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A new multiplicative consistency based method for decision making with triangular fuzzy reciprocal preference relations

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FUZZY SETS AND SYSTEMS 2017年 315卷 1-25页

作者： Meng, Fanyong Lin, Jian Tan, Chunqiao Zhang, Qiang Nanjing Audit Univ Sch Int Audit Nanjing 211815 Jiangsu Peoples R China Cent S Univ Sch Business 932 South Lushan Rd Changsha 410083 Hunan Peoples R China Fujian Agr & Forestry Univ Coll Comp & Informat Fuzhou 350002 Peoples R China Beijing Inst Technol Sch Management & Econ Beijing 100081 Peoples R China

Triangular fuzzy reciprocal preference relations (TFRPRs) are good choices to denote the decision makers' fuzzy preferences. Consistency analysis is a very important topic to preference relations that can avoid the illogical ranking order. However, all previous multiplicative consistency concepts for TFRPRs cannot well address this type of preference relations. To address this issue, this paper introduces a new multiplicative consistency concept for TFRPRs, which can be seen as a natural extension of Tanino's multiplicative consistency concept for reciprocal preference relations. Based on the new consistency concept, 0-1 mixed' programming models for judging the multiplicative consistency of TFRPRs are constructed, and an approach for deriving multiplicative consistent TFRPRs is provided. Considering the incomplete case, programming models to determine missing values ate constructed. Subsequently, a multiplicative consistency based method for decision making with TFRPRs is presented that can address the inconsistent and incomplete cases. Meanwhile, illustrative examples are provided to show the concrete application of the proposed procedure, and comparison analysis is also made. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Decision analysis TFRPR Quasi TFRPR Consistency analysis programming model

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HadoopCL2: Motivating the Design of a Distributed, Heterogeneous programming System With Machine-Learning Applications

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2016年第3期27卷 762-775页

作者： Grossman, Max Breternitz, Mauricio Sarkar, Vivek Rice Univ Dept Comp Sci 6100 Main St Houston TX USA AMD Res 7171 Southwest Pkwy Austin TX USA

Machine learning (ML) algorithms have garnered increased interest as they demonstrate improved ability to extract meaningful trends from large, diverse, and noisy data sets. While research is advancing the state-of-the-art in ML algorithms, it is difficult to drastically improve the real-world performance of these algorithms. Porting new and existing algorithms from single-node systems to multi-node clusters, or from architecturally homogeneous systems to heterogeneous systems, is a promising optimization technique. However, performing optimized ports is challenging for domain experts who may lack experience in distributed and heterogeneous software development. This work explores how challenges in ML application development on heterogeneous, distributed systems shaped the development of the HadoopCL2 (HCL2) programming system. ML applications guide this work because they exhibit features that make application development difficult: large & diverse datasets, complex algorithms, and the need for domain-specific knowledge. The goal of this work is a general, MapReduce programming system that outperforms existing programming systems. This work evaluates the performance and portability of HCL2 against five ML applications from the Mahout ML framework on two hardware platforms. HCL2 demonstrates speedups of greater than 20x relative to Mahout for three computationally heavy algorithms and maintains minor performance improvements for two I/O bound algorithms.

关键词： MapReduce heterogeneous distributed programming model GPU auto-scheduling

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Exploiting the priority weights from interval linguistic fuzzy preference relations

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SOFT COMPUTING 2019年第2期23卷 583-597页

作者： Meng, Fanyong Tang, Jie Xu, Zeshui Nanjing Audit Univ Sch Int Audit Nanjing 211815 Jiangsu Peoples R China Sichuan Univ Sch Business Chengdu 610064 Sichuan Peoples R China Cent S Univ Sch Business Changsha 410083 Hunan Peoples R China Nanjing Univ Informat Sci & Technol Sch Comp & Software Nanjing 210044 Jiangsu Peoples R China

Interval linguistic fuzzy preference relations (ILFPRs) are powerful tools to denote the decision makers' uncertain qualitative preferences. To avoid the inconsistent ranking results, consistency analysis is very critical. This paper introduces a new additive consistency concept for ILFPRs, which satisfies all properties of the additive consistency concept for fuzzy preference relations. Then, a model to judging the additive consistency of ILFPRs is constructed. When ILFPRs are inconsistent, an approach to deriving additive consistent ILFPRs is presented. Considering the incomplete case, goal programming models to determining the missing values are established. Subsequently, a distance measure-based group consensus index is given to measuring the consensus of individual ILFPRs. Furthermore, a new method for group decision making with ILFPRs is developed, which is based on the additive consistency and consensus analysis. Finally, two numerical examples are offered to show the application of the developed procedure, and a comparison analysis is performed.

