scholarly journals Evaluation of the marine economic development quality in Qingdao based on entropy and grey relational analysis

2019 ◽  
Vol 2 (1) ◽  
pp. 29-38 ◽  
Author(s):  
Peide Liu ◽  
Xiaoxiao Liu ◽  
Hongyu Yang
Keyword(s):  
Economic Development ◽  
Grey Relational Analysis ◽  
Evaluation Index System ◽  
Entropy Model ◽  
Content Type ◽  
Relational Analysis ◽  
Development Capacity ◽  
Marine Economy ◽  
Grey Relational

Purpose Accurately judging the quality of marine economic development is the premise of grasping the level and status of marine economic development. In order to scientifically evaluate the development quality of regional marine economy, the purpose of this paper is to select the marine area of Qingdao as the research object, and construct a marine economic development quality evaluation index system with 16 indicators. Design/methodology/approach The raw data is normalized by the range conversion method, and the weight of the index is determined by the information entropy model. Further, the grey relational analysis (GRA) method is used to evaluate the quality of marine economic development of Qingdao from 2012 to 2017. Findings The results show that the marine economic development capacity of Qingdao is with the generally increasing trend, the total marine economy is with on the rising trend, the marine storage and transportation capacity, and marine ecological environment are first decreased, and then increased. The utilization of marine resources is generally decreasing, and the comprehensive management of oceans varies with the changes of environment and economy. Therefore, in view of the development capacity of marine economy, the coordinated development of economy and environment should be carried out. Originality/value This paper uses the GRA to evaluate the quality of marine economic development and provides a reference for the development of marine economy in Qingdao.

Water abundance analysis of aquifer in coal roof based on grey relational analysis and analytic hierarchy process

2016 ◽  
Vol 11 (2) ◽  
pp. 487-494
Author(s):  
Li Bo
Keyword(s):  
Analytic Hierarchy Process ◽  
Grey Relational Analysis ◽  
Evaluation Model ◽  
Evaluation Index System ◽  
Analytic Hierarchy ◽  
Water Abundance ◽  
Relational Analysis ◽  
Major Factors ◽  
Grey Relational ◽  
Hierarchy Process

As water abundance of aquifer of coal roof significantly influences roof water hazard, evaluating and grading the degree of water abundance are important in practical application. By analyzing the influencing factors of water abundance of aquifer, an evaluation index system and a grading standard for the water abundance were established integrating quantitative and qualitative indexes. Meanwhile, according to the grey relation characteristics of the major factors influencing water abundance, a multi-factor evaluation model for water abundance was constructed based on grey relational analysis and analytic hierarchy process. The model can objectively reveal the influences of the multiple factors on the evaluation of water abundance. Furthermore, the method was verified by comprehensively evaluating the water abundance of the aquifer of coal roof in a working face of Pingshuo Coal Mine in Shanxi, China using the model. The method provides basis for the research on the evaluation of water abundance of aquifer in coal roof.

scholarly journals Influence of Milling Process Parameters on Machined Surface Quality of Carbon Fibre Reinforced Polymer (CFRP) Composites Using Taguchi Analysis and Grey Relational Analysis

2021 ◽  
Vol 13 (6) ◽  
Author(s):  
I.S.N.V.R. Prasanth ◽  
◽  
S. Nikitha ◽  
R. Pulsingh ◽  
M. Sampath ◽  
...  
Keyword(s):  
Carbon Fibre ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Relational Analysis ◽  
Reinforced Polymer ◽  
Carbon Fibre Reinforced Polymer ◽  
Fibre Reinforced Polymer ◽  
Grey Relational ◽  
Scanning Electron

The article presents the milled surface quality of Uni-Directional Carbon Fibre Reinforced Polymer (UD-CFRP) composites from Taguchi’s and grey relational analysis. The novelty is demonstrating the possibility of detecting the surface defects in polymer composites during milling using SEM analysis. The material used for this study is UD-CFRP composite laminates and made by hand-layup process. All the milling operations were carried out using a solid tungsten carbide end milling tool and experiments conducted on CNC milling machine. Taguchi L9, 3-level orthogonal array was considered for experimentation. Analysis of Variance (ANOVA) was conducted to explore the significance of each individual input process parameters on multiple performance characteristics. Optimal process parameters are thoroughly validated by grey relational grade achieved by the grey relational analysis for multi performance characteristics. Finally, experimental results were correlated and analyzed with scanning electron micrographs using Scanning Electron Microscope (SEM).

