Current Issue : April - June Volume : 2014 Issue Number : 2 Articles : 7 Articles
Forecasting activities play an important role in our daily life. In recent years, fuzzy time series (FTS) methods were developed to\r\ndeal with forecasting problems. FTS attracted researchers because of its ability to predict the future values in some critical situations\r\nwhere most standard forecasting models are doubtfully applicable or produce bad fittings. However, some critical issues in FTS are\r\nstill open; these issues are often subjective and affect the accuracy of forecasting. In this paper, we focus on improving the accuracy\r\nof FTS forecasting methods. The new method integrates the fuzzy clustering and genetic algorithm with FTS to reduce subjectivity\r\nand improve its accuracy. In the new method, the genetic algorithm is responsible for selecting the proper model. Also, the fuzzy\r\nclustering algorithm is responsible for fuzzifying the historical data, based on its membership degrees to each cluster, and using\r\nthese memberships to defuzzify the results. This method provides better forecasting accuracy when compared with other extant\r\nresearches....
This paper discusses and proposes a rough set model for an incomplete information system, which defines an extended tolerance\r\nrelation using frequency of attribute values in such a system. It first discusses some rough set extensions in incomplete information\r\nsystems. Next, ââ?¬Å?probability of matchingââ?¬Â is defined from data in information systems and then measures the degree of tolerance.\r\nConsequently, a rough set model is developed using a tolerance relation defined with a threshold. The paper discusses the\r\nmathematical properties of the newly developed rough set model and also introduces a method to derive reducts and the core....
Today it is very difficult to evaluate the quality of spatial databases, mainly for the heterogeneity of input data. We define a fuzzy\r\nprocess for evaluating the reliability of a spatial database: the area of study is partitioned in isoreliable zones, defined as homogeneous\r\nzones in terms of data quality and environmental characteristics.We model a spatial database in thematic datasets; each thematic\r\ndataset concerns a specific spatial domain and includes a set of layers. We estimate the reliability of each thematic dataset and\r\ntherefore the overall reliability of the spatial database. We have tested this method on the spatial dataset of the town of Cava de�\r\nTirreni (Italy)....
We show a new approach for detecting hotspots in spatial analysis based on the extended Gustafson-Kessel clustering method\r\nencapsulated in a Geographic Information System (GIS) tool. This algorithm gives (in the bidimensional case) ellipses as cluster\r\nprototypes to be considered as hotspots on the geographic map and we study their spatiotemporal evolution. The data consist of\r\ngeoreferenced patterns corresponding to positions of Talibanââ?¬â?¢s attacks against civilians and soldiers in Afghanistan that happened\r\nduring the period 2004ââ?¬â??2010.We analyze the formation through time of new hotspots, the movement of the related centroids, the\r\nvariation of the surface covered, the inclination angle, and the eccentricity of each hotspot....
Floods belong to the most hazardous natural disasters and their disaster management heavily relies on precise forecasts. These\r\nforecasts are provided by physical models based on differential equations. However, these models do depend on unreliable inputs\r\nsuch as measurements or parameter estimations which causes undesirable inaccuracies.Thus, an appropriate data-mining analysis\r\nof the physical model and its precision based on features that determine distinct situations seems to be helpful in adjusting the\r\nphysical model. An application of fuzzy GUHA method in flood peak prediction is presented.Measured water flow rate data from\r\na system for flood predictions were used in order to mine fuzzy association rules expressed in natural language. The provided data\r\nwas firstly extended by a generation of artificial variables (features).Theresulting variableswere later on translated into fuzzyGUHA\r\ntables with help of Evaluative Linguistic Expressions in order to mine associations.Thefound associations were interpreted as fuzzy\r\nIF-THEN rules and used jointly with the Perception-based Logical Deduction inference method to predict expected time shift of\r\nflow rate peaks forecasted by the given physical model. Results obtained from this adjusted model were statistically evaluated and\r\nthe improvement in the forecasting accuracy was confirmed....
This paper describes optimal operator for combining left and right sole pressure data in a personal authentication method by\r\ndynamic change of sole pressure distribution while walking.The method employs a pair of right and left sole pressure distribution\r\nchange data.These data are acquired by amat-type load distribution sensor.The system extracts features based on shape of sole and\r\nweight shift from each sole pressure distribution.We calculate fuzzy degrees of right and left sole pressures for a registered person.\r\nFuzzy if-then rules for each registered person are statistically determined by learning data set. Next, we combine the fuzzy degrees\r\nof right and left sole pressure data. In this process, we consider six combination operators. We examine which operator achieves\r\nbest accuracy for the personal authentication. In the authentication system, we identify the walking persons as a registered person\r\nwith the highest fuzzy degree. We verify the walking person as the target person when the combined fuzzy degree of the walking\r\nperson is higher than a threshold. In our experiment, we employed 90 volunteers, and our method obtained higher authentication\r\nperformance by mean and weighted sum operators....
Geographic support of decision-making processes is based on various geographic products, usually in digital form, which come\r\nfrom various foundations and sources. Each product can be characterized by its quality or by its utility value for the given type of\r\ntask or group of tasks, for which the product is used. They also usually have different characteristics and thus can very significantly\r\ninfluence the resulting analyticalmaterial.Theaimof the paper is to contribute to the solution of the question of how it is possible to\r\nwork with diverse spatial geographic information so that the user has an idea about the resulting product.The concept of fuzzy sets\r\nis used for representation of classes, whose boundaries are not clearly (not sharply) set, namely, the fuzzy approach in overlaying\r\noperations realized in ESRI ArcGIS environment. The paper is based on a research project which is being solved at the Faculty of\r\nMilitary Technologies of the University of Defence.The research deals with the influence of geographic and climatic factors on the\r\nactivity of armed forces and the Integrated Rescue System....
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