Advances in Fuzzy Systems The latest articles from Hindawi Publishing Corporation © 2015 , Hindawi Publishing Corporation . All rights reserved. Discrete-Time Exponentially Stabilizing Fuzzy Sliding Mode Control via Lyapunov’s Method Wed, 25 Feb 2015 14:20:42 +0000 The exponentially stabilizing state feedback control algorithm is developed by Lyapunov’s second method leading to the variable structure system with chattering free sliding modes. Linear time-invariant discrete-time second order plant is considered and the control law is obtained by using a simple fuzzy controller. The analytical structure of the proposed controller is derived and used to prove exponential stability of sliding subspace. Essentially, the control algorithm drives the system from an arbitrary initial state to a prescribed so-called sliding subspace S, in finite time and with prescribed velocity estimate. Inside the sliding subspace S, the system is switched to the sliding mode regime and stays in it forever. The proposed algorithm is tested on the real system in practice, DC servo motor, and simulation and experimental results are given. Radiša Ž. Jovanović and Zoran M. Bučevac Copyright © 2015 Radiša Ž. Jovanović and Zoran M. Bučevac. All rights reserved. Edge Detection via Edge-Strength Estimation Using Fuzzy Reasoning and Optimal Threshold Selection Using Particle Swarm Optimization Sun, 14 Dec 2014 06:37:11 +0000 An edge is a set of connected pixels lying on the boundary between two regions in an image that differs in pixel intensity. Accordingly, several gradient-based edge detectors have been developed that are based on measuring local changes in gray value; a pixel is declared to be an edge pixel if the change is significant. However, the minimum value of intensity change that may be considered to be significant remains a question. Therefore, it makes sense to calculate the edge-strength at every pixel on the basis of the intensity gradient at that pixel point. This edge-strength gives a measure of the potentiality of a pixel to be an edge pixel. In this paper, we propose to use a set of fuzzy rules to estimate the edge-strength. This is followed by selecting a threshold; only pixels having edge-strength above the threshold are considered to be edge pixels. This threshold is selected such that the overall probability of error in identifying edge pixels, that is, the sum of the probability of misdetection and the probability of false alarm, is minimum. This minimization is achieved via particle swarm optimization (PSO). Experimental results demonstrate the effectiveness of our proposed edge detection method over some other standard gradient-based methods. Ajay Khunteta and D. Ghosh Copyright © 2014 Ajay Khunteta and D. Ghosh. All rights reserved. Fuzzy Logic Control of a Ball on Sphere System Thu, 11 Dec 2014 09:50:24 +0000 The scope of this paper is to present a fuzzy logic control of a class of multi-input multioutput (MIMO) nonlinear systems called “system of ball on a sphere,” such an inherently nonlinear, unstable, and underactuated system, considered truly to be two independent ball and wheel systems around its equilibrium point. In this work, Sugeno method is investigated as a fuzzy controller method, so it works in a good state with optimization and adaptive techniques, which makes it very attractive in control problems, particularly for such nonlinear dynamic systems. The system’s dynamic is described and the equations are illustrated. The outputs are shown in different figures so as to be compared. Finally, these simulation results show the exactness of the controller’s performance. Seyed Alireza Moezi, Ehsan Zakeri, Yousef Bazargan-Lari, and Mahmood Khalghollah Copyright © 2014 Seyed Alireza Moezi et al. All rights reserved. Synthesis of Multicriteria Controller by Means of Fuzzy Logic Approach Wed, 19 Nov 2014 13:37:35 +0000 A two-mass fuzzy control system is considered. For fuzzification process, classical both linear and nonlinear membership functions are used. To find optimal values of membership function’s parameters, genetic algorithm is used. To take into account values of both output and intermediate parameters of the system, a penalty function is considered. Research is conducted for the case of speed control system and displacement control system. Obtained results are compared with the case of the