Forecasting Model Based on Neutrosophic Logical Relationship and Jaccard Similarity


Book Description

The daily fluctuation trends of a stock market are illustrated by three statuses: up, equal, and down. These can be represented by a neutrosophic set which consists of three functions—truth-membership, indeterminacy-membership, and falsity-membership.




Forecasting Model Based on Neutrosophic Logical Relationship and Jaccard Similarity


Book Description

The daily fluctuation trends of a stock market are illustrated by three statuses: up, equal, and down. These can be represented by a neutrosophic set which consists of three functions—truth-membership, indeterminacy-membership, and falsity-membership.




Symmetry, vol. 9, issue 10 / 2007 - Special Issue: Neutrosophic Theories Applied in Engineering


Book Description

This Special Issue presents original research papers that report on state-of-the-art and recent advancements in neutrosophic sets and logic in soft computing, artificial intelligence, big and small data mining, decision making problems, and practical achievements.




A Forecasting Model Based on Multi-Valued Neutrosophic Sets and Two-Factor, Third-Order Fuzzy Fluctuation Logical Relationships


Book Description

Making predictions according to historical values has long been regarded as common practice by many researchers. However, forecasting solely based on historical values could lead to inevitable over-complexity and uncertainty due to the uncertainties inside, and the random influence outside, of the data.







A Neutrosophic Forecasting Model for Time Series Based on First-Order State and Information Entropy of High-Order Fluctuation


Book Description

In time series forecasting, information presentation directly affects prediction efficiency. Most existing time series forecasting models follow logical rules according to the relationships between neighboring states, without considering the inconsistency of fluctuations for a related period. In this paper, we propose a new perspective to study the problem of prediction, in which inconsistency is quantified and regarded as a key characteristic of prediction rules. First, a time series is converted to a fluctuation time series by comparing each of the current data with corresponding previous data.




Neutrosophic Sets and Systems, Book Series, Vol. 34, 2020. An International Book Series in Information Science and Engineering. Special Issue: Social Neutrosophy in Latin America


Book Description

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.




Neutrosophic Sets and Systems, Vol. 34, 2020. Special Issue: Social Neutrosophy in Latin America


Book Description

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.




Fuzzy Supervised Multi-Period Time Series Forecasting


Book Description

The goal of this paper is to propose a new method for fuzzy forecasting of time series with supervised learning and k-order fuzzy relationships. In the training phase based on k previous historical periods, a multidimensional matrix of fuzzy dependencies is constructed. During the test stage, the fitted fuzzy model is run for validating the observations and each output value is predicted by using a fuzzy input vector of k previous intervals. The proposed algorithm is verified by a benchmark dataset for fuzzy time series forecasting. The results obtained are similar or better than those of other fuzzy time series prediction methods. Comparative analysis shows the high potential of the new algorithm as an alternative to fuzzy prediction and reveals some opportunities for its further improvement.