Klinkenberg permeability is an important parameter in tight gas reservoirs. There are conventional methods for determining it, but these methods depend on core permeability. Cores are few in number, but well logs are usually accessible for all wells and provide continuous information. In this regard, regression methods have been used to achieve reliable relations between log readings and Klinke...

Quantitative Structure-Property Relationship (QSPR) models for modeling and predicting thermodynamic properties such as the enthalpy of vaporization at standard condition (ΔH˚vap kJ mol-1) and normal temperature of boiling points (T˚bp K) of 57 mono and Polycyclic Aromatic Hydrocarbons (PAHs) have been investigated. The PAHs were randomly separated into 2 groups: training and test sets. A set o...

Social network is the mainstream medium of current information dissemination, and it particularly important to accurately predict its propagation law. In this paper, we introduce a social model integrating multiple linear regression infectious disease model. Firstly, proposed features that affect communication from three dimensions. Then, predicted node influence via regression. Lastly, used as...

one of the most important aspects of software project management is the estimation of cost and time required for running information system. therefore, software managers try to carry estimation based on behavior, properties, and project restrictions. software cost estimation refers to the process of development requirement prediction of software system. various kinds of effort estimation patter...

Land resource management requires extensive land mapping. Conventional soil mapping takes a long time and is expensive; therefore, geographic information system data as predictor in texture modeling can be used an alternative solution to shorten reduce costs. Through digital elevation model data, topographic variability obtained independent variable predicting texture. Geographically weighted r...

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 ...

Regression and linear programming provide the basis for popular techniques for estimating technical efficiency. Regression-based approaches are typically parametric and can be both deterministic or stochastic where the later allows for measurement error. In contrast, linear programming models are nonparametric and allow multiple inputs and outputs. The purported disadvantage of the regression-b...