1,721,294 research outputs found
A combined fuzzy group decision making framework to evaluate agile supply chain enablers
No full textTo support an effective agile supply chain management, we examine in this paper agile supply chain enablers in an analytical context We propose a new integrated method combining fuzzy logic, decision making trial and evaluation laboratory and analytic network process to determine the most important factors of agility in the supply chain management We also demonstrate the potentials of the methodology by a case study in an Turkish automotive industr
Dealing with missing values in nuclear safeguards evaluation
No full textNuclear Safeguards are a set of activities to verify that a State is living up to its international undertakings not to use nuclear programs for nuclear weapons purposes. In the nuclear safeguards evaluation, the experts from International Atomic Energy Agency evaluate and aggregate different indicators to make the final decision. However, some of the expert evaluation values are usually missing. In this study a cumulative belief-degrees based approach is proposed to aggregate die expert evaluations and deal with the missing values. An index is employed to find the reliability of the final result. A numerical example is provided to illustrate the applicability of the methodology
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Analyzing environmental samples in nuclear safeguards evaluation by a cumulative belief degrees approach
No full textIn this study we apply a cumulative belief degrees approach to an environmental sampling example in nuclear safeguards evaluation. Transformation formulas for each indicator are defined for distinguishing anthropogenic natural uranium from mineral uranium. An order weighted averaging operator-based aggregation method is proposed to make a final decision. The methodology is illustrated by a numerical example
Evaluation of road safety performance indicators using OWA operators
No full textRoad safety performance indicators have recently been proposed as a useful instrument in comparing countries on their performance of road safety risk factors. New insights can be gained in case one road safety index is composed of all risk indicators. The safety performance can be evaluated, countries can be ranked, trends identified and the impact of measures assessed. However, the aggregation process is still unclear in this context. In this paper, the use of ordered weighted averaging (OWA) operators will be experimented for an evaluation of road safety performance indicators. More specifically, several basic and more advanced aggregation operators will be applied to our indicator data set and the final index scores are then compared to the number of road fatalities per million inhabitants. It is demonstrated that compensation should not be allowed too much in the road safety context. All indicators should be incorporated in the final index to some extent and weaker performances should be stressed more
Learning and clustering of fuzzy cognitive maps for travel behaviour analysis
No full textIn modern society, more and more attention is given to the increase in public transportation or bike use. In this regard, one of the most important issues is to find and analyse the factors influencing car dependency and the attitudes of people in terms of preferred transport mode. Although the individuals’ transport behavioural modelling is a complex task, it has a notable social and economic impact. Thus, in this paper, fuzzy cognitive maps are explored to represent the behaviour and operation of such complex systems. This soft-computing technique allows modelling how the travellers make decisions based on their knowledge of different transport modes properties at different levels of abstraction. These levels correspond to the hierarchy perception including different scenarios of travelling, different benefits of choosing a specific travel mode, and different situations and attributes related to those benefits. We use learning and clustering of fuzzy cognitive maps to describe travellers’ behaviour and change trends in different abstraction levels. Cluster estimations are done before and after the learning of the maps, in order to compare people’s way of thinking if only considering an initial view of a transport mode decision for a daily activity, and when they really have a deeper reasoning process in view of benefits and consequences. The results of this study will help transportation policy decision makers in better understanding of people’s needs and consequently will help them actualizing different policy formulations and implementations
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