In geophysics, signals come with noise. It is desirable to minimize the effect of this noise. If we knew the probabilities of different values of signal and noise, we could use statistical filtering techniques. In geophysics, however, we rarely know the exact values of these probabilities; instead, we have to rely on the expertise and intuition of experts. We show how fuzzy techniques can trans...

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Two imprecise individual risk models of insurance are presented and studied in this paper. The models use the beta-binomial and the negative binomial imprecise statistical models, which can be regarded as sets of the corresponding distributions of claims. The sets of distributions strongly depend on prior statistical information about claims and their use can give an advantage when we have litt...

Received Nov 30, 2017 Revised Jan 15, 2018 Accepted Feb 4, 2018 In this paper, a review about different algorithm is proposed efficiently to segment the satellite images. Segmentation of Image is one of the promising and active researches in recent years. As literature prove that region segmentation will produce better results. Human visual perception is more effective than any machine vision s...

I present an hierarchical uncertainty model that is able to represent vague probability assessments, and to make inferences based on them. This model can be given an interpretation in terms of the behaviour of a modeller in the face of uncertainty, and is based on Walley’s theory of imprecise probabilities. It is formally closely related to Zadeh’s fuzzy probabilities, but it has a different in...

In decision-making models, the compositions (Aitchison, 1986) are employed in various forms. They can represent the normalized weights of criteria in multiple-criteria decision-making models, or the probabilities of states of the world in the models of decision making under risk. The normalized weights express the relative information about the importance of criteria, while the probabilities re...

In this paper, we describe a novel methodology for dance learning and evaluation using multi-sensor and 3D gaming technology. The learners are captured during dancing, while an avatar visualizes their motion using fused input from multiple sensors. Motion analysis and fuzzy-logic are employed for the evaluation of the learners’ performance against the performance of an expert. Specifically, a t...

This paper investigates and contrasts the use of different Bayesian networks and a fuzzy integral for real-time sensor fusion using sonar and rangefinder laser values on an ActivMedia robot. Bayesian networks have become increasingly popular because of their ability to capitalize on the conditional probabilities present in an influence chain. The Choquet fuzzy integral, which has primarily been...

In this paper, we propose a genetic fuzzy image filtering based on rank-ordered absolute differences (ROAD) and median of the absolute deviations from the median (MAD). The proposed method which is consisted of three components, including fuzzy noise detection system, fuzzy switching scheme filtering, and fuzzy parameters optimization use genetic algorithms (GA) to perform efficient and effecti...

A fuzzy random variable is viewed as the imprecise observation of the outcomes in a random experiment. Since randomness and vagueness coexist in the same framework, it seems reasonable to integrate fuzzy random variables into imprecise probabilities theory. Nevertheless, fuzzy random variables are commonly presented in the literature as classical measurable functions associated to a classical p...