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This paper describes a practical and reliable solution/approach to achieve a semi-automated sewer pipeline inspection. The central goal of this work is to detect faults in the sewer lines which are a potential threat for underground drainage system. The major challenge for sewer line inspection is the classification and interpretation of the image data that are captured mainly by CCTV cameras mounted...
Situation awareness is a promising approach to recommend to a mobile user the most suitable resources for a specific situation. However, determining the correct user situation is not a simple task since users have different habits that may affect the way in which the situations arise. Thus, an appropriate tuning aimed at adapting the situation recognizer to the specific user is desirable to make a...
In this paper we address the problem of how to measure information conveyed by an Atanassov's intuitionistic fuzzy set (A-IFS for short) and a related concept of knowledge that is explicitly context oriented and useful from the point of view of a specific purpose, notably related to decision making. We pay particular attention to the relationship between the positive and negative information and a...
Classification in imbalanced domains has become one of the most relevant problems within the area of Machine Learning at the present. This problem has raised in significance due to its presence in many real applications and it occurs when the distribution of the available examples to carry out the learning process is very different between the classes (often for binary class data-sets). Usually, the...
In recommender systems, the task of automatically deriving user profiles, encoding the actual preferences of users, covers a fundamental role. In this paper, we propose a strategy for learning and updating user profiles by using fuzzy sets that reveal to be a valid tool to model the vague and imprecise nature of preferences as well as the items to be recommended. The proposed adaptation strategy resembles...
In the work we consider the situation with exact classes and fuzzy information of object features. The classification error is presented for the two-class Bayes classifier. The results are received for the full probabilistic information. The new upper bound of the probability of an error is precise twice as much as the bound based on the information energy of fuzzy events.
Due to the huge product assortments and complex descriptions of mobile products/services, it is a great challenge for new customers to select appropriate products. To solve this issue, a fuzzy matching based recommendation approach for mobile products/services is proposed in this paper. In this approach, a new customer's requirements are obtained through asking a set of questions and represented by...
The advantages of soft c-means over its hard and fuzzy versions render it more attractive to use in a wide variety of applications. Its main merit lies in its relatively higher convergence speed, which is more obvious in the presence of huge high dimensional data. This work presents a new approach to accelerate the convergence of the original soft c-means. It is mainly based on an iterative optimization...
This paper introduces a relational fuzzy c-means clustering algorithm that is able to partition objects taking into account simultaneously several dissimilarity matrices. The aim is to obtain a collaborative role of the different dissimilarity matrices in order to obtain a final consensus partition. These matrices could have been obtained using different sets of variables and dissimilarity functions...
Control of interior permanent magnet (IPMSM) is difficult because its nonlinearity and parameter uncertainty. In this paper, a fuzzy c-regression models clustering algorithm which is based on T-S fuzzy is used to model IPMSM with a series linear model and weight them by memberships. Lagrangian of constrained function is built for calculating clustering centers where training output data are considered...
This paper introduces a novel approach which uses a Hidden Markov Model (HMM) based Fuzzy Inference System (FIS) for prediction of systems that are non deterministic, dynamical and chaotic in nature. The HMM is used for shape based batch creation of training data which is then processed one batch at a time by a FIS. The Membership functions and Rule Base of the FIS are tweaked to predict the correct...
One of the most important features of fuzzy set theory is its potential for the modeling of natural language expressions. Most works done on this topic focus on some parts of natural language, mostly those that correspond to the so-called “evaluating linguistic expressions”. We build constraints for the mathematical substitutes of these expressions to mark characteristic limits on an ordered scale...
In this paper a new application of fuzzy logic to predict the performance of Titanium Aluminum Nitride (TiAlN) sputtering coating process is presented. Titanium Aluminum Nitride (TiAlN) coated material is widely used as a cutting tool in machining due to its excellent properties such as hardness, roughness and wear. A fuzzy logic model was proposed to predict the coating roughness with respect to...
This work proposes a decision support technology to minimize risks while choosing among competitive investment projects. The technology combines two fuzzy-statistical methods, providing two stages of investment projects' evaluation. At the first stage preliminary selection of projects with small risks is made on the basis of the expertons method [2],[3]. The second stage makes more precise decisions...
Wind energy is becoming one of the most important and promising areas of renewable energy. During the past few years, wind energy generation underwent strong improvements in several fields including power electronics, mechanics, wind dynamics, etc. However, there is a high need to develop more intelligent control mechanisms that can handle the various sources of uncertainties encountered in wind turbines...
This paper proposes a novel multiagent system for complex system modeling based on a dynamic fuzzy cognitive map approach. It aims to represent the domain knowledge and carry out the inference process regarding the uncertainty, distribution and dynamism that exist in most of real world problems. The proposed multiagent system architecture is able to model dynamic real world problems that almost contain...
In this paper a new criterion is introduced for the discrete covering problem. Using the representation of a possibility measure through associated probabilities, a new criterion for discrete covering problem is constructed based on aggregation by the Monotone Expectation (ME) (or Choquet integral). In this criterion the a priori information represented by a possibility measure and a misbelief distribution...
This paper regards a group decision-making process, where experts' estimates are expressed by triangular fuzzy numbers (TFNs). It presents an approach for determination of the degree of coordination, the closeness of these opinions. The implementation of the idea is based on the metric approach providing an easy procedure to determine the coordination degree of experts' opinions. A concept of the...
In classifier combining, predictions of several classifiers are aggregated into a single prediction in order to improve the classification quality. Among others, fuzzy integrals are commonly used as aggregation operators. Usually, Sugeno lambda-measure is used as the fuzzy measure of the integral. However, interaction between the classifiers in the team (diversity), an important property in classifier...
Estimating the head pose plays an important role in computer vision and also as a key task for visual surveillance and face recognition applications hence a prominent problem in computer vision. Most of the works in this field suffer from lack of continuous estimating of the head pose and high accuracy. We know fuzzy systems as universal approximator capable of approximating an unknown function by...
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