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48
Mobile Robot Localization Using Fuzzy Maps
, 1996
"... : This paper deals with the problems of map building and mobile robot localization. Ultrasonic sensors information, obtained as the robot moves, is integrated in order to build a map of the environment. This map is afterwards used for robot localization, correcting the errors that the dead reckoning ..."
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Cited by 18 (0 self)
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: This paper deals with the problems of map building and mobile robot localization. Ultrasonic sensors information, obtained as the robot moves, is integrated in order to build a map of the environment. This map is afterwards used for robot localization, correcting the errors that the dead reckoning system accumulates in long displacements. The approach focuses on the way to analyze sensor information and on the way to reconstruct the outline of the objects. Since measuring conditions are unknown and just a small number of observations are normally available to reconstruct the boundaries of the objects, this will generate uncertainty on their real location. Fuzzy sets are used to represent this uncertainty, their degrees of membership indicating the extent to which one boundary can be considered similar to other boundaries located in the proximity. Experimental results with a mobile robot in an office environment are also presented. 1 Introduction In this paper we address the problems...
Obtaining Solutions in Fuzzy Constraint Networks
 International Journal of Approximate Reasoning
, 1997
"... In this work we propose three methods for obtaining solutions in fuzzy constraint networks and study their application to the problem of ordering fuzzy numbers. The techniques proposed may be classified as defuzzification functions which are applicable to any set of mutually dependant fuzzy numbers ..."
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Cited by 15 (2 self)
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In this work we propose three methods for obtaining solutions in fuzzy constraint networks and study their application to the problem of ordering fuzzy numbers. The techniques proposed may be classified as defuzzification functions which are applicable to any set of mutually dependant fuzzy numbers in which the dependence relationships are represented by means of metric constraints. In the paper we suggest the use of these techniques for ordering linked variables in an efficient manner, and discuss their behavior regarding several quality criteria. The first application realm of these techniques is temporal reasoning.
Multidimensional Scaling of Fuzzy Dissimilarity Data
"... Multidimensional scaling is a wellknown technique for representing measurements of dissimilarity among objects as distances between points in a pdimensional space. In this paper, this method is extended to the case where dissimilarities are expressed as intervals or fuzzy numbers. Each object is t ..."
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Cited by 7 (1 self)
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Multidimensional scaling is a wellknown technique for representing measurements of dissimilarity among objects as distances between points in a pdimensional space. In this paper, this method is extended to the case where dissimilarities are expressed as intervals or fuzzy numbers. Each object is then no longer represented by a point but by a crisp or a fuzzy region. To determine these regions, two algorithms are proposed and illustrated using typical datasets. Experiments demonstrate the ability of the methods to represent both the structure and the vagueness of dissimilarity measurements.
Efficient Acceptable Design Exploration Based on Module Utility Selection
, 1999
"... In this paper, we present a design exploration framework, called WIZARD, which aims at finding module selections leading to acceptable designs while considering scheduling and resource binding under latency, and power constraints. The framework contains two phases: choosing the resource configuratio ..."
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Cited by 7 (5 self)
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In this paper, we present a design exploration framework, called WIZARD, which aims at finding module selections leading to acceptable designs while considering scheduling and resource binding under latency, and power constraints. The framework contains two phases: choosing the resource configuration, and determining a module binding for each resource. We introduce a powerful model, called acceptability function which models design objectives, based on tradeoffs among different design constraints as well as users' willingness of accepting a design. Module utility measure cooperating with inclusion scheduling is a key to the success of the method. The module utility reects the usefulness of the module based on the acceptability function. Inclusion scheduling is a basic tool to calculate the number of generic resources as well as determine module usefulness. A heuristic which perturbs module utility values based on the given acceptability function until they lead to superior selec...
On the Implementation of Fuzzy Arithmetical Operations for Engineering Problems
 Proceedings of the 18th International Conference of the North American Fuzzy Information Processing Society  NAFIPS99
, 1999
"... Fuzzy arithmetic is a successful tool to solve engineering problems with uncertain parameters. The generalized mathematical operations for fuzzy numbers can theoretically be defined making use of Zadeh's extension principle. Practical realworld applications of fuzzy arithmetic, however, require an ..."
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Cited by 4 (2 self)
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Fuzzy arithmetic is a successful tool to solve engineering problems with uncertain parameters. The generalized mathematical operations for fuzzy numbers can theoretically be defined making use of Zadeh's extension principle. Practical realworld applications of fuzzy arithmetic, however, require an appropriate form of implementation for the fuzzy numbers and the fuzzy arithmetical operations. For this reason, the often applied concept of triangular fuzzy numbers and the more promising approach of discretized fuzzy numbers are presented and rated with respect to their practical application to solve engineering problems with uncertain parameters. As an example, a rather simple but typical problem of mechanical engineering is considered, consisting of determining the displacements in a twocomponent massless rod under tensile load with uncertain elasticity parameters. 1. Introduction To achieve reliable results for the numerical solution of engineering problems, exact values for the para...
