference values. Finally, an application example involving the Belt and Road is given and the discussion about the results is conducted.

Consistency-Driven Automatic Methodology to Set Interval Numerical Scales of 2-Tuple Linguistic Term Sets and Its Use in the Linguistic GDM With Preference Relation

Abstract: The 2-tuple linguistic modeling is a popular tool for computing with words in decision making. In order to deal with the linguistic term sets that are not uniformly and symmetrically distributed, the numerical scale model has been developed to generalize the 2-tuple linguistic modeling. In the numerical scale model, the key task of the 2-tuple based models is the definition of a numerical scale function that establishes a one to one mapping between the linguistic information and numerical values. In this paper, we propose a consistency-driven automatic methodology to set interval numerical scales of 2-tuple linguistic term sets in the decision making problems with linguistic preference relations. This consistency-driven methodology is based on a natural premise regarding the consistency of preference relations. If linguistic preference relations provided by experts are of acceptable consistency, the corresponding transformed numerical preference relations by the established interval numerical scale are also consistent. Compared with the existing approach based on canonical characteristic values, the consistency-driven methodology provides a new way to set the interval numerical scale without the need of the semantics defined by interval type-2 fuzzy sets. Meanwhile, interval multiplicative preference relations are used in the pairwise comparisons method and the presented theory can be utilized in the pairwise comparisons method as it provides a novel approach to automatic construct interval multiplicative preference relations. Finally, we present the framework for the use of the consistency-driven automatic methodology in linguistic group decision making problems and two numerical examples are given to illustrate the feasibility and validity of this proposal.