Short-term load forecasting (STLF) enables distribution system operators to perform efficient
energy management by flexibly engaging energy consumers under the intelligent demand …

Many day-to-day operation decisions in a smart city need short term load forecasting (STLF)
of its customers. STLF is a challenging task because the forecasting accuracy is affected by …

Introduction: This study utilizes a machine learning model to predict unhealthy alcohol use
treatment levels among women of childbearing age. Methods: In this cross-sectional study …

This research aims to propose an effective model for the detection of defective Printed
Circuit Boards (PCBs) in the output stage of the Surface-Mount Technology (SMT) line. The …

Background The computerised classification and prediction of heart disease can be useful
for medical personnel for the purpose of fast diagnosis with accurate results. This study …

Web-page recommendation commands a predominant part in smartweb systems.  
Discovery of meaningfulinformation from web utilization data and improvedrepresentation of …

Objective: This study presents a method for optimal selection of gene subsets to enhance
the non-clinical diagnostic classification and prediction of colorectal cancer using gene …

In this era of big data, high-dimensional data analysis has emerged as a critical area of
research with applications ranging from genomics to finance and machine learning. Outliers …

Objective: This study presents a method fo selection of gene subsets to enhance the non
classification and prediction of colorectal cancer using gen sion level of gene expression …

Работа посвящена анализу кейсов использования бисериальных коэффициентов в
различных исследовательских областях для оценки мер связей в данных. В данной …