The aim of this paper is to give a. sketch of a foundation of statistical analysis with fuzzy data, extending the methodology of Mathematical Stat,istics. For t.his purpose it will be discussed to equip the fuzzy sample spaces with suitable a-algebras and metrics. As the main application the parameter estimation in linear regression models with crisp parameters und fuzzy-valued variables will b...

Traditional statistical methods for seismic zonation require information from many subjects, such as regional geology and neotectonics, seismicity, stress field, damage analysis of historic earthquakes, geophysics and others. These subjects are weighted differently during statistics. In fact, the information from most of these subjects is more like fuzzy sets, ie, it is a sort of estimation rat...

Function Points is an important and well-accepted software size metric. However, it is absolutely essential to accurately calibrate Function Point (FP), whose aims are to fit specific software application, to reflect software industry trend, and to improve cost estimation. Neuro-Fuzzy is a technique that incorporates the learning ability from neural network and the ability to capture human know...

This paper presents the development of fuzzy‐ appearance manifold and fuzzy‐nearest distance calculation in the eigenspace domain for pose estimation of degraded face images. In order to obtain a robust pose estimation system which can deal with the fuzziness of face data caused by statistical errors, we proposed the fuzzy‐vector representation in eigenspace domain of the...

The major prevailing challenges for Software Projects are Software Estimations like cost estimation, effort estimation, quality estimation and risk analysis. Though there are several algorithmic cost estimation models in practice, each model has its own pros and cons for estimation. There is still a need to find a model that gives accurate estimates. This paper is an attempt to experiment diffe...

In this paper, we propose a scalar variable formation of fuzzy regression model based on the axiomatic credibility measure foundation. The fuzzy estimation for fuzzy regression coefficients is investigated. A general M-estimation criterion is developed under Maximum Fuzzy Uncertainty Principle, which resulted in weighted Normal equation with adjusted term for M-estimator of the regression coeff...

This paper studies fuzzy filtering design for a class of nonlinear discrete-time uncertain stochastic systems. First, the Takagi and Sugeno fuzzy model is proposed to approximate a nonlinear discrete-time uncertain stochastic system. Next, based on the fuzzy model, the fuzzy estimation for nonlinear discrete-time uncertain stochastic systems is studied. Using a suboptimal approach, the fuzzy es...

Some asymptotic properties of point estimation with n-dimensional fuzzy data with respect to a special L2-metric ρ are investigated in this paper. It is shown that the collection of all n-dimensional fuzzy data endowed with the ρ-metric is a complete and separable space. Some criterions for point estimation in such fuzzy environments are proposed and the sample mean and variance and covariance ...

Software cost estimation is a challenging and onerous task. Estimation by analogy is one of the expedient techniques in software effort estimation field. However, the methodology utilized for the estimation of software effort by analogy is not able to handle the categorical data in an explicit and precise manner. Early software estimation models are based on regression analysis or mathematical ...

awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. therefore, the present study two hybrid models, wavelet- adaptive neural fuzzy interference system (wanfis) and wavelet- artificial neural network (wann) are used for flow prediction of gamasyab river (nahavand, hamedan, iran...