The task of reducing the computational complexity contour detection in images is considered article. solution to achieved by modifying Canny detector and number passes through original image. In first case, two are excluded when determining adjacency central pixel with eight adjacent ones a frame size 3х3. second three excluded, as case third one necessary determine angle gradient direction. Th...

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 ...

A novel scheme for developing, at low computational cost, neural-fuzzy classifiers based on large-scale, model-based exemplars is outlined. The new method extends the approach that Bezdek applied to train a neural net (NN) Sobel edge classifier by training the NN on the complete population of 3x3 binary image prototypes scored to fuzzy values by a classical operator. We first show that, replaci...

This paper presents an extension of the multimode resource-constrained project scheduling problem for a large scale construction project where multiple parallel projects and a fuzzy random environment are considered. By taking into account the most typical goals in project management, a cost/weighted makespan/quality trade-off optimization model is constructed. To deal with the uncertainties, a...

This paper proposes a bilevel multiobjective optimization model with fuzzy coefficients to tackle a stone resource assignment problem with the aim of decreasing dust and waste water emissions. On the upper level, the local government wants to assign a reasonable exploitation amount to each stone plant so as to minimize total emissions and maximize employment and economic profit. On the lower le...

This study proposes a novel neural-network-based fuzzy group forecasting model for foreign exchange rates prediction. In the proposed model, some single neural network models are first used as predictors for foreign exchange rates prediction. Then these single prediction results produced by each single neural network models are fuzzified into some fuzzy prediction representations. Subsequently,...

In this paper we present a study on inference in a Fuzzy Logic Controller (FLC). Many different implication operators have been proposed in the Fuzzy Logic literature; we take into account five of them that have already been used in fuzzy control. In order to evaluate the advantages and disadvantages of each implication in practical applications, we consider the controller's defuzzified output ...

Recently, Gasimov and Yenilmez proposed an approach for solving two kinds of fuzzy linear programming (FLP) problems. Through the approach, each FLP problem is first defuzzified into an equivalent crisp problem which is non-linear and even non-convex. Then, the crisp problem is solved by the use of the modified subgradient method. In this paper we will have another look at the earlier defuzzifi...

Fuzzy risk analysis, as a powerful tool to address uncertain information, can provide an appropriate method for risk analysis. However, the previous fuzzy risk analysis methods still have some weaknesses. To overcome the weaknesses of existing fuzzy risk analysis methods, a novel method for ranking generalized fuzzy numbers is proposed for addressing fuzzy risk analysis problems. In the propose...