Electrical discharge machining has the capability of machining complicated shapes in electrically conductive materials independent of hardness of the work materials. This present article details the development of multiple regression models for envisaging the material removal rate and roughness of machined surface in electrical discharge machining of Hastelloy C276. The experimental runs are de...

Construction material prices (CMP) variations have become a major issue in properly budgeting construction projects. Inability to accurately forecast CMP volatility can also lead price overestimation or underestimation. Enhancing the accuracy of predictions enhance total costs. The purpose this study is present model for predicting that assist decision-makers make better decisions over life cyc...

abstract spatial prediction of soil organic carbon is a crucial proxy to manage and conserve natural resources, monitoring co2 and preventing soil erosion strategies within the landscape, regional, and global scale. the objectives of this study was to evaluate capability of artificial neural network and multivariate linear regression models in order to predict soil organic carbon using terrain ...

In this work some quantitative structure activity relationship models were developed for prediction of three bioenvironmental parameters of 28 volatile organic compounds, which are used in assessing the behavior of pollutants in soil. These parameters are; half-life, non dimensional effective degradation rate constant and effective Péclet number in two type of soil. The most effective descripto...

rock sawability prediction and determination of effective parameters are important in the cost estimation and the planning of the stone factories. an accurate estimation of rock sawability and performance prediction of sawing machine helps to make the planning of the rock sawing projects more efficient. it is necessary to predict the rock sawability and determine the effective parameters to ach...

Air quality prediction is highly important in view of the health impacts caused by exposure to air pollutants in urban air. This work has presented a model based on support vector machine (SVM) technique to predict daily average carbon monoxide (CO) concentrations in the atmosphere of Tehran. Two types of SVM regression models, i.e. -SVM and -SVM techniques, were used to predict average daily C...

a quantitative structure-activity relationship (qsar) study was conducted for the prediction of inhibitory activity of 1-phenyl[2h]-tetrahydro-triazine-3-one analogues as inhibitors of 5-lipoxygenase. the inhibitory activities of the 1-phenyl[2h]-tetrahydro-triazine-3-one analogues modeled as a function of molecular structures using chemometrics methods such as multiple linear regression (mlr) ...