K-nearest neighbor (KNN) is an effective nonparametric classifier that determines the neighbors of a point based only on distance proximity. The classification performance KNN disadvantaged by presence outliers in small sample size datasets and its deteriorates with class imbalance. We propose local Bonferroni Mean Fuzzy K-Nearest Centroid Neighbor (BM-FKNCN) assigns label query dependent neare...

1570-8705/$ see front matter 2011 Elsevier B.V doi:10.1016/j.adhoc.2011.11.003 ⇑ Corresponding author. Tel.: +34 954 55 28 38. E-mail addresses: [email protected] (D.F. Larios) Barbancho), [email protected] (F.J. Molina), [email protected] The localization of the sensor nodes is a fundamental problem in wireless sensor networks. There are a lot of different kinds of solutions in the literature. Some of ...

This paper aims to establish the relationship between two apparent disparate problems: (i) the aggregation of uncertain information modelled by type-1 fuzzy sets via OWA mechanism, and (ii) the computation of the centroid of type-2 fuzzy sets. In order to cut down the computational complexity of the direct approach to performing type-1 OWA operation, the α-level approach to type-1 OWA operators...

This article develops a method of ratio estimate in fuzzy sense. By both the simple random sampling and stratified random sampling, we can obtain the ratio estimate in usual statistical sense. However, the sampling data may be ambiguous in some uncertain circumstance. To solve such kind of problem, we probe into the simple random sampling and stratified random sampling in fuzzy sense, obtain th...

Localization is one of the most important research topics in the wireless sensor network applications. To improve the indoor localization accuracy, the centroid localization algorithm based on Mamdani fuzzy system has been adopted to attain the weight between sensor node and anchor node. This paper proposes a novel optimized input membership function by bat algorithm in fuzzy inference system u...

Abstract: In this paper we improvise the work of Wang & Chen (2006) that used fuzzy numbers in the computation of consistent fuzzy preference relation (CFPR). Using the Herrera-Viedma et al. (2004) approach, we incorporate the centroid-index formula in constructing the evaluation matrices with fuzzy number elements. This will transform the fuzzy numbers into crisp values. The number of pair-wis...

Failure mode and effects analysis (FMEA) has been extensively used for examining potential failures in products, processes, designs and services. An important issue of FMEA is the determination of risk priorities of the failure modes that have been identified. The traditional FMEA determines the risk priorities of failure modes using the so-called risk priority numbers (RPNs), which require the...