Characterization of the electrocaloric effect and hysteresis loss in relaxor ferroelectric thin films under alternating current bias fields

We report characterization and analysis of the frequency-dependent temperature responses in thin films exhibiting the electrocaloric (EC) effect under AC bias fields using a high-precision lock-in technique. The temperature response detected by an embedded thin-film resistance thermometer is analyzed using the steady-periodic solutions of a 3D heat conduction model to extract the equivalent volumetric heat sources/sinks, which represent the combined effects of cleclrocaloric cooling/heating and hysteresis loss. The dependence of the measured heat source strengths on the bias field frequency and amplitude is consistent with our model prediction and independently measured dielectric properties. The volumetric heating rate due to hysteresis loss is estimated to be as much as 15% of the EC heating/cooling rates for solution-cast relaxor ferroelectric polymer films studied here. Our experimental approach enables a systematic study of the electrocaloric performance of thin films and deleterious impact of hysteresis loss

Some Aggregation Operators Based on Einstein Operations under Interval-Valued Dual Hesitant Fuzzy Setting and Their Application

We investigate the multiple attribute decision making (MADM) problems in which attribute values take the form of interval-valued dual hesitant fuzzy information. Firstly, some operational laws for interval-valued dual hesitation fuzzy elements (IVDHFEs) based on Einstein operations are developed. Then we develop some aggregation operators based on Einstein operations: the interval-valued dual hesitant fuzzy Einstein weighted averaging (IVDHFEWA) operator, interval-valued dual hesitant fuzzy Einstein ordered weighted averaging (IVDHFEOWA) operator, interval-valued dual hesitant fuzzy Einstein hybrid averaging (IVDHFEHA) operator, interval-valued dual hesitant fuzzy Einstein weighted geometric (IVDHFEWG) operator, interval-valued dual hesitant fuzzy Einstein ordered weighted geometric (IVDHFEOWG) operator, and interval-valued dual hesitant fuzzy Einstein hybrid geometric (IVDHFEHG) operator. Furthermore, we discuss some desirable properties of these operators, and investigate the relationship between the developed operators and the existing ones. Based on the IVDHFEWA operator, an approach to MADM problems is proposed under the interval-valued dual hesitant fuzzy environment. Finally, a numerical example is given to show the application of the developed method, and a comparison analysis is conducted to demonstrate the effectiveness of the proposed approach

A Novel Multiple Attribute Satisfaction Evaluation Approach with Hesitant Intuitionistic Linguistic Fuzzy Information

This paper investigates the multiple attribute decision making (MADM) problems in which the attribute values take the form of hesitant intuitionistic linguistic fuzzy element (HILFE). Firstly, motivated by the idea of intuitionistic linguistic variables (ILVs) and hesitant fuzzy elements (HFEs), the concept, operational laws, and comparison laws of HILFE are defined. Then, some aggregation operators are developed for aggregating the hesitant intuitionistic linguistic fuzzy information, such as hesitant intuitionistic linguistic fuzzy weighted aggregation operators, hesitant intuitionistic linguistic fuzzy ordered weighted aggregation operators, and generalized hesitant intuitionistic linguistic fuzzy weighted aggregation operators. Moreover, some desirable properties of these operators and the relationships between them are discussed. Based on the hesitant intuitionistic linguistic fuzzy weighted average (HILFWA) operator and the hesitant intuitionistic linguistic fuzzy weighted geometric (HILFWG) operator, an approach for evaluating satisfaction degree is proposed under hesitant intuitionistic linguistic fuzzy environment. Finally, a practical example of satisfaction evaluation for milk products is given to illustrate the application of the proposed method and to demonstrate its practicality and effectiveness

Extension of VIKOR method for multi-criteria group decision making problem with linguistic information

a b s t r a c t A new method is proposed to solve multi-criteria group decision making problems in which both the criteria values and criteria weights take the form of linguistic information based on the traditional idea of VIKOR method. Firstly, the linguistic criteria weights given by all decision makers are transformed into trapezoidal fuzzy numbers, and then aggregated and defuzzified to crisp values. Secondly, the individual linguistic decision matrix given by each decision maker (DM) is transformed into 2-tuple linguistic decision matrix, and then aggregated into collective 2-tuple linguistic decision matrix by 2-tuple linguistic arithmetic mean operation. Thirdly, the 2-tuple linguistic values ðS i ; a i Þ; ðR i ; a i Þ and ðQ i ; a i Þ are calculated by defining the 2-tuple linguistic positive ideal solution (TL-PIS) and 2-tuple linguistic negative ideal solution (TL-NIS). Furthermore, the compromise solution can be obtained. Finally, a numerical example is used to illustrate the application of the proposed approach, and the method is verified by comparing the evaluation result with that of 2-tuple linguistic TOPSIS (TL-TOPSIS) method. Crow