system with classical, crisp controller. Andrew Lozynskyy and Lyubomyr Demkiv Copyright © 2014 Andrew Lozynskyy and Lyubomyr Demkiv. All rights reserved. Interest Measures for Fuzzy Association Rules Based on Expectations of Independence Tue, 07 Oct 2014 07:18:50 +0000 Lift, leverage, and conviction are three of the best commonly known interest measures for crisp association rules. All of them are based on a comparison of observed support and the support that is expected if the antecedent and consequent part of the rule were stochastically independent. The aim of this paper is to provide a correct definition of lift, leverage, and conviction measures for fuzzy association rules and to study some of their interesting mathematical properties. Michal Burda Copyright © 2014 Michal Burda. All rights reserved. Real Time Implementation of Incremental Fuzzy Logic Controller for Gas Pipeline Corrosion Control Tue, 09 Sep 2014 00:00:00 +0000 A robust virtual instrumentation based fuzzy incremental corrosion controller is presented to protect metallic gas pipelines. Controller output depends on error and change in error of the controlled variable. For corrosion control purpose pipe to soil potential is considered as process variable. The proposed fuzzy incremental controller is designed using a very simple control rule base and the most natural and unbiased membership functions. The proposed scheme is tested for a wide range of pipe to soil potential control. Performance comparison between the conventional proportional integral type and proposed fuzzy incremental controller is made in terms of several performance criteria such as peak overshoot, settling time, and rise time. Result shows that the proposed controller outperforms its conventional counterpart in each case. Designed controller can be taken in automode without waiting for initial polarization to stabilize. Initial startup curve of proportional integral controller and fuzzy incremental controller is reported. This controller can be used to protect any metallic structures such as pipelines, tanks, concrete structures, ship, and offshore structures. Gopalakrishnan Jayapalan, Ganga Agnihotri, and D. M. Deshpande Copyright © 2014 Gopalakrishnan Jayapalan et al. All rights reserved. On Intuitionistic Fuzzy Entropy of Order-α Wed, 03 Sep 2014 10:42:31 +0000 Using the idea of Rènyi’s entropy, intuitionistic fuzzy entropy of order-α is proposed in the setting of intuitionistic fuzzy sets theory. This measure is a generalized version of fuzzy entropy of order-α proposed by Bhandari and Pal and intuitionistic fuzzy entropy defined by Vlachos and Sergiadis. Our study of the four essential and some other properties of the proposed measure clearly establishes the validity of the measure as intuitionistic fuzzy entropy. Finally, a numerical example is given to show that the proposed entropy measure for intuitionistic fuzzy set is reasonable by comparing it with other existing entropies. Rajkumar Verma and BhuDev Sharma Copyright © 2014 Rajkumar Verma and BhuDev Sharma. All rights reserved. Fuzzy Set Field and Fuzzy Metric Tue, 02 Sep 2014 00:00:00 +0000 The notation of fuzzy set field is introduced. A fuzzy metric is redefined on fuzzy set field and on arbitrary fuzzy set in a field. The metric redefined is between fuzzy points and constitutes both fuzziness and crisp property of vector. In addition, a fuzzy magnitude of a fuzzy point in a field is defined. Gebru Gebray and B. Krishna Reddy Copyright © 2014 Gebru Gebray and B. Krishna Reddy. All rights reserved. Revised Max-Min Average Composition Method for Decision Making Using Intuitionistic Fuzzy Soft Matrix Theory Wed, 20 Aug 2014 07:34:43 +0000 In this paper a revised Intuitionistic Fuzzy Max-Min Average Composition Method is proposed to construct the decision method for the selection of the professional students based on their skills by the recruiters using the operations of Intuitionistic Fuzzy Soft Matrices. In Shanmugasundaram et al. (2014), Intuitionistic Fuzzy Max-Min Average Composition Method was introduced and applied in Medical diagnosis problem. Sanchez’s approach (Sanchez (1979)) for decision making is studied and the concept is modified for the application of Intuitionistic fuzzy soft set theory. Through a survey, the opportunities and selection of the students with the help of Intuitionistic fuzzy