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• A CODAS-based group decision model is designed for the T-spherical fuzzy context. • A T-spherical fuzzy Minkowski distance operator based on Heronian mean is proposed. • A novel ordered weighted Heronian Minkowski distance (TSFOWHMD) operator is advanced. • The TSFOWHMD operator is utilized to improve the CODAS method. • The applicability of the developed methodology is verified through a case study. T-spherical fuzzy sets (TSFSs) are more flexible and efficient tools to deal with ambiguous, uncertain and vague information in complex real-world decision-making problems than various extended intuitionistic fuzzy sets. This paper aims to develop a novel T-spherical fuzzy (TSF) Combinative Distance-Based ASsessment (CODAS) based on the Heronian Minkowski distance aggregation operator, this new method can capture interrelationship between input arguments. Some TSF weighted Heronian Minkowski distance (TSFWHMD) aggregation operators with generalization are developed based on Heronian mean and Minkowski-type distance, their properties are discussed as well as their families are analyzed. Furthermore, the TSF MAGDM methodology based on the improved CODAS is designed, where the Minkowski-type distance is used to define the TSF similarity for computing the expert weights and to construct the maximizing deviation method (MDM) for determining the attribute weights, respectively. The TSF ordered weighted Heronian Hamming distance (TSFOWHHD) and TSF ordered weighted Heronian Euclidean distance (TSFOWHED) operators derived from the TSFOWHMD operator are integrated into the CODAS method, which is an improved method for both measuring the deviation of the negative ideal solution from each alternative and capturing the correlation between attributes. Finally, the feasibility and practicality of developed methodology are illustrated with an example of CAE (Computer Aided Engineering) software selection for lithium-ion power battery (LiPB) design, sensitivity analysis and method comparisons are performed to elucidate the reliability and validity of the developed methodology. [ABSTRACT FROM AUTHOR]

Game theory is a powerful tool in modeling actual decision-making problems. In many cases, it is difficult for players to give a crisp value of payoff. To conquer this issue, various extensions of fuzzy sets have been introduced to represent the payoffs. Although type-2 intuitionistic fuzzy (T2IF) set (T2IFS) can solve the game problem effectively, sometimes players prefer to give the primary (secondary) membership and non-membership degrees with some approximate ranges rather than crisp values. T2IFS cannot express such uncertain payoffs. Thus, this paper initiates a new concept called type-2 interval-valued intuitionistic fuzzy (T2IVIF) set (T2IVIFS) which has stronger ability than T2IFS and interval-valued intuitionistic fuzzy set (IVIFS) in representing uncertain information. Hamacher operations of T2IVIFSs are given. Hamming and Euclidean distances between T2IVIFSs are defined respectively. Some Hamacher aggregation operators for T2IVIFSs are developed and some desirable properties are analyzed. Afterwards, an effective method is proposed for solving T2IVIF matrix game, which can make game results more accurate and reliable. An example of new energy vehicle industry development is provided to validate the proposed T2IVIF matrix game. Comparative analyses reveal that the matrix game in T2IVIF environment has better flexibility and reliability than that in T2IF and IVIF environments. [ABSTRACT FROM AUTHOR]

In the current scenario to access the data securely from wireless network, e-commerce and internet have become a great concern. As the technologies become commercialized in high markets growth, there is a need for effective and secure implementation to authenticate the identity of the people. Several biometric techniques that exploit physiological and behavioral traits of people have been developed for verification and identification of the individuals to make the system more reliable and secure. In this paper a unique method is used to extract the tragus feature of the ear. The proposed method used is an enhanced edge detection method. A line is drawn connecting the maximum coordinate, midpoint and the minimum coordinate. The mid region of this line gives the tragus of the ear. The ear feature tragus is taken because it is almost free from occlusions. In order to develop an efficient ear authentication system the feature level fusion is applied. The shape of the ear is also extracted. Then the tragus and the shape of the ear are combined together to form the fused template. The authentication rate of the system with the features of tragus, shape of the ear and the fused template is calculated using the Hamming distance technique and Euclidean distance method. The experimental result is carried out on two databases of IIT Delhi ear database and Mathematical Analysis of Images (AMI) ear database including occlusion. The proposed system is to prove that the accuracy of the ear biometric authentication system using Hamming distance technique in fused feature is better than the individual feature of tragus and the ear shape. When a single feature tragus is considered tragus is better than the ear shape as it is a unique feature of the ear. [ABSTRACT FROM AUTHOR]

Abstract: For intuitionistic fuzzy sets, it is argued that three dimensional distance functions are not necessary because two dimensional distance functions already provide a simple and concise expression of the distance between two intuitionistic fuzzy sets. However, we show that a three dimensional interpretation of intuitionistic fuzzy sets could give different comparison results to the ones obtained with their two dimensional counterparts. In addition to the existing distances, we define a three dimensional Hausdorff distance and compare its consistency with its two dimensional counterpart, which shows the usefulness of the three dimensional functions to model and provide the expression of the distance between two intuitionistic fuzzy sets. [Copyright &y& Elsevier]