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Ad-hoc networks, as well as many wireless networks and wired networks applied here to do and the proper function of routing data packets forwarding, maintenance and update routing information, the security need. Mobile ad hoc networks due to the special properties of operations and placement of often unstructured meshes, or self-organizing ad-hoc networks are known. In these networks in order to extend...
Classification systems based on Fuzzy Logic are of particular importance in the ambit of cognitive systems, due to their ability of managing uncertainty and presenting interpretable knowledge bases by emulating human cognition processes. However, the notion of interpretability is not yet exhaustively defined. In this work, the properties assessing the interpretability of a fuzzy classifier are discussed,...
From a wide variety of applications in the areas of engineering and financial sector, Fuzzy logic techniques has a potential to model academic performance evaluation too. Manual errors in student evaluation can affect their present and future opportunities, so there arises a need to develop a model that can help teachers to fairly evaluate student's performance. This article presents an improved solution...
The control level in bins and effective rate of discharge is very complex as there are many dynamic variables such as time of discharge cycle, speed of feeders, physical characteristics and chemical composition of the ore. This work addresses two variables to apply fuzzy logic, which are: “The level of material in the car dumper silos;” The effective rate of discharge. The ideal discharge occurs when...
This work presents a unified approach to derive decision procedures for model based fault detection and isolation (FDI) either from knowledge or from experiments. In the knowledge-based approach, fuzzy rule weights are defined directly from model structure. In the supervised learning approach, the decision procedure is derived from a data set. The symbolic to numeric integration provided by fuzzy...
In this work we deal with the problem of web page clustering from the point of view of document representation. Fuzzy ruled-based systems have been successfully used to represent web documents by means of heuristic combinations of criteria. In these systems, rules were established based on the way humans read documents and have been analyzed in previous works. However, membership functions parameters...
Fuzzy controllers are represented by if-then rules and thus can provide a user friendly and understandable knowledge representation. Evolutionary algorithms have been widely used for optimal design of fuzzy logic controllers (FLCs). In this paper, we present an evolutionary algorithm based on Tabu Search (TS) for generating knowledge bases for fuzzy logic systems. The algorithm dynamically adjusts...
Humans use multiple sources of sensory information to estimate environmental properties and has innate ability to integrate information from heterogeneous data sources. How the multi-sensory and multimodal information are integrated in human brain? There is consensus that it depends on the prefrontal cortex (PFC). The PFC has top-down control (favor weak) and rule-based mechanisms, and we propose...
Fuzzy Logic Controllers (FLCS) are rule-based system that successfully incorporate the flexibility of human-decision making by means of the use of fuzzy set theory. This paper provides an overview on evolutionary learning methods for the automated design and optimization of fuzzy logic controllers. A three-stage evolution framework that uses Genetic Programming (GP) and Genetic Algorithms (GAS) evolves...
Classification is a widely researched area in the machine learning and fuzzy communities with several approaches proposed by both communities. Some of the most relevant rule-based approaches from the machine learning community might include decision trees and rule inducers. The fuzzy community has also proposed many rule-based approaches, such as fuzzy decision trees and genetic fuzzy systems. This...
Fuzzy Logic Systems (FLSs) provide a proven toolset in mimicking human reasoning. In this paper, we will present the idea of Fuzzy Composite Concepts (FCCs) which allow for a closer imitation of human reasoning in terms of integrating a large number of parameters into a single concept suitable for higher level reasoning. FCCs are based on standard FLSs and transparently extend them to provide intuitively...
This paper presents definitions of a fuzzy knowledge system and fuzzy logic formulae. Information entropies of the fuzzy logic formulae and information entropies of fuzzy rules of the fuzzy knowledge system are described, and relative properties of these definitions are discussed. And then, classification and evaluation of the siso fuzzy system are given based on the information entropy. Finally,...
During the past several years, fuzzy control has emerged as one of the most suitable and efficient methods for designing and developing complex systems in environments characterized by high level of uncertainty and imprecision. Nowadays, this methodology is used to model systems in several applications domains which range from industrial machineries to financial decisions support systems. Nevertheless,...
Cutting forces prediction is very important in micromilling for cutting tool's design and process planning. This paper presents a new model for uncertainty estimation of dynamic cutting forces in micromilling using a type-2 fuzzy rule-based system. The type-2 fuzzy estimation not only filters the noise and estimates the instantaneous cutting force in micromilling using observations acquired by sensors...
Assessing interpretability of fuzzy systems still remains an open and challenging problem. Defining a good index is extremely difficult mainly due to the inherent subjective nature of interpretability. It strongly depends on the background of the person who makes the assessment according to its own knowledge, but also taking into account its previous experience and preferences. Since looking for fuzzy...
In this paper, an immune inspired multi-objective fuzzy modeling (IMOFM) mechanism is proposed specifically for high-dimensional regression problems. For such problems, high predictive accuracy is often the paramount requirement. With such a requirement in mind, however, one should also put considerable efforts in making the elicited model as interpretable as possible, which leads to a difficult optimization...
This work presents an application of the novel theory of rule based networks for building models of processes characterised by uncertainty, non-linearity, modular structure and internal interactions. The application of the theory is demonstrated for a flotation process in the context of converting a multiple rule based system into an equivalent single rule based system by linguistic composition of...
This study presents a framework of platform-based inference system design to provide specific field experts/users developing customized fuzzy inference system efficiently and effectively. The framework is composed of three major components: FML editor, FML parser and FML inference engine. First, the FML editor can let field experts compile knowledge base and rule base with friendly user interface...
Various techniques have been developed for the tracking of maneuvering targets. When the target maneuvers, the quality of the state estimates provided by the constant velocity filter can degrade significantly. Unknown target acceleration during the maneuver appears as excessive process noise on the target model and the noise variance changes drastically. In this paper, the authors propose a new fuzzy...
Interpretability represents the most important driving force behind the implementation of fuzzy logic-based systems. It can be directly related to the system's knowledge base, with reference to the human user's easiness experienced while reading and understanding the embedded pieces of information. In this paper, we present a preliminary study on interpretability conditions for fuzzy rule-based classifiers...
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