The need to update the calibration of Function Point (FP) complexity weights is discussed, 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 knowledge from fuzzy logic. The empirical validation using ISBSG d...

A survey of fuzzy logic applications and principles in wireless communications is presented, with the aim of highlighting successful usage of fuzzy logic techniques in applied telecommunications and signal processing. To the best of our knowledge, this is the first such study of its kind. This paper will focus firstly on discerning prevalent fuzzy logic or fuzzy-hybrid approaches in the areas o...

––Software development cost estimation is important for effective project management. Many models have been introduced to predict software development cost. In this paper, a novel emotional COnstructive Cost MOdel II (COCOMO II) has been proposed for software cost estimation. In COCOMO II only the project characteristics are considered, whereas the characteristics of team members are also impor...

estimation of river sediment load is one of the most important issues in design of hydraulic structures, investigating water quality, conserving fish habitat, estimating erosion and determining watershed management effects. there are two methods for estimating sediment load: empirical and hydrological methods. existence of numerous empirical methods for estimation of river sediment load and a w...

fuzzy linear regression models are used to obtain an appropriate linear relation between a dependent variable and several independent variables in a fuzzy environment. several methods for evaluating fuzzy coefficients in linear regression models have been proposed. the first attempts at estimating the parameters of a fuzzy regression model used mathematical programming methods. in this the...

This paper proposes a fuzzy-identification-based adaptive control scheme for the chaotic dynamic systems using backstepping control approach, which is referenced as adaptive fuzzy backstepping control (AFBC). The proposed AFBC offers a design approach to drive the chaotic trajectory to track a desired trajectory, and it is comprised of a fuzzy backstepping controller and a robust controller. Th...

This communication is concerned with the problem of supervised classification of fuzzy data obtained from a random experiment. The data generation process is modelled through fuzzy random variables which, from a formal point of view, can be identified with a kind of functional random element. We propose to adapt one of the most versatile discriminant approaches in the context of functional data...

We present an application of type-2 neuro-fuzzy modeling to stock price prediction based on a given set of training data. Type-2 fuzzy rules can be generated automatically by a self-constructing clustering method and the obtained type-2 fuzzy rules cab be refined by a hybrid learning algorithm. The given training data set is partitioned into clusters through input-similarity and output-similari...

In this article authors presented selected methods of risk factors and safety estimation in air transport including use of fuzzy logic inference systems (fuzzy expert inference systems are under consideration) Keywords—safety; aviation; risk factors; fuzzy inference systems.

A method is proposed for estimating the parameters in a parametric statistical model when the observations are fuzzy and are assumed to be related to underlying crisp realizations of a random sample. This method is based on maximizing the observeddata likelihood defined as the probability of the fuzzy data. It is shown that the EM algorithm may be used for that purpose, which makes it possible ...