A Hidden Markov Model (HMM) is a temporal statistical model which is widely utilized for various applications such as gene prediction, speech recognition and localization prediction. HMM represents the state of the process in a discrete variable, where the values are the possible observations of the world. For the purpose of process mining for resource allocation, HMM can be applied to discover...

cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. in recent decades, artificial neural network model has been increasingly applied to predict survival data. this research was conducted to compare cox regression and artificial neural network models in prediction of kidney transplant survival. the prese...

background: data mining (dm) is an approach used in extracting valuable information from environmental processes. this research depicts a dm approach used in extracting some information from influent and effluent wastewater characteristic data of a waste stabilization pond (wsp) in birjand, a city in eastern iran. methods: multiple regression (mr) and neural network (nn) models were examined us...

gully erosion constitutes a major problem in natural resources management and soil conservation, which causes severe land degradation in arid and semi-arid areas. therefore, determination of gully prone area and identification of gully conditioning factors can help to managers and decision makers to reduce the hazard of gully erosion. the aim of this study is to predictthe gully erosion suscept...

this research work is devoted to experimental and theoretical evaluations of a hybrid constitutive model which was designed to simulate the mechanical behavior of a tread rubber compound. the model is a combination of yeoh hyperelastic model with a strain-rate hysteresis model developed by bergstrom and boyce. the parameters of the yeoh model were calibrated from experimental data of the astm d...

In this study, a pellet scale model was developed for trickle bed reactor utilizing CFD techniques. Drag coefficients were calculated numerically at different velocities and bulk porosities in the case of single phase flow through the dry bed. The simulation results were then compared with the prediction of Kozeny-Carman (K-C) equation. The results indicated that drag coefficients calculated fr...

A plasticity-fracture constitutive model is presented for prediction of the behavior of confined plain concrete. A three-parameter yield surface is used to define the elastic limit. Volumetric plastic strain is defined as hardening parameter, which together with a nonlinear plastic potential forms a non-associated flow rule. The use of non-associated flow rule improves the prediction of the dil...

Slope stability analysis is an enduring research topic in the engineering and academic sectors. Accurate prediction of the factor of safety (FOS) of slopes, their stability, and their performance is not an easy task. In this work, the adaptive neuro-fuzzy inference system (ANFIS) was utilized to build an estimation model for the prediction of FOS. Three ANFIS models were implemented including g...

This study is concerned with the prediction of particles’ velocity in a dilute turbulent gas-solidboundary layer flow using a fully Eulerian two-fluid model. The closures required for equationsdescribing the particulate phase are derived from the kinetic theory of granular flows. Gas phaseturbulence is modeled by one-equation model and solid phase turbulence by MLH theory. Resultsof one-way and...

The relationship between annual water level of Danube and annual catches of Pontic shad (Alosa immaculata, Bennett 1835) in Romania were analyzed. For analysis of long term data on the Danube water level and Pontic shad catch (1920-2013), combinations of different methods were applied using programs Statistica, SPSS 13.0 and MATLAB 6. Periodograms, containing cyclic patterns, were obtained usin...