Quality improvement of smart senior care service platform in China based on grey relational analysis and Fuzzy-QFD

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Lan Xu ◽  
Yu Zhang
Keyword(s):  
Quality Improvement ◽  
Grey Relational Analysis ◽  
Care Service ◽  
The Elderly ◽  
Service Platform ◽  
Content Type ◽  
Relational Analysis ◽  
Improvement Method ◽  
Grey Relational ◽  
Quality Improvement Method

PurposeSmart senior care industry in China currently faces a series of practical difficulties such as an imbalance in the demand and supply structure, service products unable to cater to the actual needs of the elderly and a low degree of marketization. This study therefore proposes using grey relational analysis and the Fuzzy-quality function development (QFD) quality improvement method to help solve these problems.Design/methodology/approachThe proposed method converts the fuzzy requirements of the elderly into the technical characteristics of technologically augmented senior care service products. It then, uses the QFD relationship matrix, combined with grey relational analysis, to analyze the relationship between the needs of elderly and the converted technical characteristics, and subsequently identifies key technical characteristics.FindingsResults show that an improvement in the smart senior care service platform according to the differences of the elderly's preferences can significantly improve users' satisfaction with the service in addition to enhancing market competitiveness of the technologically assisted senior care service products.Originality/valueA novel method to improve the need of smart senior care is proposed by considering age difference. The proposed grey relational analysis and Fuzzy-QFD quality improvement method can help improve the service quality of the smart senior care service platform.

Negative grey relational model and measurement of the reverse incentive effect of fields medal

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sifeng Liu
Keyword(s):  
Grey Relational Analysis ◽  
Research Output ◽  
Analysis Model ◽  
Content Type ◽  
Relational Analysis ◽  
Fields Medal ◽  
Definition Of ◽  
Grey Relational ◽  
Analysis Models ◽  
The Relationship

PurposeThe purpose of this paper is to construct some negative grey relational analysis models to measure the relationship between reverse sequences.Design/methodology/approachThe definition of reverse sequence has been given at first based on analysis of relative position and change trend of sequences. Then, several different negative grey relational analysis models, such as the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model have been put forward based on the corresponding common grey relational analysis models. The properties of the new models have been studied.FindingsThe negative grey relational analysis models proposed in this paper can solve the problem of relationship measurement of reverse sequences effectively. All the new negative grey relational degree satisfying the requirements of normalization and reversibility.Practical implicationsThe proposed negative grey relational analysis models can be used to measure the relationship between reverse sequences. As a living example, the reverse incentive effect of winning Fields Medal on the research output of winners is measured based on the research output data of the medalists and the contenders using the proposed negative grey relational analysis model.Originality/valueThe definition of reverse sequence and the negative grey similarity relational analysis model, the negative grey absolute relational analysis model, the negative grey relative relational analysis model, the negative grey comprehensive relational analysis model and the negative Deng’s grey relational analysis model are first proposed in this paper.

Application of grey relational analysis to expose individual student's cognitive difficulties in English public speaking

2014 ◽  
Vol 4 (2) ◽  
pp. 232-249
Author(s):  
Yow-jyy Joyce Lee ◽  
Lawrence W. Lan
Keyword(s):  
Grey Relational Analysis ◽  
Teaching And Learning ◽  
Public Speaking ◽  
Learning Difficulties ◽  
Cognitive Learning ◽  
Content Type ◽  
Cognitive Difficulties ◽  
Relational Analysis ◽  
Grey Relational ◽  
Grey Relation

