In this paper, a new set of spline functions called ``Flat End Fuzzy Spline" is defined to interpolate given fuzzy data. Some important theorems on these splines together with their existence and uniqueness properties are discussed. Then numerical examples are presented to illustrate the differences between of using our spline and other interpolations that have been studied before.

abstract— in this paper, a new extended method of multi criteria decision making based on fuzzy-topsis theory is introduced. fuzzy mcdm algorithm for determining the best choice among all possible choices when the data are fuzzy is also presented. using a new index leads to procedure for choosing fuzzy ideal and negative ideal solutions directly from the fuzzy data observed alternatives.in this...

In recent years, fuzzy rough set theory has emerged as a suitable tool for performing feature selection. Fuzzy rough feature selection enables us to analyze the discernibility of the attributes, highlighting the most attractive features in the construction of classifiers. However, its results can be enhanced even more if other data reduction techniques, such as instance selection, are considere...

Data envelopment analysis (DEA) is a widely used mathematical programming approach for evaluating the relative efficiency of decision making units (DMUs) in organizations. Crisp input and output data are fundamentally indispensable in traditional DEA evaluation process. However, the input and output data in real-world problems are often imprecise or ambiguous. In this study, we present a four-p...

The way human beings communicate is contextdependent and it is not easily reproduced on traditional computer systems. We propose combined advances in Context-aware Computing and Fuzzy Databases with the aim of producing more intelligent, flexible and personalized systems. We focus on the interaction of users with a Database System where contextual data could affect the output. We present a deve...

A hybrid modeling technique is proposed to make models during the development phase of a fed-batch bioprocess. A limited amount of data is available and experimental data are therefore combined with a priori information about the mass balances and the chemical reaction network inside the cell (the metabolic network). This information highly constraints the model, and only a few degrees of freed...

Genetic Algorithms (GAs) and other evolutionary optimization methods to design fuzzy rules from data for systems modeling and classification have received much attention in recent literature. We show that different tools for modeling and complexity reduction can be favorably combined in a scheme with GA-based parameter optimization. Fuzzy clustering, rule reduction, rule base simplification and...

The Composite Link Model is a generalization of the generalized linear model in which expected values of observed counts are constructed as a sum of generalized linear components. When combined with penalized likelihood, it provides a powerful and elegant way to estimate haplotype probabilities from observed genotypes. Uncertain ("fuzzy") genotypes, like those resulting from AFLP scores, can be...

The present article proposes a fuzzy set-based classifier with a better learning and generalization capability. The proposed classifier exploits the feature-wise degree of belonging of a pattern to all classes, generalization in the fuzzification process and the combined class-wise contribution of features effectively. The classifier uses a -type membership function and product aggregation reas...

Product quality strongly depend on production process quality. So, performance of production process must be strictly monitored. Statistical Process Control (SPC) is a technique used for evaluate process performance using statistical method to analyze, control, and influence process performance improvement. Combined of two control chart, individual chart and cusum chart could improve performanc...