关键词： Group decision making Interval linguistic fuzzy preference relation Additive consistency Consensus programming model

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Group decision making based on acceptable consistency analysis of interval linguistic hesitant fuzzy preference relations

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INFORMATION SCIENCES 2020年 530卷 66-84页

作者： Meng, Fanyong Chen, Shyi-Ming Zhang, Shaolin Beijing Wuzi Univ Sch Informat Beijing 101149 Peoples R China Natl Taiwan Univ Sci & Technol Dept Comp Sci & Informat Engn Taipei Taiwan Cent South Univ Sch Business Changsha 410083 Peoples R China

To represent decision makers' qualitative uncertainty and hesitation judgments, interval linguistic hesitant fuzzy variables (ILHFVs) are efficient tools, which can be regarded as an expansion of interval linguistic variables (ILVs). Taking the merits of ILHFVs and preference relations, this paper focuses on group decision making (GDM) with interval linguistic hesitant fuzzy preference relations (ILHFPRs). By considering the consistency of ILHFPRs, a new definition of acceptable consistency is presented. Using the acceptable consistency index, some models are built to measure whether a given ILHFPR is acceptable consistent. If the consistency is unacceptable, some models are constructed to derive acceptable consistent ILHFPRs by considering the total adjustment and the number of adjusting ILVs. In order to cope with incomplete ILHFPRs, some models for obtaining the values of unknown ILVs are proposed. For GDM with ILHFPRs, an index for measuring the consensus degree of ILHFPRs is proposed. When ILHFPRs do not meet the requirement of the consensus, some models for enhancing the consensus degree are proposed. According to the analysis of acceptable additive consistency and consensus of ILHFPRs, a new method for GDM with ILHFPRs is proposed. In order to show the merits of the proposed GDM method, an application example is used. (C) 2020 Elsevier Inc. All rights reserved.

关键词： Group decision making Acceptable consistency ILHFPR programming model

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Global optimisation model and algorithm for unit restarting sequence considering black-start zone partitioning

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第13期13卷 2652-2663页

作者： Gu, Xueping Zhou, Guangqi Li, Shaoyan Liu, Tong North China Elect Power Univ Sch Elect & Elect Engn Baoding 071003 Hebei Peoples R China

Unit restarting after a blackout is the basis of the overall restoration process for a power system. A reasonable restarting sequence of units may speed up the restoration process and reduce economic loss. In view of the situation that there are usually several black-start sources in a large-scale power system, a global optimisation method for unit restarting considering black-start zone partitioning is proposed in this study. On the basis of the multiple time-step modelling framework, the optimisation problem is formulated as a mixed integer linear programming model, with the objective functions to maximise the total-weighted MWh output and minimise the links between the subsystems under various operational constraints. The hierarchical method based on generalised Benders decomposition is applied to decompose the optimisation problem into one master problem and two sub-problems: (i) determination of the unit restarting sequence considering only the grouping of units and (ii) rationality check of unit grouping and check of operational constraints based on power flow calculation. The master problem and sub-problems are alternately and iteratively solved until the optimal solution is obtained. The results of New England 10-unit 39-bus system and a practical power system in southwest China verify the validity of the proposed method.

