Optimal Performance Analysis of a Three-Terminal Thermoelectric Refrigerator with Ideal Tunneling Quantum Dots

The model of a three-terminal thermoelectric refrigerator with ideal tunneling quantum dots is established. It consists of a cavity connected to two quantum dots embedded between two electron reservoirs at different temperatures and chemical potentials. According to the Landauer formula the expressions for the heat current, the cooling rate and the coefficient of performance （COP） are derived analytically. The performance characteristic curves of the cooling rate versus the coefficient of performance are plotted with numerical calculation. The optimal regions of the cooling rate and the COP are determined. Moreover, we optimize the cooling rate and the COP with respect to the position of energy level of the right quantum dot, respectively. The influence of the width of energy level and the temperature ratio on performance of the three-terminal thermoelectric refrigerator is analyzed. Lastly, when the width of energy level is small enough, the optimal performance of the refrigerator is discussed in detail.

基于组合赋权-TOPSIS模型的机场运行效率评价

为提高机场运行效率评价结果的科学性和全面性,提出了一种基于组合赋权-TOPSIS(technique for order performance by similarity to ideal solution)模型的机场运行效率评价方法。从机位运行效率、旅客登机效率、飞机滑行效率和协同效率4个维度出发,构建了由航班靠桥率、廊桥周转率、机位变更比例等11个指标组成的机场运行效率评价体系;利用G1法、熵权法分别计算评价指标主观和客观权重,以最小化主客观加权属性偏离程度为目标计算组合权重;使用TOPSIS计算待评价机场综合评价指数。利用该模型分析国内3类共8家机场的运行效率,可以得到各评价对象的运行效率等级和综合排名。结果表明:该模型能够有效探明影响机场运行效率的主要因素,具有一定的参考价值。

Extension of TOPSIS for fuzzy multi-attribute decision making problem based on experimental analysis

This paper is concerned with a technique for order performance by similarity to ideal solution（TOPSIS） method for fuzzy multi-attribute decision making,in which the information about attribute weights is partly known and the attribute values take form of triangular fuzzy numbers.Considering the fact that the triangular fuzzy TOPSIS results yielded by different distance measures are different from others,a comparative analysis of triangular fuzzy TOPSIS ranking from each distance measure is illustrated with discussion on standard deviation.By applying the most reasonable distance,the deviation degrees between attribute values are measured.A linear programming model based on the maximal deviation of weighted attribute values is established to obtain the attribute weights.Therefore,alternatives are ranked by using TOPSIS method.Finally,a numerical example is given to show the feasibility and effectiveness of the method.

Risk assessment of floor water inrush in coal mines based on MFIM-TOPSIS variable weight model

Floor water inrush is one of the main types of coal mine water hazards.With the development of deep mining,the prediction and evaluation of floor water inrush is particularly significant.This paper proposes a variable weight model,which combines a multi-factor interaction matrix(MFIM)and the technique for order performance by similarity to ideal solution(TOPSIS)to implement the risk assessment of floor water inrush in coal mines.Based on the MFIM,the interaction between seven evaluation indices,including the confined water pressure,water supply condition and aquifer water yield property,floor aquifuge thickness,fault water transmitting ability,fracture development degree,mining depth and thickness and their influence on floor water inrush were considered.After calculating the constant weights,the active degree evaluation was used to assign a variable weight to the indices.The values of the middle layer and final risk level were obtained by TOPSIS.The presented model was successfully applied in the 9901 working face in the Taoyang Mine and four additional coal mines and the results were highly consistent with the engineering situations.Compared with the existing nonlinear evaluation methods,the proposed model had advantages in terms of the weighting,principle explanation,and algorithm structure.

Fuzzy TOPSIS method to primary crusher selection for Golegohar Iron Mine(Iran)

Selection of the crusher required a great deal of design regarding to the mine planning. Selection of suitable primary crusher from all of available primary crushers is a multi-criterion decision making(MCDM) problem. The present work explores the use of technique for order performance by similarity to ideal solution(TOPSIS) with fuzzy set theory to select best primary crusher for Golegohar Iron Mine in Iran. Gyratory, double toggle jaw, single toggle jaw, high speed roll crusher, low speed sizer, impact crusher, hammer mill and feeder breaker crushers have been considered as alternatives. Also, the capacity, feed size, product size, rock compressive strength, abrasion index and application of primary crusher for mobile plants were considered as criteria for solution of this MCDM problem. To determine the order of the alternatives, closeness coefficient is defined by calculating the distances to the fuzzy positive ideal solution(FPIS) and fuzzy negative ideal solution(FNIS). Results of our work based on fuzzy TOPSIS method show that the gyratory is the best primary crusher for the studied mine.

TOPSIS with Belief Structure for Group Belief Multiple Criteria Decision Making

The technique for order performance by similarity to ideal solution （TOPSIS） is one of the major techniques in dealing with multiple criteria decision making （MCDM） problems, and the belief structure （BS） model has been used successfully for uncertain MCDM with incompleteness, impreciseness or ignorance. In this paper, the TOPSIS method with BS model is proposed to solve group belief MCDM problems. Firstly, the group belief MCDM problem is structured as a belief decision matrix in which the judgments of each decision maker are described as BS models, and then the evidential reasoning approach is used for aggregating the multiple decision makers＇ judgments. Subsequently, the positive and negative ideal belief solutions are defined with the principle of TOPSIS. To measure the separation from ideal solutions, the concept and algorithm of belief distance measure are defined, which can be used for comparing the difference between BS models. Finally, the relative closeness and ranking index are calculated for ranking the alternatives. A numerical example is given to illustrate the proposed method.

Synthetic security assessment for incomplete interval-valued information system

In order to understand the security conditions of the incomplete interval-valued information system （IllS） and acquire the corresponding solution of security problems, this paper proposes a multi-attribute group decision- making （MAGDM） security assessment method based on the technique for order performance by similarity to ideal solution （TOPSIS）. For IllS with preference information, combining with dominance-based rough set approach （DRSA）, the effect of incomplete interval-valued information on decision results is discussed. For the imprecise judgment matrices, the security attribute weight can be obtained using Gibbs sampling. A numerical example shows that the proposed method can acquire some valuable knowledge hidden in the incomplete interval-valued information. The effectiveness of the proposed method in the synthetic security assessment for IIIS is verified.