In order to study the effect of R2O/Al2O3 (where R=Na or K), SiO2/Al2O3, Na2O/K2O and H2O/R2O molar ratios on the compressive strength (CS) of Metakaolin base geopolymers, more than forty data were gathered from literature. To increase the number of data, some experiments were also designed. The resulted data were utilized to train and test the three layer artificial neural network (ANN). Bayes...

Dynamic Bayesian network is the extension of Bayesian network in solving time series problems .It can be well dealt with the time-varying multivariable problem. A state model is given based on Dynamic Bayesian network. The model can more accurately describe the relationship between the system state and the influencing factors. Single-step and multi-step prediction algorithms are given to predic...

One of the most important processes in the early stages of construction projects is to estimate the cost involved. This process involves a wide range of uncertainties, which make it a challenging task. Because of unknown issues, using the experience of the experts or looking for similar cases are the conventional methods to deal with cost estimation. The current study presents data-driven metho...

State-of-the-art Bayesian Network learning algorithms do not scale to more than a few hundred variables; thus, they fall far short from addressing the challenges posed by the large datasets in biomedical informatics (e.g., gene expression, proteomics, or text-categorization data). In this paper, we present a BN learning algorithm, called the Max-Min Bayesian Network learning (MMBN) algorithm th...

We present new algorithms for learning Bayesian networks from data with missing values using a data augmentation approach. An exact Bayesian network learning algorithm is obtained by recasting the problem into a standard Bayesian network learning problem without missing data. As expected, the exact algorithm does not scale to large domains. We build on the exact method to create an approximate ...

A feasibility study of using of Dynamic Bayesian Networks in combination with ARMA modeling in exchange rate prediction is presented. A new algorithm (ARMA-DBN) is constructed and applied to the exchange rate forecast of RMB. Results show that the improved dynamic Bayesian forecast algorithm has better performance than the standard ARMA model.

With Internet entering all walks of life, development internet and usage expansion demand better performance, especially the application 5G network that adopts NAS networking mode. Some bandwidth cannot fully support current demand, which causes fluctuations other concerns. In this paper, a method for optimizing topological structure bottom layer communication is proposed has outage performance...

It has been attempted to reveal regulatory information from microarray data using Bayesian network [1]. However, due to limitation of microarray, successful result is obtained only under a limited condition. For this reason, Bayesian network from combining microarray with biological knowledge was proposed [2]. In this paper, we proposed Bayesian network learned by genetic algorithm to infer gen...