Processing technique of ratings for ranking of alternatives (<scp>PROTERRA</scp>)

Selection of proper phase-change material (PCM) plays a crucial role in the development of latent heat thermal management module. Very often, selection of improper material leads to early failure of the product which results in huge economic loss. Most of the researchers utilize PCM in a particular application based on their experience and availability. The designer needs to consider all possible alternatives and evaluate in terms of various conflicting criteria or attributes. The optimal selection of PCM for a particular application is a multiattribute decision-making problem. Here, two evaluation techniques such as technique for order of preference by similarity to ideal solution (TOPSIS) and fuzzy TOPSIS are employed to select the optimal PCM for thermal management of electronic components. The analytical hierarchy process technique is utilized to determine the weight of the attributes. The present study considers 30 PCMs and 11 attributes for the selection of best PCM. The results are compared with both the methods and it is observed that RT 44 HC is found to be optimal PCM for thermal management of electronic components. The model is validated and results are found to be in good agreement with the existing experimental results.

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“…Step 5: Determine the relative closeness index to the ideal solution (C Ã i ). This can be obtained using Equation (23).…”

Section: Fuzzy Topsis Approachmentioning

confidence: 99%

“…It was found that AISI A2 steel is best for the given application. Kobryn and Prystrom 23 presented a new approach to multi‐criteria decision analysis known as processing technique of ratings for ranking of alternatives. This method was used in choice of shopping center selection.…”

Section: Introductionmentioning

confidence: 99%

Selection of phase‐change material for thermal management of electronic devices usingmulti‐attributedecision‐making technique

et al. 2020

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“…b) In some cases, the methods SAW and PROTERRA provided a slightly different assignment of the considered countries to a specific class of the innovation level. It may be assumed that this is the result, among other things, of the fact that the PROTERRA method reflects a disparity the values of the initial assessments for particular objects/options to a greater degree [as signaled by: Kobryń, Prystrom, 2018]. c) When comparing sets of countries assigned to each class level of innovation in the INPUTS and OUTPUTS, a proper correlation is not always visible.…”

Section: Analysis Of the Innovation Level In The European Union Countriesmentioning

confidence: 99%

Evaluation of the innovation level in the EU countries in 2016 and 2011

Prystrom

2020

Optimum

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Purpose – The main aim of this paper is to evaluate the innovation level in the European Union countries, but in a different way than it was adopted in the European Union reports (European Innovation Scoreboard, and earlier Innovation Union Scoreboard). Analyses were performed in relation to INPUTS-OUTPUTS. Research method – Two methods of multi-criteria analysis were used in the calculations. The first is the popular method known as Simple Additive Weighting. The second is the method known as Processing Technique of Ratings for Ranking of Alternatives, which was developed by the author of this article. Results – The obtained results of the innovation level were analyzed. Analysis concerned two periods: 2016 and 2011 and determined aggregate ratings, which characterized the innovation level of particular European Union countries. Four classes of the innovation level were defined: innovation leaders, good innovators, week innovators and innovation outsiders. Then, based on the calculated global ratings, European Union countries have been assigned to the appropriate classes. The results of this analysis were compared with the classification of the EU Member States in terms of the innovation level that IUS / EIS reports contain. Analyses in relation to INPUTS-OUTPUTS have also made it possible to assess the usefulness of indicators from the IUS / EIS reports to measure the innovation level in such a way. Originality /value / implications /recommendations – The analysis of the innovation level was carried out using two multi-criteria analysis methods.

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“…In literature a wide variety of procedures and multicriteria methods of decision support are described. There are methods based on the f unctional model (the American school) and the relation model (the European school) [4][5][6]. In road planning, technologies such as GIS (Geographic Information System) are becoming increasingly popular [7][8][9][10], as well as methods using genetic algorithms [11].…”

Section: Introductionmentioning

confidence: 99%

Bulletin of the Polish Academy of Sciences: Technical Sciences

Żabicki¹,

Gardziejczyk²

2020

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The article presents the methodology for selecting the optimal variant of the road on a regional level. The suggested methodology is based on a combination of criteria value normalization method and the variant assessment method. Based on survey studies conducted using the Delphi method, a starting list of criteria was designed and the significance of the individual groups of main criteria and sub-criteria was determined. The final assessments of the analysed variants are calculated based on the aggregation of the marks obtained for the normalization and assessment methods. The methodology can be divided into six stages: determining the variants for analysis, selecting the variant assessment criteria, creating the assessment matrix, normalizing criteria value, using the variant assessment method, variant ranking. The methodology was tested on the examples of planning a bypass of Mazury and Księżyno towns as a part of Regional Road 678 in Poland.

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Processing technique of ratings for ranking of alternatives (PROTERRA)

Cited by 7 publications

References 19 publications

Selection of phase‐change material for thermal management of electronic devices usingmulti‐attributedecision‐making technique

Selection of phase‐change material for thermal management of electronic devices usingmulti‐attributedecision‐making technique

Evaluation of the innovation level in the EU countries in 2016 and 2011

Bulletin of the Polish Academy of Sciences: Technical Sciences

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