A Nearly Strict Fuzzy Arithmetic for Solving Problems with Uncertainties
 In Proc. of the 19th International Conference of the North American Fuzzy Information Processing Society  NAFIPS 2000
, 2000
"... Fuzzy arithmetic is a powerful tool to solve engineering problems with uncertain parameters. In doing so, the uncertain parameters in the model equations are expressed by fuzzy numbers, and the problem is solved by using fuzzy arithmetic to carry out the mathematical operations in a generalized form ..."
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Cited by 4 (1 self)
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Fuzzy arithmetic is a powerful tool to solve engineering problems with uncertain parameters. In doing so, the uncertain parameters in the model equations are expressed by fuzzy numbers, and the problem is solved by using fuzzy arithmetic to carry out the mathematical operations in a generalized form. The practical use of standard fuzzy arithmetic, however, turns out to be very problematic, basically because of the overestimation effect which is responsible for a more or less large discrepancy between the proper arithmetical solution of the problem and the calculated one. In this paper, a new implementation of fuzzy arithmetic is presented by which those discrepancies in general can be reduced to a slight remainder and in many cases can even be totaly avoided. The effectiveness of the method is illustrated by some typical examples. 1. Introduction To achieve reliable results for the numerical solution of engineering problems, exact values for the parameters of the model equations shou...
Investment using technical analysis and fuzzy logic
 FUZZY SETS AND SYSTEMS
, 2002
"... Deploy fuzzy logic engineering tools in the finance arena, specifically in the technical analysis field. Since technical analysis theory consists of indicators used by experts to evaluate stock prices, the new proposed method maps these indicators into new inputs that can be fed into a fuzzy logic s ..."
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Cited by 4 (0 self)
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Deploy fuzzy logic engineering tools in the finance arena, specifically in the technical analysis field. Since technical analysis theory consists of indicators used by experts to evaluate stock prices, the new proposed method maps these indicators into new inputs that can be fed into a fuzzy logic system. The only required inputs to these indicators are past sequence of stock prices. This method relies on fuzzy logic to formulate a decision making when certain price movements or certain price formations occur. The success of the system is measured by comparingsystem output versus stock price movement. The new stock evaluation method is proven to exceed market performance and it can be an excellent tool in the technical
Imprecise task schedule optimization
 In Proceedings of the International Conference on Fuzzy Systems
, 1997
"... Considerable research has been done in order to schedule tasks to a multiple processing systems. Some of the computation time of these tasks may, however, be imprecise due to the nature of the problem. In this paper, an imprecise task graph is used to model the problem where each node represents a t ..."
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Cited by 4 (0 self)
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Considerable research has been done in order to schedule tasks to a multiple processing systems. Some of the computation time of these tasks may, however, be imprecise due to the nature of the problem. In this paper, an imprecise task graph is used to model the problem where each node represents a task associated with its computation time. An algorithm, called rotation scheduling, is extended to handle the imprecise task scheduling and fuzzy arithmetic is used to estimate the size of a schedule. The goal of the algorithm is to give the optimized schedule as much as possible. The experiments showing the effectiveness of this approach are also presented.
Inverse arithmetic operators for fuzzy intervals
"... Fuzzy arithmetic is a powerful tool in many engineering problems such as decision making, control theory, fuzzy systems and approximate reasoning. However, it is well known that the practical use of standard fuzzy arithmetic operators gives results more imprecise than necessary or in some cases, eve ..."
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Cited by 3 (2 self)
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Fuzzy arithmetic is a powerful tool in many engineering problems such as decision making, control theory, fuzzy systems and approximate reasoning. However, it is well known that the practical use of standard fuzzy arithmetic operators gives results more imprecise than necessary or in some cases, even incorrect. This problem is due to the overestimation effect induced by computing fuzzy arithmetic operations. In this paper a modified implementation for fuzzy unimodal interval arithemtics is defined where new subtraction and division operators are proposed. These new operators are exactly the inverse of the addition and multiplication operators. The effectiveness of the proposed methodology is illustrated by simulation examples.
On Applying Fuzzy Arithmetic to Finite Element Problems
 In Proc. of the NAFIPS 1998, Pensacola Beach, FL
, 1998
"... Fuzzy arithmetic, based on Zadeh's extension principle, is applied to solve finite element problems with uncertain parameters. As an example, a rather simple, onedimensional static problem consisting of a twocomponent massless rod under tensile load is considered. Application of fuzzy arithmetic di ..."
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Cited by 2 (2 self)
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Fuzzy arithmetic, based on Zadeh's extension principle, is applied to solve finite element problems with uncertain parameters. As an example, a rather simple, onedimensional static problem consisting of a twocomponent massless rod under tensile load is considered. Application of fuzzy arithmetic directly to the traditional techniques for the numerical solution of finite elements, i.e. primarily on the algorithms for solving systems of linear equations, however, turnes out to be impracticable in all circumstances. In contrast to the use of exclusively crisp numbers, the results for the calculations including fuzzy numbers usually differ to a large extent depending on the solution technique applied. The uncertainties expressed in the different calculation results are then basically twofold. On the one hand, uncertainty is caused by the presence of parameters with fuzzy value, on the other hand, an additional, undesirable uncertainty is artificially created by the solution technique itse...