Time series forecasting is one of the main goals of time series analysis, whether it uses
conventional, advance, or hybrid method. One of the most popular and commonly used …

Time series are one of the most common data types encountered by data scientists and, in
the context of today's exponentially increasing data, learning how to best model them to …

In recent decades, the operational impact of Artificial Intelligence (AI) strategies is massively
dominating the scientific arena of improving the operation of energy systems and their hybrid …

Photovoltaic (PV) modules play an important role in modern distribution networks; however,
from the beginning, PV modules have mostly been used in order to produce clean, green …

Installation of down-hole gauges in oil wells to determine Flowing Bottom-Hole Pressure
(FBHP) is a dominant process especially in wells lifted with electrical submersible pumps …

In data mining classification techniques are used to predict group membership for data
instances. These techniques are capable of processing a wider variety of data and the …

Abstract ASEAN through ASEAN Economics Community (AEC) 2020 treaty has proposed
financial integration via capital markets integration in order to aim comprehensive ASEAN …

The losses in distribution networks have always been key elements in predicting investment,
planning work, evaluating the efficiency and effectiveness of a network. This paper …

Purpose: Support vector regression (SVR) has long been known as a great tool in
forecasting. SVR combined with evolutionary algorithms have been used in many …

Abstract Objective: Prediction of Short term electrical load forecasting with the help of
Sensitivity Analysis. Methods/Statistical Analysis: Traditional and Intelligent methods are …