soft matrix operations along with Intuitionistic fuzzy max-min average composition method is discussed. P. Shanmugasundaram, C. V. Seshaiah, and K. Rathi Copyright © 2014 P. Shanmugasundaram et al. All rights reserved. Development of a System to Assist Automatic Translation of Hand-Drawn Maps into Tactile Graphics and Its Usability Evaluation Wed, 23 Jul 2014 11:29:17 +0000 Tactile graphics are images that use raised surfaces so that a visually impaired person can feel them. Tactile maps are used by blind and partially sighted people when navigating around an environment, and they are also used prior to a visit for orientation purposes. Since the ability to read tactile graphics deeply depends on individuals, providing tactile graphics individually is needed. This implies that producing tactile graphics should be as simple as possible. Based on this background, we are developing a system for automating production of tactile maps from hand-drawn figures. In this paper, we first present a pattern recognition method for hand-drawn maps. The usability of our system is then evaluated by comparing it with the two different methods to produce tactile graphics. Jianjun Chen and Noboru Takagi Copyright © 2014 Jianjun Chen and Noboru Takagi. All rights reserved. Designing of 2-Stage CPU Scheduler Using Vague Logic Tue, 22 Jul 2014 09:22:59 +0000 In operating system the CPU scheduler is designed in such a way that all the resources are fully utilized. With static priority scheduling the scheduler ensures that CPU time will be assigned according to the highest priority but ignores other factors; hence it affects the performance. To improve the performance, we propose a new 2-stage vague logic based scheduler. In first stage, scheduler handles the uncertainty of tasks using the proposed vague inference system (VIS). In second stage, scheduler uses a vague oriented priority scheduling (VOPS) algorithm for selection of next process. The goal of this work is to handle the uncertainty as well as to optimize both the average and the amount of variation with respect to performance matrices average waiting time, average turnaround time, and average normalized turnaround time. A simulation using MATLAB is also conducted to evaluate the performance. Simulation results show that the proposed scheduler using VOPS algorithm is better than the scheduler with traditional priority scheduling algorithm. Results are based on the dual concept of fuzzy theory and its generalization, vague theory. Additionally, this work comprises the evaluation of VOPS and shortest job first algorithm. The outcome of proposed VOPS algorithm is much closer to the result obtained by traditional shortest job first. Supriya Raheja, Reena Dhadich, and Smita Rajpal Copyright © 2014 Supriya Raheja et al. All rights reserved. A Geometric Fuzzy-Based Approach for Airport Clustering Thu, 17 Jul 2014 10:03:06 +0000 Airport classification is a common need in the air transport field due to several purposes—such as resource allocation, identification of crucial nodes, and real-time identification of substitute nodes—which also depend on the involved actors’ expectations. In this paper a fuzzy-based procedure has been proposed to cluster airports by using a fuzzy geometric point of view according to the concept of unit-hypercube. By representing each airport as a point in the given reference metric space, the geometric distance among airports—which corresponds to a measure of similarity—has in fact an intrinsic fuzzy nature due to the airport specific characteristics. The proposed procedure has been applied to a test case concerning the Italian airport network and the obtained results are in line with expectations. Maria Nadia Postorino and Mario Versaci Copyright © 2014 Maria Nadia Postorino and Mario Versaci. All rights reserved. Several Types of Totally Continuous Functions in Double Fuzzy Topological Spaces Thu, 10 Jul 2014 08:41:20 +0000 We introduce the notions of totally continuous functions, totally semicontinuous functions, and semitotally continuous functions in double fuzzy topological spaces. Their characterizations and the relationship with other already known kinds of functions are introduced and discussed. Fatimah M. Mohammed, M. S. M. Noorani, and A. Ghareeb Copyright © 2014 Fatimah M. Mohammed et al. All rights reserved. Credit Risk Prediction Using