A Novel Method for Multiattribute Decision Making with Dual Hesitant Fuzzy Triangular Linguistic Information

This paper studies the multiattribute decision making (MADM) problems in which the attribute values take the form of dual hesitant fuzzy triangular linguistic elements and the weights of attributes take the form of real numbers. Firstly, to solve the situation where the membership degree and the nonmembership degree of an element to a triangular linguistic variable, the concept, operational laws, score function, and accuracy function of dual hesitant fuzzy triangular linguistic elements (DHFTLEs) are defined. Then, some dual hesitant fuzzy triangular linguistic geometric aggregation operators are developed for aggregating the DHFTLEs, including dual hesitant fuzzy triangular linguistic weighted geometric (DHFTLWG) operator, dual hesitant fuzzy triangular linguistic ordered weighted geometric (DHFTLOWG) operator, dual hesitant fuzzy triangular linguistic hybrid geometric (DHFTLHG) operator, generalized dual hesitant fuzzy triangular linguistic weighted geometric (GDHFTLWG) operator, and generalized dual hesitant fuzzy triangular linguistic ordered weighted geometric (GDHFTLOWG) operator. Furthermore, some desirable properties of these operators are investigated in detail. Based on the proposed operators, an approach to MADM with dual hesitant fuzzy triangular linguistic information is proposed. Finally, a numerical example for investment alternative selection is given to illustrate the application of the proposed method

Some Aggregation Operators with Intuitionistic Trapezoid Fuzzy Linguistic Information and their Applications to Multi-Attribute Group Decision Making

We study the multi-attribute group decision making (MAGDM) problems in which the attribute values provided by the decision makers take the form of intuitionistic trapezoid fuzzy linguistic (ITrFL) information considering the uncertainty and inaccuracy of input arguments. Some new aggregation operators called intuitionistic trapezoid fuzzy linguistic weighted average (ITrFLWA), intuitionistic trapezoid fuzzy linguistic ordered weighted average (ITrFLOWA) and intuitionistic trapezoid fuzzy linguistic hybrid weighted average (ITrFLHWA) operators are proposed at first. Then, we study some desirable properties of the proposed operators, such as monotonicity, idempotency, commutativity and boundedness. Next, two novel approaches based on the proposed operators are developed to solve MAGDM problems with intuitionistic trapezoid fuzzy linguistic information. Finally, an illustrative example of emergency logistics supplier selection is provided to verify the feasibility of the proposed approaches

A mathematical programming-based method for heterogeneous multicriteria group decision analysis with aspirations and incomplete preference information

International audienceAspirations, which serve as a performance target and simplify cognitive processes associated with decision making, are an important decision factor for individuals and organizations. However, this factor is usually ignored in traditional multicriteria decision making. This paper considers a multicriteria group decision making problem with aspirations and incomplete preference information, in which criteria values and aspirations accept multiple formats. To solve this problem, new consistency and inconsistency indices considering importance and interaction as well as aspirations of criteria are defined. Then, we propose a bi-objective intuitionistic fuzzy programming model to identify importance and interaction parameters, based on which, an individual ranking of alternatives can be elicited. Next, to elicit a group ranking of individuals, a flexible mix 0-1 nonlinear programming model of minimizing the inconsistencies between the group final ranking and the individual ranking is established by comprehensively considering both the majority and the minority principles. Finally, an example of selecting the best strategic freight forwarder is used to illustrate the feasibility of the proposed method, followed by a sensitivity analysis and a comparison analysis. The prominent advantages of the developed method are its ability to handle multiple preference information characterizing bounded rationality and nonadditive behaviors of decision makers as well as improve a cardinal inputs-based group decision making model

An intelligent cross-border transaction system based on consortium blockchain: A case study in Shenzhen, China.

Cross-border transactions have been more and more popular around the world. However, the current cross-border transactions still have risks and challenges, e.g., differences in regulation policies and unbalanced profits of banks. To address this critical issue, we construct a new framework for the transaction system with the support of blockchain technology. In this paper, we propose a new consortium blockchain system, namely asymmetric consortium blockchain (ACB), to ensure the implementation of cross-border transactions. Different from traditional consortium blockchain, the new blockchain system could support the supernode to regulate all the transactions timely. Furthermore, the new smart contract is designed to lower the opportunity loss for each node and make the profits allocation system fairer. In the end, the numerical experiments were carried out based on the transactions of Shenzhen and Hong Kong. The results show that the proposed ACB system is efficient to make the profit allocation fairer for the participants and keep intelligent for the new cross-border transaction system