关键词： load flow integer programming power system restoration power grids optimisation power system security linear programming black-start zone partitioning unit restarting restoration process reasonable restarting sequence black-start sources large-scale power system global optimisation method multiple time-step modelling framework optimisation problem programming model total-weighted MWh output operational constraints master problem unit grouping check power flow calculation New England 10-unit 39-bus system practical power system

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The AXIOM platform for next-generation cyber physical systems

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MICROPROCESSORS AND MICROSYSTEMS 2017年 52卷 540-555页

作者： Theodoropoulos, Dimitris Mazumdar, Somnath Ayguade, Eduard Bettin, Nicola Bueno, Javier Ermini, Sara Filgueras, Antonio Jimenez-Gonzalez, Daniel Alvarez Martinez, Carlos Martorell, Xavier Montefoschi, Francesco Oro, David Pnevmatikatos, Dionisis Rizzo, Antonio Gai, Paolo Garzarella, Stefano Morelli, Bruno Pomella, Alberto Giorgi, Roberto Fdn Res & Technol Hellas FORTH Inst Comp Sci Iraklion Greece Univ Siena Dipartimento Ingn Informaz & Sci Matemat Siena Italy BSC Barcelona Spain VIMAR SpA Marostica Marostica Italy Univ Siena Dipartimento Sci Sociali Polit & Cognit Siena Italy Univ Politecn Cataluna Comp Architecture Dept Barcelona Spain Herta Secur Barcelona Barcelona Spain Tech Univ Crete Sch ECE Khania Greece Evidence Srl San Giuliano Terme Italy

Cyber-Physical Systems (CPSs) are widely used in many applications that require interactions between humans and their physical environment. These systems usually integrate a set of hardware-software components for optimal application execution in terms of performance and energy consumption. The AXIOM project (Agile, eXtensible, fast I/O Module), presented in this paper, proposes a hardware-software platform for CPS coupled with an easy parallel programming model and sufficient connectivity so that the performance can scale-up by adding multiple boards. AXIOM supports a task-based programming model based on OmpSs and leverages a high-speed, inexpensive communication interface called AXIOM-Link. The board also tightly couples the CPU with reconfigurable resources to accelerate portions of the applications. As case studies, AXIOM uses smart video surveillance, and smart home living applications. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Cyber-physical systems Distributed shared memory programming model Performance evaluation Reconfigurable Smart video surveillance Smart home living

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IOTSim: A simulator for analysing IoT applications

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JOURNAL OF SYSTEMS ARCHITECTURE 2017年 72卷 93-107页

作者： Zeng, Xuezhi Garg, Saurabh Kumar Strazdins, Peter Jayaraman, Prem Prakash Georgakopoulos, Dimitrios Ranjan, Rajiv Australian Natl Univ Res Sch Comp Sci Canberra ACT 2914 Australia Univ Tasmania Hobart Tas 7001 Australia RMIT Melbourne Vic Australia Newcastle Univ Newcastle Upon Tyne Tyne & Wear England

A disruptive technology that is influencing not only computing paradigm but every other business is the rise of big data. Internet of Things (loT) applications are considered to be a major source of big data. Such loT applications are in general supported through clouds where data is stored and processed by big data processing systems. In order to improve the efficiency of cloud infrastructure so that they can efficiently support loT big data applications, it is important to understand how these applications and the corresponding big data processing systems will perform in cloud computing environments. However, given the scalability and complex requirements of big data processing system5, an empirical evaluation on actual cloud infrastructure can hinder the development of timely and cost effective loT solutions. Therefore, a simulator supporting MT applications in cloud environment is highly demanded, but such work is still in its infancy. To fill this gap, we have designed and implemented IOTSim which supports and enables simulation of loT big data processing using MapReduce model in cloud computing environment. A real case study validates the efficacy of the simulator. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Internet of things (Iot) Big data Mapreduce Cloud computing programming model modelling and simulation

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Decision making with intuitionistic linguistic preference relations

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2019年第5期26卷 2004-2031页

作者： Meng, Fanyong Tang, Jie An, Qingxian Chen, Xiaohong Cent S Univ Sch Business Changsha 410083 Hunan Peoples R China Collaborat Innovat Ctr Forecast Nanjing 210044 Jiangsu Peoples R China Nanjing Univ Informat Sci & Technol Nanjing 210044 Jiangsu Peoples R China Hunan Univ Commerce Sch Accounting Changsha 410205 Hunan Peoples R China

