An automatic iterative decision-making method for intuitionistic fuzzy linguistic preference relations

As a new preference structure, the intuitionistic fuzzy linguistic preference relation (IFLPR) was recently introduced to efficiently deal with situations in which the membership and non-membership are represented as linguistic terms. In this paper, we study the issues of additive consistency and the derivation of the intuitionistic fuzzy weight vector of an IFLPR. First, the new concepts of order consistency, additive consistency and weak transitivity for IFLPRs are introduced, and followed by a discussion of the characterisation about additive consistent IFLPRs. Then, a parameterised transformation approach is investigated to convert the normalised intuitionistic fuzzy weight vector into additive consistent IFLPRs. After that, a linear optimisation model is established to derive the normalised intuitionistic fuzzy weights for IFLPRs, and a consistency index is defined to measure the deviation degree between an IFLPR and its additive consistent IFLPR. Furthermore, we develop an automatic iterative decision-making method to improve the IFLPRs with unacceptable additive consistency until the adjusted IFLPRs are acceptable additive consistent, and it helps the decision-maker to obtain the reasonable and reliable decision-making results. Finally, an illustrative example is provided to demonstrate the validity and applicability of the proposed method.     

An approach to multiplicative linguistic group decision making based on possibility degrees

In order to compare two uncertain multiplicative linguistic variables, a possibility degree formula has been developed and its properties are also studied. Then a possibility degree matrix (also considered as a reciprocal preference relation) is constructed to compare a collection of uncertain multiplicative linguistic variables. Two models are further provided to derive the priority vector from the possibility degree matrix based on the additive consistency and multiplicative consistency. Especially, if the parameters are assigned specific values, then the models reduce to the existing ones. A group decision making method has been developed to deal with the situations where the preferences on alternatives are expressed by uncertain multiplicative linguistic variables. In this method, the possibility degree matrix is first constructed, from which the priority of alternatives is obtained using the developed models. At the end, an example is given to illustrate the proposed method.     

Improving branch divergence performance on GPGPU with a new PDOM stack and multi-level warp scheduling

General-purpose graphics processing unit (GPGPU) plays an important role in massive parallel computing nowadays. A GPGPU core typically holds thousands of threads, where hardware threads are organized into warps. With the single instruction multiple thread (SIMT) pipeline, GPGPU can achieve high performance. But threads taking different branches in the same warp violate SIMD style and cause branch divergence. To support this, a hardware stack is used to sequentially execute all branches. Hence branch divergence leads to performance degradation. This article represents the PDOM (post dominator) stack as a binary tree, and each leaf corresponds to a branch target. We propose a new PDOM stack called PDOM-ASI, which can schedule all the tree leaves. The new stack can hide more long operation latencies with more schedulable warps without the problem of warp over-subdivision. Besides, a multi-level warp scheduling policy is proposed, which lets part of the warps run ahead and creates more opportunities to hide the latencies. The simulation results show that our policies achieve 10.5% performance improvements over baseline policies with only 1.33% hardware area overhead.     

Application of fuzzy-analytic hierarchy process algorithm and fuzzy load profile for load shedding in power systems

In an electrical competitive market, load shedding decision support systems are needed to find the ways to process load shedding to satisfy both economic and technical conditions. This paper proposed the Fuzzy Analytic Hierarchy Process algorithm (Fuzzy-AHP) and fuzzy logic for load profile approach to determine the weight of the load nodes of the system and select the control strategy when the system operates at various load levels. Weights of the load nodes were calculated by triangular fuzzy numbers in the pair comparison. These results combined with the fuzzy logic for load profile to draw out the suitable control strategies for various load levels in case of emergency. The effectiveness of the algorithm was demonstrated through the experiment of load shedding of IEEE 37 bus compared with traditional AHP algorithm.     

