Fuzzy Interval-Valued Multi Criteria Based Decision Making for Ranking Features in Multi-Modal 3D Face Recognition

Soodamani Ramalingam, 'Fuzzy interval-valued multi criteria based decision making for ranking features in multi-modal 3D face recognition', Fuzzy Sets and Systems, In Press version available online 13 June 2017. This is an Open Access paper, made available under the Creative Commons license CC BY 4.0 https://creativecommons.org/licenses/by/4.0/This paper describes an application of multi-criteria decision making (MCDM) for multi-modal fusion of features in a 3D face recognition system. A decision making process is outlined that is based on the performance of multi-modal features in a face recognition task involving a set of 3D face databases. In particular, the fuzzy interval valued MCDM technique called TOPSIS is applied for ranking and deciding on the best choice of multi-modal features at the decision stage. It provides a formal mechanism of benchmarking their performances against a set of criteria. The technique demonstrates its ability in scaling up the multi-modal features.Peer reviewedProo

Multicriteria optimization to select images as passwords in recognition based graphical authentication systems

Usability and guessability are two conflicting criteria in assessing the suitability of an image to be used as password in the recognition based graph -ical authentication systems (RGBSs). We present the first work in this area that uses a new approach, which effectively integrates a series of techniques in order to rank images taking into account the values obtained for each of the dimen -sions of usability and guessability, from two user studies. Our approach uses fuzzy numbers to deal with non commensurable criteria and compares two multicriteria optimization methods namely, TOPSIS and VIKOR. The results suggest that VIKOR method is the most applicable to make an objective state-ment about which image type is better suited to be used as password. The paper also discusses some improvements that could be done to improve the ranking assessment

Evaluation of e-learning web sites using fuzzy axiomatic design based approach

High quality web site has been generally recognized as a critical enabler to conduct online business. Numerous studies exist in the literature to measure the business performance in relation to web site quality. In this paper, an axiomatic design based approach for fuzzy group decision making is adopted to evaluate the quality of e-learning web sites. Another multi-criteria decision making technique, namely fuzzy TOPSIS, is applied in order to validate the outcome. The methodology proposed in this paper has the advantage of incorporating requirements and enabling reductions in the problem size, as compared to fuzzy TOPSIS. A case study focusing on Turkish e-learning websites is presented, and based on the empirical findings, managerial implications and recommendations for future research are offered

FUZZY COMPARATIVE CONCORDANCE ANALYSIS. Proposal and evaluation by a case study

In this paper it is proposed a fuzzy multiple attribute analysis, that we have called comparative concordance, as a help instrument to the decision-making process in an environment of lack of precise information as it generally is the decision-making in regional planning. Through an application to the selection of proceeding programs of the Environmental Plan of Andalusia, 1995-2000, it will be compared to other methods.fuzzy sets, multiple attribute decision, environmental planning

Type-2 neutrosophic number based multi-attributive border approximation area comparison (MABAC) approach for offshore wind farm site selection in USA.

The technical, logistical, and ecological challenges associated with offshore wind development necessitate an extensive site selection analysis. Technical parameters such as wind resource, logistical concerns such as distance to shore, and ecological considerations such as fisheries all must be evaluated and weighted, in many cases with incomplete or uncertain data. Making such a critical decision with severe potential economic and ecologic consequences requires a strong decision-making approach to ultimately guide the site selection process. This paper proposes a type-2 neutrosophic number (T2NN) fuzzy based multi-criteria decision-making (MCDM) model for offshore wind farm (OWF) site selection. This approach combines the advantages of neutrosophic numbers sets, which can utilize uncertain and incomplete information, with a multi-attributive border approximation area comparison that provides formulation flexibility and easy calculation. Further, this study develops and integrates a techno-economic model for OWFs in the decision-making. A case study is performed to evaluate and rank five proposed OWF sites off the coast of New Jersey. To validate the proposed model, a comparison against three alternative T2NN fuzzy based models is performed. It is demonstrated that the implemented model yields the same ranking order as the alternative approaches. Sensitivity analysis reveals that changing criteria weightings does not affect the ranking order

