In statistical inference, the point estimation problem is very crucial and has a wide range of applications. When, we deal with some concepts such as random variables, the parameters of interest and estimates may be reported/observed as imprecise. Therefore, the theory of fuzzy sets plays an important role in formulating such situations. In this paper, we rst recall the crisp uniformly minimum ...

With the rapid development of information and automation technology, manufacturing system is evolving towards more complexity integration. The components will inevitably suffer from degeneration, impact component-level failure on reliability a valuable issue to be studied, especially when dependence exists among components. Thus, it vital construct evaluation mechanism that helps characterize h...

Large Scale Signal Processing systems are incapable of storing and working on data which change at high frequencies with large differences in the operating range. This paper looks at an easier method of solving this problem by constructing dynamic fuzzy logic based neural networks after sampling the data using through Bayesian classifier based probabilities. This technique has also been extende...

Most Gene Regulatory Network (GRN) studies ignore the impact of the noisy nature of gene expression data despite its significant influence upon inferred results. This paper presents an innovative Collateral-Fuzzy Gene Regulatory Network Reconstruction (CF-GeNe) framework for Gene Regulatory Network (GRN) inference. The approach uses the Collateral Missing Value Estimation (CMVE) algorithm as it...

The interactions among peers in Peer-to-Peer systems as a distributed collaborative system are based on asynchronous and unreliable communications. Trust is an essential and facilitating component in these interactions specially in such uncertain environments. Various attacks are possible due to large-scale nature and openness of these systems that affects the trust. Peers has not enough inform...

in this study, an image backlight compensation method using adaptive luminance modification is proposed for efficiently obtaining clear images.the proposed method combines the fuzzy c-means clustering method, a recurrent functional neural fuzzy network (rfnfn), and a modified differential evolution.the proposed rfnfn is based on the two backlight factors that can accurately detect the compensat...

A Bayesian model coupled with a fuzzy neural network (BFNN) is developed to alleviate the difficulty of using geophysical data in lithology estimation when cross correlation between lithology and geophysical attributes is nonlinear. The prior estimate is inferred from borehole lithology measurements using indicator kriging based on spatial correlation, and the posterior estimate is obtained fro...

The interactions among peers in Peer-to-Peer systems as a distributed collaborative system are based on asynchronous and unreliable communications. Trust is an essential and facilitating component in these interactions specially in such uncertain environments. Various attacks are possible due to large-scale nature and openness of these systems that affects the trust. Peers has not enough inform...

This paper proposes an online Bayesian Ying-Yang (OBYY) clustering algorithm, which is then applied to the fuzzy cerebellar model articulation controller (FCMAC). Inspired by ancient Chinese Ying-Yang philosophy, Xu’s Bayesian Ying Yang (BYY) learning has been successfully applied to clustering by harmonizing the visible input data (Yang) and the invisible clusters (Ying). In this research, the...

Classifying web users in a personalised search setup is cumbersome due the very nature of dynamism in user browsing history. This fluctuating nature of user behaviour and user interest shall be well interpreted within a fuzzy setting. Prior to analysing user behaviour, nature of user interests has to be collected. This work proposes a fuzzy based user classification model to suit a personalised...