Horizontal directional drilling (HDD) is widely used in soil and rock engineering. In a variety of conditions, it is necessary to estimate the torque required for performing the reaming operation. Nevertheless, there is not presently a convenient method to accomplish this task. In this paper, to overcome this difficulty based on the basic concepts of rock engineering systems (RES), a model for ...

evaporation is one of the main parameters for the optimum operation of reservoirs, design of irrigation systems and scientific management of water resources. accurate estimation of the water evaporation level is crucial in any region especially in arid and semiarid regions. in this study, the feasibility of simulation of pan evaporation in maraghe station using the multiple regression models we...

one of the models that can be used to study the relationship between boolean random sets and explanatory variables is growth regression model which is defined by generalization of boolean model and permitting its grains distribution to be dependent on the values of explanatory variables. this model can be used in the study of behavior of boolean random sets when their coverage regions variation...

PURPOSE To develop a preoperative prediction model using a computer-assisted volumetric assessment of potential spared parenchyma to estimate the probability of chronic kidney disease (CKD, estimated glomerular filtration rate [eGFR] <60 mL/min/1.73 m(2)) 6 months from extirpative renal surgery (nephron-sparing surgery [NSS] or radical nephrectomy [RN]). PATIENTS AND METHODS Retrospective ana...

The potential use of TerraSAR-X and Radarsat-2 data for soil moisture retrieval over bare agricultural areas was investigated using both empirical and semi-empirical approaches. For the empirical approach, the Support Vector Regression (SVR) model was used with two cases: (1) using only one C-band or X-band image; and (2) using a pair of C-band and X-band images jointly. For the semi-empirical ...

This study applies unsupervised machine learning techniques for classification and clustering to a collection of descriptive variables from 10,442 lung cancer patient records in the Surveillance, Epidemiology, and End Results (SEER) program database. The goal is to automatically classify lung cancer patients into groups based on clinically measurable disease-specific variables in order to estim...

Active microwave remote sensing observations hold the potential for efficient and reliable mapping of spatial soil moisture distributions. However, soil moisture retrievals from microwave remote sensing techniques are typically complex because of the inherent difficulty in characterizing the interactions among land surface parameters that contribute to the retrieval process. Therefore adequate ...

This article has been compiled to identify the best model of housing price forecasting using machine learning methods with maximum accuracy and minimum error. Five important machine learning algorithms are used to predict housing prices, including Nearest Neighbor Regression Algorithm (KNNR), Support Vector Regression Algorithm (SVR), Random Forest Regression Algorithm (RFR), Extreme Gradient B...

The selection of independent variables in a regression model is often a challenging problem. Ideally, one would like to obtain the most adequate regression model. This task can be tackled with techniques such as expert based selection, stepwise regression and stochastic search heuristics, such as genetic algorithms (GA). In this study, we investigate the performance of two GAs for regressors se...