Purpose – The purpose of this paper is to propose a formative assessment framework to expose individual student's cognitive learning difficulties in English public speaking. The paper aims to provide student feedback and information during the teaching and learning process. A grey student-construct (S-C) chart is developed to represent the students’ cognitive mapping of the speech difficulties in relation to their overall speech conceptualization. This grey S-C chart can facilitate the instructors to ameliorate the classroom teaching and learning performance in English public speaking. Design/methodology/approach – In total, 26 students in a class of English Speech and Rhetoric participate in the experiment – each student views the online video segments of a great speaker's speech, and then decides what segments would best support the speaking skill constructs and also reflects on his/her own difficulties in the same constructs. The grey relational analysis (GRA) method is used to analyze the empirical data. The individual student's construct localization grey relation grade values are calculated to rank the grey relation for both students and constructs. Accordingly, a grey S-C matrix is constructed and a grey S-C chart can thus be developed. Findings – The grey S-C chart manifestly displays the cognitive difficulties in sequences of both students and constructs. Practical implications – According to the grey S-C chart, the instructors may modify teaching strategies to enhance the overall classroom performance. The students may adjust learning strategies to eliminate their specific difficulties. Offering individualized advanced and remedial practices to those largely deviating from the norm is also possible. Originality/value – The study is the first of its kind to apply the GRA method to expose individual student's cognitive learning difficulties in English public speaking. The grey S-C chart is novel in education literature, which can reveal individual student's learning difficulty patterns.

Grey relational analysis between Turkey’s macroeconomic indicators and domestic savings

2017 ◽  
Vol 7 (1) ◽  
pp. 45-59 ◽  
Author(s):  
Engin Duran ◽  
Burcu Uzgur Duran ◽  
Diyar Akay ◽  
Fatih Emre Boran
Keyword(s):  
Grey Relational Analysis ◽  
Data Set ◽  
Content Type ◽  
Relational Analysis ◽  
Domestic Savings ◽  
Macroeconomic Indicators ◽  
Private Savings ◽  
Grey Relational ◽  
High Degree ◽  
The Relationship

Purpose It is of great importance for economy policy makers to comprehend the relationship between macroeconomic indicators and domestic savings, and to find out which indicator is more determinative on the dynamics of domestic savings. The purpose of this paper is to analyze the degree of relationship between Turkey’s domestic savings and selected macroeconomic indicators. Design/methodology/approach To examine the relationship, grey relational analysis (GRA) is applied together with the entropy method to determine the weight of the indicators according to the information level they provide. The analysis covers the data of the period from 1990 to 2014. In practice, however, the data set is used by dividing into two separate periods including before and after the 2001 crisis. Findings The results indicate that the unemployment rate and the gross domestic product (GDP) per capita growth stand out with a relatively high degree of relationship for the period before 2001. When examining the post-2001 period, current balance ratio and GDP growth are ascertained as indicators which have a high degree of relationship with domestic savings. Practical implications These indicators have different aspects affecting both public and private savings. Therefore, it may be beneficial to concentrate on these indicators when designing a policy in order to increase the domestic saving rate. Originality/value There are many econometric models used for investigating Turkey’s macroeconomic indicators and domestic savings causality. But before now, any study which investigates relationship between macroeconomic indicators and domestic savings by GRA could not be encountered. Using one of the newest developed theories (the grey systems theory) for this subject is the significance of this research.

Optimization of process parameters on drilling of natural fibres reinforced in epoxy resin matrices using Taguchi–Grey relational analysis

2020 ◽  
Vol 16 (5) ◽  
pp. 937-949
Author(s):  
Alagappan K M ◽  
Vijayaraghavan S ◽  
Jenarthanan M P ◽  
Giridharan R
Keyword(s):  
Epoxy Resin ◽  
Process Parameters ◽  
Grey Relational Analysis ◽  
Natural Fibres ◽  
Content Type ◽  
Relational Analysis ◽  
Optimization Of Process Parameters ◽  
Machining Force ◽  
Drill Diameter ◽  
Grey Relational

PurposeThe purpose of this paper is to identify the ideal process parameters to be set for the drilling of hybrid fibre-reinforced polymer (FRP) (kenaf and banana) composite using High-Speed Steel drill bits (5, 10, 15 mm) coated with tungsten carbide by means of statistical reproduction of the delamination factor and machining force using Taguchi–Grey Relational Analysis.Design/methodology/approachThe contemplated process parameters are Feed, Speed and Drill Diameter. The trials were carried out by taking advantage of the L-27 factorial design by Taguchi. Three factors, the three level Taguchi Orthogonal Array design in Grey Relational Analysis was used to carry out the trial study. Video Measuring System was used to identify the damage around the drill region. “Minitab 18” was used to examine the data collected by taking advantage of the various statistical and graphical tools available. Examination of variance is used to legitimize the model in identifying the most notable parameter.FindingsThe optimised set of input parameters were found out successfully which are as follows: Feed Rate: 450 mm/min, Cutting Speed: 3,000 rpm and Drill Diameter of 5 mm. When these values are fed in as input the optimised output is being obtained. From ANOVA analysis, it is apparent that the Speed (contribution of 92.6%) is the most influencing parameter on the delamination factor and machining force of the FRP material.Originality/valueOptimization of process parameters on drilling of natural fibres reinforced in epoxy resin matrices using Taguchi–Grey Relational Analysis has not been previously explored.