To address the preferred and nonpreferred degrees of linguistic variables, this paper introduces intuitionistic linguistic preference relations (ILPRs) that apply intuitionistic linguistic variables (ILVs) to denote the decision makers' preferences. To judge the consistency of ILPRs, a consistent concept is introduced, and a consistency index is defined. When ILPRs are unacceptably inconsistent, a method to improve the consistency is introduced. Then, an approach to rank ILVs is introduced. In some situations where ILPRs might be incomplete, the consistency-based linear programming model is constructed to evaluate the missing values. Considering group decision making, a group consensus index is defined, and its several desirable properties are discussed. Meanwhile, an acceptability-based consistency and consensus approach is developed, and the associated example is offered to show the efficiency of the proposed procedure.

关键词： intuitionistic linguistic preference relation consistency index group consensus index aggregation operator programming model

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Two-Sided Stable Matching Decision-Making Method Considering Matching Intention under a Hesitant Fuzzy Environment

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Computer modeling in Engineering & Sciences 2023年第5期135卷 1603-1623页

作者： Qi Yue Zhibin Deng School of Management Shanghai University of Engineering ScienceShanghai201620China School of Information Management Jiangxi University of Finance and EconomicsNanchang330013China

In this paper,a stable two-sided matching(TSM)method considering the matching intention of agents under a hesitant fuzzy environment is *** method uses a hesitant fuzzy element(HFE)as its ***,the HFE preference matrix is transformed into the normalized HFE preference *** this basis,the distance and the projection of the normalized HFEs on positive and negative ideal solutions are ***,the normalized HFEs are transformed into agent *** the stable matching constraints,a multiobjective programming model with the objective of maximizing the satisfactions of two-sided agents is *** on the agent satisfaction matrix,the matching intention matrix of two-sided agents is *** to the agent satisfaction matrix and matching intention matrix,the comprehensive satisfaction matrix is set ***,the multiobjective programming model based on satisfactions is transformed into a multiobjective programming model based on comprehensive *** the G-S algorithm,the multiobjective programming model based on comprehensive satisfactions is solved,and then the best TSM scheme is ***,a terminal distribution example is used to verify the feasibility and effectiveness of the proposed method.

关键词： Two-sided matching stable matching hesitant fuzzy element matching intention programming model

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Consistency and consensus improvement models driven by a personalized normalization method with probabilistic linguistic preference relations

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INFORMATION FUSION 2021年 69卷 156-176页

作者： Tian, Zhang-peng Nie, Ru-xin Wang, Jian-qiang China Univ Min & Technol Sch Econ & Management Xuzhou 221116 Peoples R China Cent South Univ Sch Business Changsha 410083 Peoples R China

Probabilistic linguistic preference relation (PLPR) provides an effective and flexible tool with which preference degrees of decision-makers can be captured when they vacillatingly express linguistic preference values among several linguistic terms. Individual consistency and group consensus are two important research topics of PLPRs in group decision making (GDM). Considering the problems associated with these two topics, this study proposes a novel GDM framework with consistency-driven and consensus-driven optimization models based on a personalized normalization method for managing complete and incomplete PLPRs. First, existing limitations of the traditional normalization method for probabilistic linguistic term sets (PLTSs) managing ignorance information are specifically discussed. Given the potential valuable information hidden in PLTSs, a personalized normalization method is newly proposed through a two-stage decision-making process with a comprehensive fusion mechanism. Then, based on the proposed normalization method for PLTSs, consistency-driven optimization models that aim to minimize the overall adjustment amount of a PLPR are constructed to improve consistency. Moreover, the developed models are extended to improve consistency and estimate the missing values of an incomplete PLPR. Subsequently, a consensus-driven optimization model that aims to maximize group consensus by adjusting experts? weights is constructed to support the consensus-reaching process. Finally, an illustrative example, followed by some comparative analyses is presented to demonstrate the application and advantages of the proposed approach.

关键词： Group decision making Probabilistic linguistic term set programming model Incomplete probabilistic linguistic preference relation

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