The objective of this chapter is to present and compare different fusion rules which can be used for Generalized Data Association (GDA) for multitarget tracking (MTT) in clutter. Most of tracking methods including Target Identification (ID) or attribute information are based on classical tracking algorithms such PDAF, JPDAF, MHT, IMM, etc. and either on the Bayesian estimation and prediction of...

The T-Spherical Fuzzy set (T-SPHFS) is one of the core simplifications quite a lot fuzzy concepts such as (FS), intuitionistic (ITFS), picture (PIFS), Q-rung orthopair (Q-RUOFS), etc. T-SPHFS reveals judgment by degree positive membership, abstinence, negative and refusal with relaxed conditions, this more powerful mathematical tool to pair inconsistent, indecisive, indistinguishable informatio...

We are interested in generalizations of the concepts of t-norm and t-conorm. In a companion chapter in this volume [14] we have presented a family of hypert-norms ∧q and a family of hyper-t-conorms ∨p. The prefix hyper is used to indicate multi-valued operations, also known as hyperoperations (see [5, 14]), i.e. operations which map pairs of elements to sets of elements. See [14] for the constr...

As a natural generalization of a measure space, Butnariu and Klement introduced T-tribes of fuzzy sets with T-measures. They gave a complete characterization of T-measures for a Frank triangular norm T. Here we characterize T-measures with respect to non-Frank strict triangular norms. We show the speciic roles of Frank triangular norms and a newly introduced family, nearly Frank triangular norm...

Over the last decade or so, significant advances have been made in two distinct technological areas: fuzzy logic and computational neutral networks. The theory of fuzzy logic provides a mathematical framework to capture the uncertainties associated with human cognitive processes, such as thinking and reasoning. Also, it provides a mathematical morphology to emulate certain perceptual and lingui...

Genetic Fuzzy Systems (GFSs) are models capable of integrating accuracy and high comprehensibility in their results. In the case of GFSs for classification, more emphasis has been given to improving the “Genetic” component instead of its “Fuzzy” counterpart. This paper focus on the Fuzzy Inference component to obtain a more accurate and interpretable system, presenting the so-called Genetic Pro...

In this paper we consider compound conditionals, Fr\'echet-Hoeffding bounds and the probabilistic interpretation of Frank t-norms. By studying solvability suitable linear systems, show under logical independence sharpness for prevision conjunctions disjunctions $n$ conditional events. We study set all coherent assessments on a family containing events their conjunction, by verifying that it is ...

Abstract The term “ q -Rung orthopair fuzzy sets ( $$q^{r}$$ q r OFSs)” refers to the collection of most differentiated ideas for expressing data in decision-making rules. OFSs can gradually adapt region information by adjusting parameter $$q \ge 1$$ ...

Optimal decision-making has become increasingly more difficult due to their inherent complexity exacerbated by uncertain and rapidly changing environmental conditions in which they are defined. Hence, with the aim of improving uncertainty management facilitating weighting criteria, this paper introduces an improved fuzzy Einstein Combined Compromise Solution (CoCoSo) methodology. Such a CoCoSo ...