Identification and ranking of effective factors of marketing (controllable) to receive the services from free zone with MADM approach

This study applies the fuzzy MCDM (multicriteria decision making) to evaluate the services Performance in free trade zone. Performance evaluation is an important issue for managers, since it can be used as a reference in decision making with regard to performance improvement, specially teaching performance improvement. For this purpose, in this study, we use fuzzy set theory for the measurement of performance and apply AHP in obtaining criteria weight and TOPSIS in ranking. A fuzzy MCDM is an approach for evaluating decision alternatives involving subjective judgments made by a group of decision makers. A pairwise comparison process is used to help individual decision makers make comparative judgments, and a linguistic rating method is used for making absolute judgments

Evaluating high risks in large-scale projects using an extended VIKOR method under a fuzzy environment

The complexity of large-scale projects has led to numerous risks in their life cycle. This paper presents a new risk evaluation approach in order to rank the high risks in large-scale projects and improve the performance of these projects. It is based on the fuzzy set theory that is an effective tool to handle uncertainty. It is also based on an extended VIKOR method that is one of the well-known multiple criteria decision-making (MCDM) methods. The proposed decision-making approach integrates knowledge and experience acquired from professional experts, since they perform the risk identification and also the subjective judgments of the performance rating for high risks in terms of conflicting criteria, including probability, impact, quickness of reaction toward risk, event measure quantity and event capability criteria. The most notable difference of the proposed VIKOR method with its traditional version is just the use of fuzzy decision-matrix data to calculate the ranking index without the need to ask the experts. Finally, the proposed approach is illustrated with a real-case study in an Iranian power plant project, and the associated results are compared with two well-known decision-making methods under a fuzzy environment

Identification and ranking of effective factors of marketing (controllable) to receive the services from free zone with MADM approach

This study applies the fuzzy MCDM (multicriteria decision making) to evaluate the services Performance in free trade zone. Performance evaluation is an important issue for managers, since it can be used as a reference in decision making with regard to performance improvement, specially teaching performance improvement. For this purpose, in this study, we use fuzzy set theory for the measurement of performance and apply AHP in obtaining criteria weight and TOPSIS in ranking. A fuzzy MCDM is an approach for evaluating decision alternatives involving subjective judgments made by a group of decision makers. A pairwise comparison process is used to help individual decision makers make comparative judgments, and a linguistic rating method is used for making absolute judgments

Identification and ranking of effective factors of marketing (controllable) to receive the services from free zone with MADM approach

This study applies the fuzzy MCDM (multicriteria decision making) to evaluate the services Performance in free trade zone. Performance evaluation is an important issue for managers, since it can be used as a reference in decision making with regard to performance improvement, specially teaching performance improvement. For this purpose, in this study, we use fuzzy set theory for the measurement of performance and apply AHP in obtaining criteria weight and TOPSIS in ranking. A fuzzy MCDM is an approach for evaluating decision alternatives involving subjective judgments made by a group of decision makers. A pairwise comparison process is used to help individual decision makers make comparative judgments, and a linguistic rating method is used for making absolute judgments

Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences

Mathematical fuzzy logic (MFL) specifically targets many-valued logic and has significantly contributed to the logical foundations of fuzzy set theory (FST). It explores the computational and philosophical rationale behind the uncertainty due to imprecision in the backdrop of traditional mathematical logic. Since uncertainty is present in almost every real-world application, it is essential to develop novel approaches and tools for efficient processing. This book is the collection of the publications in the Special Issue “Mathematical Fuzzy Logic in the Emerging Fields of Engineering, Finance, and Computer Sciences”, which aims to cover theoretical and practical aspects of MFL and FST. Specifically, this book addresses several problems, such as:- Industrial optimization problems- Multi-criteria decision-making- Financial forecasting problems- Image processing- Educational data mining- Explainable artificial intelligence, etc