Fuzzy Immune Learning Tue, 24 Jun 2014 00:00:00 +0000 The use of credit has grown considerably in recent years. Banks and financial institutions confront credit risks to conduct their business. Good management of these risks is a key factor to increase profitability. Therefore, every bank needs to predict the credit risks of its customers. Credit risk prediction has been widely studied in the field of data mining as a classification problem. This paper proposes a new classifier using immune principles and fuzzy rules to predict quality factors of individuals in banks. The proposed model is combined with fuzzy pattern classification to extract accurate fuzzy if-then rules. In our proposed model, we have used immune memory to remember good B cells during the cloning process. We have designed two forms of memory: simple memory and k-layer memory. Two real world credit data sets in UCI machine learning repository are selected as experimental data to show the accuracy of the proposed classifier. We compare the performance of our immune-based learning system with results obtained by several well-known classifiers. Results indicate that the proposed immune-based classification system is accurate in detecting credit risks. Ehsan Kamalloo and Mohammad Saniee Abadeh Copyright © 2014 Ehsan Kamalloo and Mohammad Saniee Abadeh. All rights reserved. Application of Coupled Fixed Point Technique in Solving Integral Equations on Modified Intuitionistic Fuzzy Metric Spaces Sun, 22 Jun 2014 00:00:00 +0000 We establish a common coupled fixed point theorem for weakly compatible mappings on modified intuitionistic fuzzy metric spaces. As an application of our result, we study the existence and uniqueness of the solution to a nonlinear Fredholm integral equation. We also give an example to demonstrate our result. Bhavana Deshpande and Amrish Handa Copyright © 2014 Bhavana Deshpande and Amrish Handa. All rights reserved. Genetic Algorithm Based Hybrid Fuzzy System for Assessing Morningness Sun, 15 Jun 2014 11:05:36 +0000 This paper describes a real life case example on the assessment process of morningness of individuals using genetic algorithm based hybrid fuzzy system. It is observed that physical and mental performance of human beings in different time slots of a day are majorly influenced by morningness orientation of those individuals. To measure the morningness of people various self-reported questionnaires were developed by different researchers in the past. Among them reduced version of Morningness-Eveningness Questionnaire is mostly accepted. Almost all of the linguistic terms used in questionnaires are fuzzily defined. So, assessing them in crisp environments with their responses does not seem to be justifiable. Fuzzy approach based research works for assessing morningness of people are very few in the literature. In this paper, genetic algorithm is used to tune the parameters of a Mamdani fuzzy inference model to minimize error with their predicted outputs for assessing morningness of people. Animesh Biswas and Debasish Majumder Copyright © 2014 Animesh Biswas and Debasish Majumder. All rights reserved. HYEI: A New Hybrid Evolutionary Imperialist Competitive Algorithm for Fuzzy Knowledge Discovery Mon, 26 May 2014 13:16:56 +0000 In recent years, imperialist competitive algorithm (ICA), genetic algorithm (GA), and hybrid fuzzy classification systems have been successfully and effectively employed for classification tasks of data mining. Due to overcoming the gaps related to ineffectiveness of current algorithms for analysing high-dimension independent datasets, a new hybrid approach, named HYEI, is presented to discover generic rule-based systems in this paper. This proposed approach consists of three stages and combines an evolutionary-based fuzzy system with two ICA procedures to generate high-quality fuzzy-classification rules. Initially, the best feature subset is selected by using the embedded ICA feature selection, and then these features are used to generate basic fuzzy-classification rules. Finally, all rules are optimized by using an ICA algorithm to reduce their length or to eliminate some of them. The performance of HYEI has been evaluated by using several benchmark datasets from the UCI machine learning repository. The classification accuracy attained by the proposed algorithm has the highest classification