A hybrid grey based artificial neural network and C&R tree for project portfolio selection

2017 ◽  
Vol 24 (3) ◽  
pp. 651-665 ◽  
Author(s):  
Farshad Faezy Razi ◽  
Seyed Hooman Shariat
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Decision Tree ◽  
Portfolio Selection ◽  
Grey Relational Analysis ◽  
Project Portfolio ◽  
Content Type ◽  
Relational Analysis ◽  
Project Portfolio Selection ◽  
Grey Relational

Purpose The purpose of this paper is twofold: the selection of project portfolios through hybrid artificial neural network algorithms, feature selection based on grey relational analysis, decision tree and regression; and the identification of the features affecting project portfolio selection using the artificial neural network algorithm, decision tree and regression. The authors also aim to classify the available options using the decision tree algorithm. Design/methodology/approach In order to achieve the research goals, a project-oriented organization was selected and studied. In all, 49 project management indicators were chosen from A Guide to the Project Management Body of Knowledge (PMBOK Guide), and the most important indicators were identified using a feature selection algorithm and decision tree. After the extraction of rules, decision rule-based multi-criteria decision making matrices were produced. Each matrix was ranked through grey relational analysis, similarity to ideal solution method and multi-criteria optimization. Finally, a model for choosing the best ranking method was designed and implemented using the genetic algorithm. To analyze the responses, stability of the classes was investigated. Findings The results showed that projects ranked based on neural network weights by the grey relational analysis method prove to be better options for the selection of a project portfolio. The process of identification of the features affecting project portfolio selection resulted in the following factors: scope management, project charter, project management plan, stakeholders and risk. Originality/value This study presents the most effective features affecting project portfolio selection which is highly impressive in organizational decision making and must be considered seriously. Deploying sensitivity analysis, which is an innovation in such studies, played a constructive role in examining the accuracy and reliability of the proposed models, and it can be firmly argued that the results have had an important role in validating the findings of this study.

scholarly journals Integrated analytical hierarchy process and grey relational analysis approach to measure supply chain complexity

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sujan Piya ◽  
Ahm Shamsuzzoha ◽  
Mohammed Khadem ◽  
Mahmoud Al Kindi
Keyword(s):  
Mathematical Model ◽  
Supply Chain ◽  
Analytical Hierarchy Process ◽  
Grey Relational Analysis ◽  
Extensive Literature ◽  
Content Type ◽  
Relational Analysis ◽  
Grey Relational ◽  
Hierarchy Process

PurposeThe purpose of this paper is to understand the drivers that create complexity in the supply chain and develop a mathematical model to measure the level of supply chain complexity (SCC).Design/methodology/approachThrough extensive literature review, the authors discussed various drivers of SCC. These drivers were classified into five dimensions based on expert opinion. Moreover, a novel hybrid mathematical model was developed by integrating analytical hierarchy process (AHP) and grey relational analysis (GRA) methods to measure the level of SCC. A case study was conducted to demonstrate the applicability of the developed model and analyze the SCC level of the company in the study.FindingsThe authors identified 22 drivers of SCC, which were further clustered into five complexity dimensions. The application of the developed model to the company in the case study showed that the SCC level of the company was 0.44, signifying that there was a considerable scope of improvement in terms of minimizing complexity. The company that serves as the focus of this case study mainly needs improvement in tackling issues concerning government regulation, internal communication and information sharing and company culture.Originality/valueIn this paper, the authors propose a model by integrating AHP and GRA methods that can measure the SCC level based on various complexity drivers. The combination of such methods, considering their ability to convert the inheritance and interdependence of drivers into a single mathematical model, is preferred over other techniques. To the best of the authors' knowledge, this is the first attempt at developing a hybrid multicriteria decision-based model to quantify SCC.

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