this paper presents a prediction model based on a new neuro-fuzzy algorithm for estimating time in construction projects. the output of the proposed prediction model, which is employed based on a locally linear neuro-fuzzy (llnf) model, is useful for assessing a project status at different time horizons. being trained by a locally linear model tree (lolimot) learning algorithm, the model is int...

Comparing the performance of a set of activities or organizations under uncertainty environment has been performed by means of Fuzzy Data Envelopment Analysis (FDEA) since the traditional DEA models require accurate and precise performance data. As regards a method for dealing with uncertainty environment, many researchers have introduced DEA models in fuzzy environment. Some of these models ar...

Regarding the fact that getting a suitable combination of the human resources and service stations is one of the important issues in the most service and manufacturing environments, In this paper, we have studied the two models of planning queuing systems and its effect on the cost of the each system by using two fuzzy queuing models of M/M/1 and M/E2/1. In the first section, we have compar...

this paper studies housing choice under fuzzy circumstances. in this article, fuzzy distance method is employed for selection process. methodology of housing choice with fuzzy distance approach is based on the minimizing fuzzy distance of features from desired amount under fuzzy condition. meanwhile, in the discrete choice models, housing choice is based on utility maximizing of available optio...

in this paper, the researchers present a multi-objective linear fractional inventory model using fuzzy pro-gramming. the proposed method in this paper is applied to a problem with two objective functions. the re-sulted fuzzy model is transformed into an ordinary linear programming. the implementation of the develop-ing model presented in this paper is demonstrated through the use of some numeri...

We use the basic binomial option pricing method but allow someor all the parameters in the model to be uncertain and model this uncertaintyusing fuzzy numbers. We show that with the fuzzy model we can, with areasonably small number of steps, consider almost all possible future stockprices; whereas the crisp model can consider only n + 1 prices after n steps.

the goal of this paper is to show how the concept of fuzzy logic can be used to establish a degree to which an investment project belongs to a class of risk. also, the probability of the fuzzy event is presented and is ap-plied to calculate the probability of the fuzzy event “the project x is a good investment”. this process has to enable the decision maker to compare several alternative invest...

introduction the ardabil plain aquifer, with area about 900 km2, has high concentration amounts of nitrate in some parts. nowadays, nitrate pollution in groundwater due to the widespread application of fertilizers and increasing of drinking water demand, has encountered consumers with problem. the adverse health effects of high nitrate levels in drinking water have been well documented. in the ...

A special method for fuzzy-logic-based system modeling is presented to develop multi-variable fuzzy models on the basis of the system's measured input and output data. The global modeling problem is proposed to be solved in two steps: by fuzzy model connguration and fuzzy model identiication. The fuzzy model connguration procedure is characterized by preliminary considerations leading to the de...