accuracy in 6 out of the 7 dataset problems and is comparative to the classification accuracy of the 5 other test problems, as compared to the best results previously published. D. Jalal Nouri, M. Saniee Abadeh, and F. Ghareh Mohammadi Copyright © 2014 D. Jalal Nouri et al. All rights reserved. Using Trapezoidal Intuitionistic Fuzzy Number to Find Optimized Path in a Network Sun, 11 May 2014 14:20:07 +0000 In real life, information available on situations/issues/problems is vague, inexact, or insufficient and so the parameters involved therein are grasped in an uncertain way by the decision maker. But in real life such uncertainty is unavoidable. One possible way out is to consider the knowledge of experts about the parameters involved as fuzzy data. In a network, the arc length may represent time or cost. In Relevant literature reports there are several methods to solve such problems in network-flow. This paper proposes an optimized path for use in networks, using trapezoidal intuitionistic fuzzy numbers, assigned to each arc length in a fuzzy environment. It proposes a new algorithm to find the optimized path and implied distance from source node to destination node. P. Jayagowri and G. Geetha Ramani Copyright © 2014 P. Jayagowri and G. Geetha Ramani. All rights reserved. Interval-Valued Semiprime Fuzzy Ideals of Semigroups Sun, 04 May 2014 16:16:48 +0000 We introduce the notion of (i-v) semiprime (irreducible) fuzzy ideals of semigroups and investigate its different algebraic properties. We study the interrelation among (i-v) prime fuzzy ideals, (i-v) semiprime fuzzy ideals, and (i-v) irreducible fuzzy ideals and characterize regular semigroups by using these (i-v) fuzzy ideals. Sukhendu Kar, Paltu Sarkar, and Kostaq Hila Copyright © 2014 Sukhendu Kar et al. All rights reserved. Vague Soft Hypergroups and Vague Soft Hypergroup Homomorphism Mon, 31 Mar 2014 08:10:46 +0000 We introduce and develop the initial theory of vague soft hyperalgebra by introducing the novel concept of vague soft hypergroups, vague soft subhypergroups, and vague soft hypergroup homomorphism. The properties and structural characteristics of these concepts are also studied and discussed. Ganeshsree Selvachandran and Abdul Razak Salleh Copyright © 2014 Ganeshsree Selvachandran and Abdul Razak Salleh. All rights reserved. A New Fuzzy TOPSIS-TODIM Hybrid Method for Green Supplier Selection Using Fuzzy Time Function Mon, 17 Mar 2014 16:26:59 +0000 Today green supply chain is considered all around the world and supplier selection has been changed regarding these green and carbon emission criteria, so green supplier selection has been a major problem in this area. In this study we use fuzzy time function to assist managers in green supplier selection under uncertainty and ambiguity. This function will consider derivation from the goal during the time and by using it, and we will be able to have the best supplier in every period after having some modification in legal limitations for green supplier selection criteria. We use a fuzzy TOPSIS to have better initial weighting in TODIM, a discrete multicriteria method based on prospect theory in uncertainty (known as TODIM in Portuguese) decision making method. The results indicated that our proposed approach can easily and effectively accommodate criteria with gains and loss functions during time and also by using this method we will have a more reasonable predict of our suppliers ranking in future and that will help us in future investment in these suppliers. Finally it has been shown in car industries in Iran. Alireza Arshadi Khamseh and Mahdi Mahmoodi Copyright © 2014 Alireza Arshadi Khamseh and Mahdi Mahmoodi. All rights reserved. Fuzzy Methods and Approximate Reasoning in Geographical Information Systems Wed, 12 Mar 2014 09:05:15 +0000 Ferdinando Di Martino, Irina Perfilieva, Salvatore Sessa, and Sabrina Senatore Copyright © 2014 Ferdinando Di Martino et al. All rights reserved. Fuzzy Approach for Group Sequential Test Wed, 19 Feb 2014 10:01:05 +0000 Buckley’s approach (Buckley (2004), (2005), (2006)) uses sets of confidence intervals by taking into consideration both of the uncertainty and impreciseness of concepts that produce triangular shaped fuzzy numbers for the estimator. This approach produces fuzzy test statistics and fuzzy critical values in hypothesis testing. In