A hesitant fuzzy model of computational trust considering hesitancy,vagueness and uncertainty

The aim of this work is to introduce a trust model, which is highly consistent with the social nature of trust in computational domains. To this end, we propose a hesitant fuzzy multi-criteria decision making based computational trust model capable of taking into account the fundamental building blocks corresponding to the concept of trust. The proposed model is capable of considering the contextuality property of trust and the subjective priorities of the trustor regarding the chosen goal. This is due to viewing trust not as a single label or an integrated concept, but as a collection of trustworthiness facets that may form the trust decision in various contexts and toward different goals. The main benefit of the proposed model is the consideration of the hesitancy of recommenders and the trustor in the process of trust decision making which can create a more flexible mapping between the social and computational requirements of trust. This type of formulation also allows for taking into account the vagueness of the provided opinions. In addition to the vagueness of the provided opinions, the model is capable of considering the certainty of recommendations and its effect on the aggregation process of gathered opinions. In the proposed model, the taste of the recommenders and the similarity of opinions are also considered. This will allow the model to assign more weight to recommendations that have a similar taste compared to the trustor. Finally, taking into consideration the attitudes of the trustors toward change of personality that may occur for various entities in the environment is another advantage of the proposed model. A step-by-step illustrative example and the results of several experimental evaluations, which demonstrate the benefits of the proposed model, are also presented in this paper.     

A linguistic approach to non-identical parallel processor scheduling with fuzzy processing times

This study presents an application of non-identical parallel processor scheduling under uncertain operation times. We have been motivated from a real case scheduling problem that contains some uncommon welding operations to be processed by workers in an automotive subcontract company. Here each operator may weld each job but in different processing times depending on learning effect because of operator’s ability and experience, and batch sizes. To determine the crisp operation times in such a fuzzy environment, a linguistic reasoning approach (with a 75-“If- Then” rules) considering the learning effect is proposed in the study. Since the fuzzy linguistic approach allows the representation of expert information more directly and adequately, it can be more possible to make realistic schedules under uncertainty. With the objective to balance the workload among all operators, the longest processing time heuristic algorithm is been used and measured average makespan. For evaluating the effectiveness of this approach, it is compared with the scheduling method that use the random operation times generated from a uniform distribution. Results showed that the proposed fuzzy linguistic scheduling approach has balanced the workload of operators with a standard deviation of 0.37 and improved the Cmax value as 16%. A general conclusion can be drawn the proposed approach is able to generate realistic schedules and especially useful to solve non-identical parallel processor scheduling problem under uncertainty. An important contribution of this study is that Mamdani inference method with learning effect is the first time used to obtain the crisp processing times of non-identical processors by the help of a rule base with expert knowledge.     

Information theoretic learning with adaptive kernels

This paper presents an online algorithm for adapting the kernel width that is a free parameter in information theoretic cost functions using Renyi's entropy. This kernel computes the interactions between the error samples and essentially controls the nature of the performance surface over which the parameters of the system adapt. Since the error in an adaptive system is non-stationary during training, a fixed value of the kernel width may affect the adaptation dynamics and even compromise the location of the global optimum in parameter space. The proposed online algorithm for adapting the kernel width is derived from first principles and minimizes the Kullback-Leibler divergence between the estimated error density and the true density. We characterize the performance of this novel approach with simulations of linear and nonlinear systems training, using the minimum error entropy criterion with the proposed adaptive kernel algorithm. We conclude that adapting the kernel width improves the rate of convergence of the parameters, and decouples the convergence rate and misadjustment of the filter weights.     

基于特征散度K-means红外图像分割遗传算法

针对红外图像中目标和背景的对比度低,边缘模糊的特点,本文提出了改进的聚类分割算法KFGA。用特征散度的内积范数作为K-means算法的距离测度,改进算法的普适性;针对K-means算法收敛的局部寻优问题,将遗传算法与K-means算法结合实现全局寻优;在种群每一次演化操作后实行一次K-means聚类,加快算法的收敛速度,在全局寻优的过程中嵌入局部寻优加快算法的收敛速度。     

大功率激光器阵列光场分布测试方法的研究

针对大功率半导体激光器阵列难以进行光场分布测试评价的问题,设计了大功率激光器光场分布测试系统。从测试系统探测器的抗损伤阈值方面,分析了对激光衰减的比例要求,提出了几种衰减的方法,设计了低透射系数高抗激光损伤的衰减方案,并进行逐一的测试比较,得到了理想的衰减效果。结合测试系统要求,完成了大功率半导体激光器光场分布的测试与评价。     

变发散角半导体激光器光束整形发射系统设计

变发散角半导体激光束具有重要的应用意义.根据光线传输的基本原理,从理论上推导了变发散角半导体激光器光束整形发射系统的设计公式,在推导过程中,为了更准确地设计系统,保证出射光束质量,需考虑半导体激光器的固有像散.讨论了最佳的系统结构形式,推导了半导体激光器光束整形的变发散角公式,根据该公式设计了一个变发散角半导体激光器光...