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Distance measure and similarity measure have been applied to various multi-criteria decision-making environments, like talent selections, fault diagnoses and so on. Some improved distance and similarity measures have been proposed by some researchers. However, hesitancy is reflected in all aspects of life, thus the hesitant information needs to be considered in measures. Then, it can effectively avoid the loss of fuzzy information. However, regarding fuzzy information, it only reflects the subjective factor. Obviously, this is a shortcoming thatwill result in an inaccurate decision conclusion. Thus, based on the definition of a probabilistic neutrosophic hesitant fuzzy set (PNHFS), as an extended theory of fuzzy set, the basic definition of distance, similarity and entropy measures of PNHFS are established. Next, the interconnection among the distance, similarity and entropy measures are studied. Simultaneously, a novel measure model is established based on the PNHFSs. In addition, the new measure model is compared by some existed measures. Finally, we display their applicability concerning the investment problems, which can be utilized to avoid redundant evaluation processes.
Covering a wide range of notions concerning hesitant fuzzy set and its extensions, this book provides a comprehensive reference to the topic. In the case where different sources of vagueness appear simultaneously, the concept of fuzzy set is not able to properly model the uncertainty, imprecise and vague information. In order to overcome such a limitation, different types of fuzzy extension have been introduced so far. Among them, hesitant fuzzy set was first introduced in 2010, and the existing extensions of hesitant fuzzy set have been encountering an increasing interest and attracting more and more attentions up to now. It is not an exaggeration to say that the recent decade has seen the blossoming of a larger set of techniques and theoretical outcomes for hesitant fuzzy set together with its extensions as well as applications.As the research has moved beyond its infancy, and now it is entering a maturing phase with increased numbers and types of extensions, this book aims to give a comprehensive review of such researches. Presenting the review of many and important types of hesitant fuzzy extensions, and including references to a large number of related publications, this book will serve as a useful reference book for researchers in this field.
Neutrosophy as science has inclusive attributes that make possible to extract the contributions of neutral values in the analysis of data sets; it builds a unified field of logic for transdisciplinary studies that transcend the boundaries between natural and social sciences. Neutral philosophy seeks to solve the problems of indeterminacy that appear universally, to reform the current natural or social sciences, with an open methodology to promote innovation. The research products related in this special issue start from the premise that the difficulty is not the complexity of the social environment, but the instrumental obsolescence to observe, interpret and manage that complexity, there are bold approaches and proposals for valid solutions that come to enrich the universe of resolution through the use of neutral methods. In the last year, the use of tools related to neutrosophy and its application to the social sciences, modeling of social phenomena based on simulation agents, problems associated with health, psychology, education, environmental management and sustainability solutions and legal sciences has increased in the events organized by the Asociacion Latinoamericana de Ciencias Neutrosoficas (ALCN in Spanish). The methods of higher incidence are cognitive maps, neutral Iadovs, neutral Delphi, analytical hierarchy process methods, neutral statistics, neutral personality models, among the most significant. In this special issue, there is a predominance of research from Ecuadorian universities, demonstrating how neutrosophy and its methods are consolidated as instruments of analysis, inference and research validation.
Cognitive Intelligence with Neutrosophic Statistics in Bioinformatics investigates and presents the many applications that have arisen in the last ten years using neutrosophic statistics in bioinformatics, medicine, agriculture and cognitive science. This book will be very useful to the scientific community, appealing to audiences interested in fuzzy, vague concepts from which uncertain data are collected, including academic researchers, practicing engineers and graduate students. Neutrosophic statistics is a generalization of classical statistics. In classical statistics, the data is known, formed by crisp numbers. In comparison, data in neutrosophic statistics has some indeterminacy. This data may be ambiguous, vague, imprecise, incomplete, and even unknown. Neutrosophic statistics refers to a set of data, such that the data or a part of it are indeterminate in some degree, and to methods used to analyze the data. Introduces the field of neutrosophic statistics and how it can solve problems working with indeterminate (imprecise, ambiguous, vague, incomplete, unknown) data Presents various applications of neutrosophic statistics in the fields of bioinformatics, medicine, cognitive science and agriculture Provides practical examples and definitions of neutrosophic statistics in relation to the various types of indeterminacies