addition, the sample size is fixed for this test. When data comes sequentially, however, it is not suitable to study with a fixed sample size test. In such cases, sequential and group sequential tests are recommended. Unlike a sequential test, a group of sequential test provides substantial savings in sample and enables us to make decisions as early as possible. This intends paper to combine the benefits of group sequential test and Buckley's approach using -cuts. It attempts to show that using -cuts can be used within the group sequential tests. To illustrate the test more explicitly a numerical example is also given. Duygu İçen, Sevil Bacanlı, and Süleyman Günay Copyright © 2014 Duygu İçen et al. All rights reserved. An Extended Analytical Approach to Evaluating Monotonic Functions of Fuzzy Numbers Tue, 11 Feb 2014 12:22:18 +0000 This paper presents an extended analytical approach to evaluating continuous, monotonic functions of independent fuzzy numbers. The approach is based on a parametric α-cut representation of fuzzy numbers and allows for the inclusion of parameter uncertainties into mathematical models. Arthur Seibel and Josef Schlattmann Copyright © 2014 Arthur Seibel and Josef Schlattmann. All rights reserved. A New Method for Short Multivariate Fuzzy Time Series Based on Genetic Algorithm and Fuzzy Clustering Wed, 18 Dec 2013 13:38:41 +0000 Forecasting activities play an important role in our daily life. In recent years, fuzzy time series (FTS) methods were developed to deal with forecasting problems. FTS attracted researchers because of its ability to predict the future values in some critical situations where most standard forecasting models are doubtfully applicable or produce bad fittings. However, some critical issues in FTS are still open; these issues are often subjective and affect the accuracy of forecasting. In this paper, we focus on improving the accuracy of FTS forecasting methods. The new method integrates the fuzzy clustering and genetic algorithm with FTS to reduce subjectivity and improve its accuracy. In the new method, the genetic algorithm is responsible for selecting the proper model. Also, the fuzzy clustering algorithm is responsible for fuzzifying the historical data, based on its membership degrees to each cluster, and using these memberships to defuzzify the results. This method provides better forecasting accuracy when compared with other extant researches. Kamal S. Selim and Gihan A. Elanany Copyright © 2013 Kamal S. Selim and Gihan A. Elanany. All rights reserved. Mining Linguistic Associations for Emergent Flood Prediction Adjustment Tue, 17 Dec 2013 15:45:48 +0000 Floods belong to the most hazardous natural disasters and their disaster management heavily relies on precise forecasts. These forecasts are provided by physical models based on differential equations. However, these models do depend on unreliable inputs such as measurements or parameter estimations which causes undesirable inaccuracies. Thus, an appropriate data-mining analysis of the physical model and its precision based on features that determine distinct situations seems to be helpful in adjusting the physical model. An application of fuzzy GUHA method in flood peak prediction is presented. Measured water flow rate data from a system for flood predictions were used in order to mine fuzzy association rules expressed in natural language. The provided data was firstly extended by a generation of artificial variables (features). The resulting variables were later on translated into fuzzy GUHA tables with help of Evaluative Linguistic Expressions in order to mine associations. The found associations were interpreted as fuzzy IF-THEN rules and used jointly with the Perception-based Logical Deduction inference method to predict expected time shift of flow rate peaks forecasted by the given physical model. Results obtained from this adjusted model were statistically evaluated and the improvement in the forecasting accuracy was confirmed. Michal Burda, Pavel Rusnok, and Martin Štěpnička Copyright © 2013 Michal Burda et al. All rights reserved. Fuzzy Reliability in Spatial Databases Sun, 15 Dec 2013 14:29:37 +0000 Today it is very difficult to evaluate the quality of spatial databases, mainly for the heterogeneity of input data. We define a fuzzy process for evaluating the reliability of a spatial database: