Selecting a learning algorithm to implement for a particular application on the basis of
performance still remains an ad-hoc process using fundamental benchmarks such as …

This work compares user's perception about indoor environmental quality (IEQ) and
corporate satisfaction in green building and similar ones: specifically, three green buildings …

Ecological environmental early-warning can make timely warning to predict the ecosystem
degradation and the deterioration of environmental quality caused by industry development …

The aim of this study was to estimate the occurrence of Bartonella spp. per household in cats
and the risk factors for Bartonella spp. positivity in cats and their owners from Valdivia, Chile …

Abstract Background: The Adverse Childhood Experiences (ACEs) study articulated the
negative effects of childhood trauma on adult weight and health. The purpose of the current …

Back propagation neural network (BPNN) models and multiple linear regression (MLR)
models are widely used to predict heating energy consumption. To improve the prediction …

Companies are pinning high hopes on competitive advantages through data analytics. So
far, value gains through analytics have been demonstrated for IT-heavy and data-rich …

The article is devoted to the using of machine learning algorithms for the diagnosis of human
diseases on the basis of General blood analysis. The value of this research is in the strategy …

Sampling fraction is crucial to sampling-related studies and applications, especially in the
big data era when most data are neither originally designed nor controllable in the data …

Prediction insolvency is one of the most important issues during creditworthiness
assessment, especially in the turmoil environment. That is why the problem of insolvency …