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Recently, it has been shown that interval type-2 fuzzy sets (IT2FSs) are more general than interval-valued fuzzy sets (IVFSs), and some of these IT2FSs can actually be non-convex. Although these IT2FSs could be considered within the general type-2 fuzzy sets' (GT2FSs) scope, this latter have always been studied and developed under certain conditions considering the convexity and normality of their...
Environmental problems are complex in nature and are usually exacerbated by unsustainable trends that are driven by anthropogenic, economic and development factors. One of the key challenges of sustainability is the ability to examine the range of possible future paths of combined social and environmental conditions, under consideration of human perceptions, uncertainty and cause-effect factors, with...
Fuzzy linear regression is applied to the real estate appraisal and to the evaluation of parameters of the relationship between the stock of knowledge and R&D. In both cases fuzzy linear regression yields results that have meaningful economic interpretation.
The study of ecology seeks to understand the relationships between organisms and their environment and to use this knowledge to remedy environmental issues. However, the use of statistical analysis in ecology is hampered because many ecological components cannot be quantified with precision. Consequently, some ecologists have become interested in the application of fuzzy logic to accommodate ecological...
This paper presents a modeling approach based on fuzzy logic based system in order to analyze the economic sustainability of End of life vehicle (ELV) dismantlers under uncertainties. The proposed modeling approach with considering the different types of uncertainty including auto manufacturers design changes, technology market and regulations, provides a framework for auto manufacturers to evaluate...
In this paper we describe a method of using interval valued survey responses from multiple experts on multiple occassions to produce General Type-2 fuzzy sets. In the method we propose, both the intra- and inter-person variability are modelled, with no loss of information. The resulting sets are completely determined by the data, providing an accurate representation (in terms of being defined solely...
An important class of community-based activities of mobile users is searching and querying for common locations to visit or come together for a specific task. For this purpose, Group Nearest-Neighbor (GNN) queries are used a generalization of nearest-neighbor queries where the goal is to find one or more points from a set of destination points that have the smallest total distance from all query points...
A unique fuzzy approach is developed to model uncertainties in the preferences of a decision maker involved in a conflict. Human judgments, including expressing preferences over a set of feasible outcomes or states in a conflict, are usually imprecise. Situations characterized by vagueness, impreciseness, incompleteness and ambiguity, are often reflected in the decision maker's preferences. When modeling...
The interest of this paper is focused on the detection of some potential contradictions in fuzzy ontology. A high level net approach integrated with uncertainty inference is proposed for this purpose. It makes use of a State Controlled Coloured Petri Net (SCCPN), which has been proposed for ontology representation and verification in our previous work. In this paper, the SCCPN model designed to handle...
For the vague nature of trust and reputation, the traditional reputation modelings used the classic probability or fuzzy sets to describe and measure the degree of trust. The theoretic foundation of these models is subject logic or fuzzy logic. But in some practical applications, the usage of simple probability model led trust's subjectivity and uncertainty to randomness. For the fuzzy logic, the...
One of the biggest challenges in Software Engineering is accurately forecasting how much time and effort it will take either to develop a system. So far no model has proved to be successful at effectively and consistently predicting software development cost due to the lot of uncertainty factor of input size. In this paper we proposed an Interval Type 2 Fuzzy logic for software cost estimation. The...
As part of this paper we are highlighting several - in our opinion- important aspects of type-2 fuzzy logic systems which seem important to its future development and application. It is the aim of the paper to provide more questions and more suggestive points than actual answers. With type-2 fuzzy logic and its application to modelling and handling uncertainty still a very young area of research,...
Nowadays turbulent environment exposes global producing companies to many risks caused by uncertain parameters. Therefore, a correct evaluation of investments in factories including uncertainties becomes increasingly important. Existing monetary evaluation methods as the calculation of the net present value (NPV) integrate only static parameters like wages, material costs or overhead costs. Most evaluating...
Fuzzy models and fuzzy differential equations have experimented a great development in the last years, due to their application to the modelisation of systems subject to imprecision and to handle uncertainty. In this paper, a fuzzy evolution of mathematical tumor model is considered and interpreted from different point of view. Consider a crisp continuous system whose process of evolution depends...
In this paper the control of a bioprocess using an adaptive type-2 fuzzy logic controller is proposed. The process is concerned with the aerobic alcoholic fermentation for the growth of Saccharomyces Cerevisiae and is characterized by nonlinearity and parameter uncertainty. Three type-2 fuzzy controllers heve been developed and tested by simulation: a simple type-2 fuzzy logic controller with 49 rules;...
There exist several ways to model population growth at present time, which are mainly based on mathematics. However we present a new model based on fuzzy cellular theory. An interval type-2 fuzzy logic system (IT2-FLS) is designed to evaluate the population growth parameters based on the environment resources stochasticity, in time and space. Interval type-2 fuzzy sets are used to measure the uncertainties...
The sheer complexity of causation in the economic arena mandates a fuzzy approach. In this study we consider economic system as human centric and imperfect information based realistic multi-agent system with fuzzy-logic-based representation of the economic agents' behavior and with imprecise constraints. We will mainly consider two important problems of fuzzy economics: fuzzy decision principle and...
This paper introduce a type-2 fuzzy function system for uncertainty modeling using evolutionary algorithms (ET2FF). The type-1 fuzzy inference systems (FISs) with fuzzy functions, which do not entail if...then rule bases, have demonstrated better performance compared to traditional FIS. Nonetheless, the performance of these approaches is usually affected by their uncertain parameters. The proposed...
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