Contributors to current issue (listed in papers’ order): Noel Batista Hernández; C.V. Valenzuela Chicaiza; O.G. Arciniegas Paspuel; P.Y. Carrera Cuesta; D.R. Álvarez Hernández, C.E. Pozo Hernández; E.T. Mejía Álvarez; E.T. Villa Shagnay; S. Guerrón Enríquez; M.A. Tello Cadena; E.M. Pinos Medina; M. Jaramillo Burgos; F. Jara Vaca; R. Aguilar Berrezueta; E.M. Sandoval; B. Villalta Jadán; D. Palma Rivera; L.E. Valencia Cruzaty; M. Reyes Tomalá; C.M. Castillo Gallo, M.R. Velázquez; M.R. Mena Peralta; L. Ricardo Domínguez; D. Andrade Santamaría; X.Cangas Oña; M. Jaramillo Burgos; G.A. Calderón Vallejo; M. Orellana Cepeda; M.F. Galarza Villalba; M.S. Serrano Viteri; I. Ramos Castro; F. Vera Díaz; N.P. Lastra Calderón; D.L. Villarruel Delgado; D. Sandoval Malquín; E. Araujo Guerrón; A.R. Pupo Kairuz; D.V. Ponce Ruiz; F. Viteri Pita; F.S. Bustillo Mena; M.E. Narváez Jaramillo; M.A. Guerrero Ayala; D.A. Flores Jurado; O.M. Alonzo Pico; A.I. Utrera Velázquez; D.A. García Coello; E. Real Garlobo; C. Escobar Vinueza; R.C. Hernández Infante; M.E. Infante Miranda; F.R. Rivadeneira Enríquez; C.J. Galeano Páez; R.M. Montalvo Pantoja; K.A. Narváez Ortiz; S. Guaytarilla Salas; A.D. Rodríguez Lara; C.P. Rendón Tello; J. Almeida Blacio; R. Hurtado Guevara; L.G. Guallpa Zatán; H.J. Paillacho Chicaiza; J. Yaguar Mariño; M. Aguilar Carrión; D.A. Viteri Intriago; L. Álvarez Gómez; D. Ponce Ruiz; L.H. Carrión Hurtado; W.R. Salas Espín; M. Benalcázar Paladines; L. Moreira Rosales; L.K. Baque Villanueva; M.A. Mendoza; R. Salcedo; A.M. Izquierdo Morán; M.A. Checa Cabrera; B.J. Ipiales Chasiguano; A.L. Sandoval Pillajo; R. Díaz Vázquez; N.P. Becerra Arévalo; M.F. Calles Carrasco; John Luis Toasa Espinoza; M. Velasteguí Córdova; V.M. Parrales Carvajal; M.T. Macías Valverde; R. Aguas Pután; N. García Arias; N. Quevedo Arnaiz; S. Gavilánez Villamarín; M. Cleonares Borbor; M.F. Galarza Villalba; R. Aguas Pután; J. Mora Romero; J.E. Espìn Oviedo; L.J. Molina Chalacán; L.O. Albarracín Zambrano; E.J. Jalón Arias; A. Zúñiga Paredes; F. Smarandache; J. Estupiñán Ricardo; E. González Caballero; M.Y. Leyva Vázquez.
(Fuzzy) rough sets are closely related to (fuzzy) topologies. Neutrosophic rough sets and neutrosophic topologies are extensions of (fuzzy) rough sets and (fuzzy) topologies, respectively. In this paper, a new type of neutrosophic rough sets is presented, and the basic properties and the relationships to neutrosophic topology are discussed.
This book presents a collection of recent research on topics related to Pythagorean fuzzy set, dealing with dynamic and complex decision-making problems. It discusses a wide range of theoretical and practical information to the latest research on Pythagorean fuzzy sets, allowing readers to gain an extensive understanding of both fundamentals and applications. It aims at solving various decision-making problems such as medical diagnosis, pattern recognition, construction problems, technology selection, and more, under the Pythagorean fuzzy environment, making it of much value to students, researchers, and professionals associated with the field.
This book provides the readers with a thorough and systematic introduction to hesitant fuzzy theory. It presents the most recent research results and advanced methods in the field. These includes: hesitant fuzzy aggregation techniques, hesitant fuzzy preference relations, hesitant fuzzy measures, hesitant fuzzy clustering algorithms and hesitant fuzzy multi-attribute decision making methods. Since its introduction by Torra and Narukawa in 2009, hesitant fuzzy sets have become more and more popular and have been used for a wide range of applications, from decision-making problems to cluster analysis, from medical diagnosis to personnel appraisal and information retrieval. This book offers a comprehensive report on the state-of-the-art in hesitant fuzzy sets theory and applications, aiming at becoming a reference guide for both researchers and practitioners in the area of fuzzy mathematics and other applied research fields (e.g. operations research, information science, management science and engineering) characterized by uncertain ("hesitant") information. Because of its clarity and self contained explanations, the book can also be adopted as a textbook from graduate and advanced undergraduate students.
This book introduces readers to the novel concept of spherical fuzzy sets, showing how these sets can be applied in practice to solve various decision-making problems. It also demonstrates that these sets provide a larger preference volume in 3D space for decision-makers. Written by authoritative researchers, the various chapters cover a large amount of theoretical and practical information, allowing readers to gain an extensive understanding of both the fundamentals and applications of spherical fuzzy sets in intelligent decision-making and mathematical programming.
As a variation of fuzzy sets and intuitionistic fuzzy sets, neutrosophic sets have been developed to represent uncertain, imprecise, incomplete and inconsistent information that exists in the real world. Simplified neutrosophic sets (SNSs) have been proposed for the main purpose of addressing issues with a set of specific numbers. However, there are certain problems regarding the existing operations of SNSs, as well as their aggregation operators and the comparison methods. Therefore, this paper defines the novel operations of simplified neutrosophic numbers (SNNs) and develops a comparison method based on the related research of intuitionistic fuzzy numbers. On the basis of these operations and the comparison method, some SNN aggregation operators are proposed. Additionally, an approach for multi-criteria group decision-making (MCGDM) problems is explored by applying these aggregation operators. Finally, an example to illustrate the applicability of the proposed method is provided and a comparison with some other methods is made.