Search results for "Fuzzy logi"
showing 10 items of 471 documents
Fuzzy Metric Approach to Aggregation of Risk Levels
2019
In this paper we propose a special construction of a general aggregation operator. The construction allows to aggregate fuzzy sets taking into account the distance between elements of the universe. We consider the case when fuzzy sets to be aggregated represent the risk level evaluation by several experts. We describe how the proposed construction could be applied for risk level assessment in the case when a strong fuzzy metric is used to characterize the similarity of objects under evaluation.
Modeling risk perception in ATIS context through Fuzzy Logic
2011
Abstract This research is aimed at investigating the effect of accuracy of ATIS (Advanced Traveller Information Systems) in terms of route choices and travellers concordance to informative system. A Stated Preference Experiment has been made by using a Travel Simulator developed at the Technische Universiteit of Delft (The Netherlands). During the experiment respondents have been asked to make repeated route choices in presence of ATIS. Two kinds of information have been tested: descriptive (respondents are provided with the estimated travel times on each route), and prescriptive (respondents are provided with the estimated shortest route). For each kind of information four levels of accura…
On the robust design of unknown inputs Takagi-Sugeno observer
2012
This paper deals with the observer design for Takagi-Sugeno (T-S) fuzzy models subject to unknown inputs and disturbance affecting both states and outputs of the system. Sufficient conditions to design an unknown input T-S observer are given in Linear Matrix Inequalities (LMIs) terms. Relaxations are introduced by using intermediate variables. Numerical example is given to illustrate the effectiveness of the given result.
Parallel Genetic Algorithms for the Tuning of a Fuzzy AQM Controller
2003
This paper presents the results of the application of a parallel Genetic Algorithm (GA) in order to design a Fuzzy Proportional Integral (FPI) controller for active queue management on Internet routers. The Active Queue Management (AQM) policies are those policies of router queue management that allow the detection of network congestion, the notification of such occurrences to the hosts on the network borders, and the adoption of a suitable control policy. Two different parallel implementations of the genetic algorithm are adopted to determine an optimal configuration of the FPI controller parameters. Finally, the results of several experiments carried out on a forty nodes cluster of workst…
Intelligent Traction Control for Wheeled Space Vehicles
2006
This paper presents the SC-MER, safety control for Mars exploration rover, an innovative traction control scheme for wheeled mobile vehicles. The system is thought to be used on space mission rovers and is based on fuzzy logic and competitive neural networks to achieve optimal navigation on rough terrain with variable morphology. The main goal of this research is to minimize the power consumption needed during the navigation and improve the overall stability and safety of the rover itself
Approximation-based adaptive tracking control of stochastic nonlinear systems with a general form
2014
In this paper, an approximation-based adaptive tracking control scheme is proposed for a class of stochastic nonlinear systems with a more general structure. Fuzzy logical systems are used to approximate unknown nonlinearities in the controller design procedure and the backstepping technique is utilized to construct a state-feedback adaptive controller. The proposed controller can guarantee that all the signals in the closed-loop system are fourth-moment semi-globally uniformly ultimately bounded and the tracking error eventually converges to a small neighborhood around the origin. Simulation results are used to show the effectiveness of the proposed control scheme.
Automatic Detection of Hemangioma through a Cascade of Self-organizing Map Clustering and Morphological Operators
2016
Abstract In this paper we propose a method for the automatic detection of hemangioma regions, consisting of a cascade of algorithms: a Self Organizing Map (SOM) for clustering the image pixels in 25 classes (using a 5x5 output layer) followed by a morphological method of reducing the number of classes (MMRNC) to only two classes: hemangioma and non-hemangioma. We named this method SOM-MMRNC. To evaluate the performance of the proposed method we have used Fuzzy C-means (FCM) for comparison. The algorithms were tested on 33 images; for most images, the proposed method and FCM obtain similar overall scores, within one percent of each other. However, in about 18% of the cases, there is a signif…
Studying the feasibility of a recommender in a citizen web portal based on user modeling and clustering algorithms
2006
This paper presents a methodology to estimate the future success of a collaborative recommender in a citizen web portal. This methodology consists of four stages, three of them are developed in this study. First of all, a user model, which takes into account some usual characteristics of web data, is developed to produce artificial data sets. These data sets are used to carry out a clustering algorithm comparison in the second stage of our approach. This comparison provides information about the suitability of each algorithm in different scenarios. The benchmarked clustering algorithms are the ones that are most commonly used in the literature: c-Means, Fuzzy c-Means, a set of hierarchical …
Stable Automatic Unsupervised Segmentation of Retinal Vessels Using Self-Organizing Maps and a Modified Fuzzy C-Means Clustering
2011
In this paper an automatic unsupervised method for the segmentation of retinal vessels is proposed. Three features are extracted from the tested image. The features are scaled down by a factor of 2 and mapped into a Self-Organizing Map. A modified Fuzzy C-Means clustering algorithm is used to divide the neuron units of the map in 2 classes. The entire image is again input for the Self-Organizing Map and the class of each pixel will be the class of its best matching unit in the Self-Organizing Map. Finally, the vessel network is post-processed using a hill climbing strategy on the connected components of the segmented image. The experimental evaluation on the DRIVE database shows accurate ex…
A multiscale approach to automatic and unsupervised retinal vessel segmentation using Self-Organizing Maps
2016
In this paper an automatic unsupervised method for retinal vessel segmentation is described. Self-Organizing Map, modified Fuzzy C-Means, STAPLE algorithms and majority voting strategy were adopted to identify a segmentation of the retinal vessels. The performance of the proposed method was evaluated on the DRIVE database.