To maximize asset reliability cost-effectively, maintenance should be scheduled based on the likely deterioration of an asset. A number of types of statistical model have been proposed for predicting this but they have important practical limitations. We present a Bayesian network model that can be used for maintenance decision support to overcome these limitations. The model extends an existin...

uncertainty associated with mixing models is often substantial, but has not yet been fully incorporated in models. the objective of this study is to develop and apply a bayesian-mixing model that estimates probability distributions of source contributions to a mixture associated with multiple sources for assessing the uncertainty estimation in sediment fingerprinting in zidasht catchment, iran....

Ratcliff, Gomez and McKoon (2004) suggested much of what goes on in lexical decision is attributable to decision processes, and may not be particularly informative about word recognition. They proposed that lexical decision should be characterized by a decision process, taking the form of a drift-diffusion model (Ratcliff, 1978), which operates on the output of lexical model. The present paper ...

Several activity-based transportation models are now becoming operational and are entering the stage of application for the modelling of travel demand. Some of these models use decision rules to support its decision making instead of principles of utility maximization. Decision rules can be derived from different modelling approaches. In a previous study, it was shown that Bayesian networks out...

A Bayesian network is a graphical model that encodes probabilistic relationships among variables of interest. Dynamic Bayesian networks are an extension of Bayesian networks for modeling dynamic processes. In this paper we present a decision support system based on a dynamic Bayesian network. Its purpose is to monitor the dry weight of patients suffering from chronic renal failure treated by he...

This article introduces a general framework of multi-granulation fuzzy probabilistic roughsets (MG-FPRSs) models in multi-granulation fuzzy probabilistic approximation space over twouniverses. Four types of MG-FPRSs are established, by the four different conditional probabilitiesof fuzzy event. For different constraints on parameters, we obtain four kinds of each type MG-FPRSs...

Intellectual Capital (IC) is one type of capital which is known as an intangible asset of an organization. Therefore, IC is claimed to be a valuable asset in the organization. However, the study of IC was not widely conducted in Thailand. IC includes human capital, structural capital and customer capital. This paper applies data mining techniques, classification algorithms for generating IC mod...

animal models are used to model the observations of animal performance that are genetically dependent.these models are considered as generalized linear mixed models and the genetic correlation structure of data is considered through random effects of breeding values. one goal of the mentioned models is to estimate variance components. in this research, an approximate bayesian approach presented...