Application of Fuzzy Calculation Methodology to Check the Correctness of Forecast Calculations of Financial Return in a Global Context

Fuzzy set theory is circumscribed to the need to broaden the scope of classical mathematics meaning potentiation possibilities of mathematical modeling of real world systems. One can appreciate that the nature of reality and our way of thinking and the symbolism of interpersonal communication languages ​​are also sources of uncertainty, imprecision, vagueness, ambiguity. The imperative of handling properties not necessarily "perfect determinable", namely "vaguely defined" (but with a measurable degree of uncertainty) has led to the imposition of fuzzy sets theory, which proved to be the systematic frame suitable to management of ambiguity and imprecision. Using fuzzy numbers involves some difficulties (related for example to the relaxation of equalities relative to invertible elements) that could be surpassed by using fuzzy numbers characterizing through families of "confidence intervals"

The Application of Fuzzy Logic for the Choice of Supplier

Diplomová práce se bude zabývat vyhodnocením výběrového řízení vhodného dodavatele inventárního systému za využití pokročilých metod umělé inteligence. K řešení bude využito programu MS Excel, programového prostředí MATLAB a jeho Toolboxů.Master's thesis will deal with the evaluation of the tender for supplier of inventory system using advanced artificial intelligence methods. For solution will be used MS Excel and MATLAB programming and its Toolboxes.

Suspended sediment estimation of Ekbatan reservoir sub basin using Adaptive Neuro-Fuzzy Inference Systems (ANFIS), Artificial Neural Networks (ANN), and sediment rating curves (SRC)

River morphodynamics and sediment transportMechanics of sediment transpor

Many-Valued And Fuzzy Logic Systems From The Viewpoint Of Classical Logic

The thesis that the two-valued system of classical logic is insufficient to explanation the various intermediate situations in the entity, has led to the development of many-valued and fuzzy logic systems. These systems suggest that this limitation is incorrect. They oppose the law of excluded middle (tertium non datur) which is one of the basic principles of classical logic, and even principle of non-contradiction and argue that is not an obstacle for things both to exist and to not exist at the same time. However, contrary to these claims, there is no inadequacy in the two-valued system of classical logic in explanation the intermediate situations in existence. The law of exclusion and the intermediate situations in the external world are separate things. The law of excluded middle has been inevitably accepted by other logic systems which are considered to reject this principle. The many-valued and the fuzzy logic systems do not transcend the classical logic. Misconceptions from incomplete information and incomplete research are effective in these criticisms. In addition, it is also effective to move the discussion about the intellectual conception (tasawwur) into the field of judgmental assent (tasdiq) and confusion of the mawhum (imaginable) with the ma‘kûl (intellegible)

A Single Conjunction Risk Assessment Metric: the F-Value

The Conjunction Assessment Team at NASA Goddard Space Flight Center provides conjunction risk assessment for many NASA robotic missions. These risk assessments are based on several figures of merit, such as miss distance, probability of collision, and orbit determination solution quality. However, these individual metrics do not singly capture the overall risk associated with a conjunction, making it difficult for someone without this complete understanding to take action, such as an avoidance maneuver. The goal of this analysis is to introduce a single risk index metric that can easily convey the level of risk without all of the technical details. The proposed index is called the conjunction "F-value." This paper presents the concept of the F-value and the tuning of the metric for use in routine Conjunction Assessment operations

Formulación de un examen académico óptimo

The aim of this paper is to formulate an optimal academic exam for a given subject. To do this, the probability is first modelled of a student passing the exam according to the number of units he studies and the professor evaluates. That simulation model is developed by performing a probabilistic analysis. An optimal exam is then defined as the one that awards the grade that the student deserves. Therefore, in an optimal exam, approve those who deserve to approve, and disapprove those that do not deserve to approve. Besides, this exam must respect the limitations of time and effort that the professor imposes. Based on this definition and using the simulation model, an INLP type optimization model is formulated. This optimization model determines the number of units the professor must evaluate to maximize the probability of getting an optimal exam.El objetivo de este trabajo es formular un examen académico óptimo para una materia dada. Para ello, primero, se modela la probabilidad de que un estudiante apruebe el examen en función del número de unidades que estudia y de las que el profesor evalúa. Ese modelo de simulación es desarrollado realizando un análisis probabilístico. Un examen óptimo es luego definido como aquel que asigna la nota que el estudiante merece. Por lo tanto, en un examen óptimo, aprueban quienes merecen aprobar, y desaprueban quienes no merecen aprobar. Además, el examen debe respetar las limitaciones de tiempo y esfuerzo que el profesor impone. En base a esta definición y usando el modelo de simulación, se formula un modelo de optimización del tipo INLP. Este modelo de optimización determina el número de unidades que el profesor debe evaluar para maximizar la probabilidad de conseguir un examen óptimo.Fil: Tarifa, Enrique Eduardo. Universidad Nacional de Jujuy. Facultad de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta; ArgentinaFil: Martínez, Sergio Luis. Universidad Nacional de Jujuy. Facultad de Ingeniería; ArgentinaFil: Franco Domínguez, Samuel. Universidad Nacional de Jujuy. Facultad de Ingeniería; ArgentinaFil: Argañaraz, Jorgelina Francisca. Universidad Nacional de Jujuy. Facultad de Humanidades y Ciencias Sociales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta; Argentin

Formulación de un examen académico óptimo

The aim of this paper is to formulate an optimal academic exam for a given subject. To do this, the probability is first modelled of a student passing the exam according to the number of units he studies and the professor evaluates. That simulation model is developed by performing a probabilistic analysis. An optimal exam is then defined as the one that awards the grade that the student deserves. Therefore, in an optimal exam, approve those who deserve to approve, and disapprove those that do not deserve to approve. Besides, this exam must respect the limitations of time and effort that the professor imposes. Based on this definition and using the simulation model, an INLP type optimization model is formulated. This optimization model determines the number of units the professor must evaluate to maximize the probability of getting an optimal exam.El objetivo de este trabajo es formular un examen académico óptimo para una materia dada. Para ello, primero, se modela la probabilidad de que un estudiante apruebe el examen en función del número de unidades que estudia y de las que el profesor evalúa. Ese modelo de simulación es desarrollado realizando un análisis probabilístico. Un examen óptimo es luego definido como aquel que asigna la nota que el estudiante merece. Por lo tanto, en un examen óptimo, aprueban quienes merecen aprobar, y desaprueban quienes no merecen aprobar. Además, el examen debe respetar las limitaciones de tiempo y esfuerzo que el profesor impone. En base a esta definición y usando el modelo de simulación, se formula un modelo de optimización del tipo INLP. Este modelo de optimización determina el número de unidades que el profesor debe evaluar para maximizar la probabilidad de conseguir un examen óptimo.Facultad de Informátic