In this research we applied classification models for prediction of students' performance, and
cluster models for grouping students based on their cognitive styles in e-learning …

Road transport today is dominated by oil-delivered fuels and internal combustion engines
and such a high level of dependence on one single source of primary energy carries …

Support Vector Regression is becoming one of the most attractive models for load
forecasting, in recent years. The performance of Support Vector Regression deeply depends …

In recent years, support vector regression (SVR) models have been widely applied in short-
term electricity load forecasting. A critical challenge when applying the SVR model is to …

Nowadays, the modern economies depend on electricity. Its production and consumption
(load) have to be in equilibrium at all times since storing electricity, in a substantial quantity …

Featured Application As the load characteristics of power systems tend to be complex, the
difficulty of accurate and reliable load point prediction is constantly increasing, and it is more …

Basic aim of this study is to identify the quality of cotton by using knowledge of computer,
which help to identify quality in cotton industries Most of the existing supervised …

Support vector machines (SVM) is a machine learning framework that has exhibited
optimum performance in the functions of classification and clustering. This study explored …

환경규제와 자동차 시장 패러다임 변화로 전기자동차의 보급이 활발해지고 있다. 하지만
전기자동차의 수가 점차 늘어나면서, 소비자의 전기자동차 충전 패턴에 따라 전기자동차 …

Краткосрочное прогнозирование электропотребления энергорайонов и региона с
учетом метеофакторов КОРЗИНА ПОИСК НАВИГАТОР ЖУРНАЛЫ КНИГИ ПАТЕНТЫ …