in this paper, a maximum likelihood estimation and a minimum entropy estimation for the expected value and variance of normal fuzzy variable are discussed within the framework of credibility theory. as an application, a credibilistic portfolio selection model is proposed, which is an improvement over the traditional models as it only needs the predicted values on the security returns instead of...

In this paper, a maximum likelihood estimation and a minimum entropy estimation for the expected value and variance of normal fuzzy variable are discussed within the framework of credibility theory. As an application, a credibilistic portfolio selection model is proposed, which is an improvement over the traditional models as it only needs the predicted values on the security returns instead of...

The Bayesian reliability estimation under fuzzy environments is proposed in this paper. In order to apply the Bayesian approach, the fuzzy parameters are assumed to be fuzzy random variables with fuzzy prior distributions. The (conventional) Bayesian estimation method will be used to create the fuzzy Bayes point estimator of reliability by invoking the well-known theorem called ‘Resolution Iden...

This paper reviews the use of Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for vector-controlled induction motor drives. While conventional schemes do not deal well with the highly nonlinear nature of motor control, fuzzy logic with its adjustability and neural networks with their adaptability have been shown to be excellent alternatives. ANFIS combines the advantages of fuzzy logic and neura...

Software development effort estimation is among one of the most challenging jobs that software developers need to perform. Due to the lack of information during the early stages of software development, the developers often express their inability to estimate accurately the effort, cost and schedule of the software under consideration. This inaccuracy in estimation leads to monetary losses as w...

The present study deals with the inverse DEA using the non-radial Enhanced Russell (ER)-measure in the presence of fuzzy data. This paper proposes a technique to treat the fuzzy data in the problem of simultaneous estimation of input-output levels. Necessary and sufficient conditions are provided for ER-measure maintaining in the presence of fuzzy data. A numerical example with real data is pre...

Software Cost Estimation is the challenging factor in project management. Accurate cost estimation helps to complete project with in time and budget. Due to this behavior of the project it is considered as a risky project .Under these conditions risk management is mandatory. Large numbers of estimation models have been proposed over the last 30 years. Constructive Cost Model (COCOMO) is one of ...

As software cost drivers are fuzzy and uncertain, software cost estimates are prone to a certain degree of estimation errors especially in their early stages of software development life cycle. However, most of the existing software cost estimation models in present literature only generate a single point estimate and do not explicitly reveal the degree of risks caused by their inaccuracies. Th...

This paper investigates delay-dependent robust asymptotic state estimation of fuzzy neural networks with mixed interval time-varying delay. In this paper, the Takagi–Sugeno (T–S) fuzzy model representation is extended to the robust state estimation of Hopfield neural networks with mixed interval time-varying delays. The main purpose is to estimate the neuron states, through available output mea...

Six-Sigma has some measures which measure performance characteristics related to a process. In most of the traditional methods, exact estimation is used to assess these measures and to utilize them in practice. In this paper, to estimate some of these measures, including Defects per Million Opportunities (DPMO), Defects per Opportunity (DPO), Defects per unit (DPU) and Yield, a new algorithm ba...