the area of study is partitioned in isoreliable zones, defined as homogeneous zones in terms of data quality and environmental characteristics. We model a spatial database in thematic datasets; each thematic dataset concerns a specific spatial domain and includes a set of layers. We estimate the reliability of each thematic dataset and therefore the overall reliability of the spatial database. We have tested this method on the spatial dataset of the town of Cava de' Tirreni (Italy). Ferdinando Di Martino and Salvatore Sessa Copyright © 2013 Ferdinando Di Martino and Salvatore Sessa. All rights reserved. On Optimal Operator for Combining Left and Right Sole Pressure Data in Biometrics Security Thu, 12 Dec 2013 10:55:42 +0000 This paper describes optimal operator for combining left and right sole pressure data in a personal authentication method by dynamic change of sole pressure distribution while walking. The method employs a pair of right and left sole pressure distribution change data. These data are acquired by a mat-type load distribution sensor. The system extracts features based on shape of sole and weight shift from each sole pressure distribution. We calculate fuzzy degrees of right and left sole pressures for a registered person. Fuzzy if-then rules for each registered person are statistically determined by learning data set. Next, we combine the fuzzy degrees of right and left sole pressure data. In this process, we consider six combination operators. We examine which operator achieves best accuracy for the personal authentication. In the authentication system, we identify the walking persons as a registered person with the highest fuzzy degree. We verify the walking person as the target person when the combined fuzzy degree of the walking person is higher than a threshold. In our experiment, we employed 90 volunteers, and our method obtained higher authentication performance by mean and weighted sum operators. Takahiro Takeda, Kei Kuramoto, Syoji Kobashi, and Yutaka Hata Copyright © 2013 Takahiro Takeda et al. All rights reserved. Hotspots Detection in Spatial Analysis via the Extended Gustafson-Kessel Algorithm Mon, 09 Dec 2013 09:34:16 +0000 We show a new approach for detecting hotspots in spatial analysis based on the extended Gustafson-Kessel clustering method encapsulated in a Geographic Information System (GIS) tool. This algorithm gives (in the bidimensional case) ellipses as cluster prototypes to be considered as hotspots on the geographic map and we study their spatiotemporal evolution. The data consist of georeferenced patterns corresponding to positions of Taliban’s attacks against civilians and soldiers in Afghanistan that happened during the period 2004–2010. We analyze the formation through time of new hotspots, the movement of the related centroids, the variation of the surface covered, the inclination angle, and the eccentricity of each hotspot. Ferdinando Di Martino and Salvatore Sessa Copyright © 2013 Ferdinando Di Martino and Salvatore Sessa. All rights reserved. Usage of Fuzzy Spatial Theory for Modelling of Terrain Passability Thu, 28 Nov 2013 17:39:55 +0000 Geographic support of decision-making processes is based on various geographic products, usually in digital form, which come from various foundations and sources. Each product can be characterized by its quality or by its utility value for the given type of task or group of tasks, for which the product is used. They also usually have different characteristics and thus can very significantly influence the resulting analytical material. The aim of the paper is to contribute to the solution of the question of how it is possible to work with diverse spatial geographic information so that the user has an idea about the resulting product. The concept of fuzzy sets is used for representation of classes, whose boundaries are not clearly (not sharply) set, namely, the fuzzy approach in overlaying operations realized in ESRI ArcGIS environment. The paper is based on a research project which is being solved at the Faculty of Military Technologies of the University of Defence. The research deals with the influence of geographic and climatic factors on the activity of armed forces and the Integrated Rescue System. Alois Hofmann, Sarka Hoskova-Mayerova, and Vaclav Talhofer Copyright © 2013 Alois Hofmann et al. All rights reserved.