Multiple attribute grey relational analysis using DEA and AHP

Pakkar, Mohammad Sadegh

doi:10.1007/s40747-016-0026-4

Cited by 17 publications

(9 citation statements)

References 19 publications

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“…U c . Owing to the propagation property of the power grid, the influences from other nodes need to be considered, thus the grey relational degree [21] is introduced in this paper. It is appropriate for both position and shape attributes measurement because of its ability to integrate local distance and global maximum and minimum distance for phasor sequences.…”

Section: U T Andmentioning

confidence: 99%

Dynamic Identification of Critical Nodes and Regions in Power Grid Based on Spatio-Temporal Attribute Fusion of Voltage Trajectory

et al. 2019

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Accurate identification of critical nodes and regions in a power grid is a precondition and guarantee for safety assessment and situational awareness. Existing methods have achieved effective static identification based on the inherent topological and electrical characteristics of the grid. However, they ignore the variations of these critical nodes and regions over time and are not appropriate for online monitoring. To solve this problem, a novel data-driven dynamic identification scheme is proposed in this paper. Three temporal and three spatial attributes are extracted from their corresponding voltage phasor sequences and integrated via Gini-coefficient and Spearman correlation coefficient to form node importance and relevance assessment indices. Critical nodes and regions can be identified dynamically through importance ranking and clustering on the basis of these two indices. The validity and applicability of the proposed method pass the test on various situations of the IEEE-39 benchmark system, showing that this method can identify the critical nodes and regions, locate the potential disturbance source accurately, and depict the variation of node/region criticality dynamically.

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Section: U T Andmentioning

confidence: 99%

Dynamic Identification of Critical Nodes and Regions in Power Grid Based on Spatio-Temporal Attribute Fusion of Voltage Trajectory

et al. 2019

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“…The method of AHP is based on three principles: first, structure of the model; second, comparative judgment of alternatives and decisionmaking criteria; third, synthesis of the priorities [35][36][37]. In recent research, the AHP methodology has been applied to solve many complex multiple criteria decision problems [1,23,26,30,31,39,40,43,44]. The process starts with organizing the decision problem in a hierarchical structure of decision elements (criteria and alternatives).…”

Section: Analytic Hierarchy Process (Ahp)mentioning

confidence: 99%

A hybrid decision support model using axiomatic fuzzy set theory in AHP and TOPSIS for multicriteria route selection

Singh

2018

Complex Intell. Syst.

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This paper presents a hybrid decision support model aimed to help the travelers in selecting best route among multiple alternatives. The proposed model consists of three parts: (i) analytic hierarchy process (AHP) to determine relative importance of route attributes, (ii) axiomatic fuzzy set (AFS) theory for description of alternative routes, and (iii) technique for order preference by similarity to ideal solution (TOPSIS)-based final selection. TOPSIS methodology is used to determine ranking order of alternative routes in multicriteria decision situations. In TOPSIS, the alternative routes are described using AFS theory to normalize the decision matrix for consistent rating of routes over attributes. The main advantage of the developed model is that it copes inconsistency caused by both, different types of fuzzy numbers and normalization methods. An illustrative example of route selection is presented to better understand the hybrid methodological process. A comparative analysis with an established multicriteria decision-making technique shows the effectiveness and validity of the hybrid model for route selection.

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“…Applications of the formal theories of system science in science of science are demonstrated, which reveals how system structural and behavioral complexities may be efficiently reduced [28]. As a popular and effective mathematical method, data envelopment analysis (DEA) has been deeply studied and widely used in many fields [2,22]. Bagheri et al [2] proposed a DEA-based method to multiobjective shortest path problem.…”

Section: Introductionmentioning

confidence: 99%

“…Bagheri et al [2] proposed a DEA-based method to multiobjective shortest path problem. Pakkar and Mohammad Sadegh [22] integrated DEA and analytic hierarchy process (AHP) approach to obtain attribute weights.…”

Section: Introductionmentioning

confidence: 99%

Using context-dependent DEA to analyze the efficiency of highly funded scientists in China

Xiang

Liang

Guo

et al. 2021

Complex Intell. Syst.

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Funding inputs and research outputs have always been two central issues in the science of science. In recent decades, research funding plays an increasingly important role in scientific research. Thus, it is progressively significant for management authorities to measure the research efficiency of highly funded scientists, which can be helpful for them to make effective policies. However, few researchers use quantitative analysis to study these issues. To promote the research in this field, we begin with collecting a dataset. This dataset contains research funding and other information from 345 highly funded scientists in Mainland China. Next, we use the dataset to measure the efficiency of highly funded scientists based on the data envelopment analysis. In this way, highly funded scientists are placed into several levels according to their research inputs and outputs. We also give their attractiveness and progress scores compared to other grades. The learning path for less efficient scientists is also provided. We find that highly funded scientists have relatively high efficiency in three kinds of projects, such as the Major Research Plan. Besides, the career length and career start year are demonstrated to have a limited impact on the highly funded scientists. These patterns are beneficial for the development of the scientific community and management authorities to make policies.

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Multiple attribute grey relational analysis using DEA and AHP

Cited by 17 publications

References 19 publications

Dynamic Identification of Critical Nodes and Regions in Power Grid Based on Spatio-Temporal Attribute Fusion of Voltage Trajectory

Dynamic Identification of Critical Nodes and Regions in Power Grid Based on Spatio-Temporal Attribute Fusion of Voltage Trajectory

A hybrid decision support model using axiomatic fuzzy set theory in AHP and TOPSIS for multicriteria route selection

Using context-dependent DEA to analyze the efficiency of highly funded scientists in China

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