The economic growth of every nation is highly related to its electricity infrastructure, network,
and availability since electricity has become the central part of everyday life in this modern …

Electric load forecasting (ELF) is a vital process in the planning of the electricity industry and
plays a crucial role in electric capacity scheduling and power systems management and …

In the era of ever-changing market landscape, enterprises tend to make quick and informed
decisions to survive and prosper in the competition. Decision makers within an organization …

In this paper, we present a feature fusion method designed for the Gaussian process
model's kernel functions for the probabilistic long-term load forecasting. To enrich the …

This study focuses on the important issue of predicting electricity load for efficient energy
management. To achieve this goal, different statistical methods were compared, and results …

In order to realize the goal of optimal use of energy sources and cleaner environment at a
minimal cost, researchers; field professionals; and industrialists have identified the …

The paper proposes a mathematical model for long‐term load forecast (LTLF) based on
parametric and time series statistical techniques. The flowchart of the proposed algorithm …

Purpose The purpose of this study is to present a hybrid approach to model and predict long-
term energy peak load using Bayesian and Holt–Winters (HW) exponential smoothing …

Forecasting retail sales often requires various number of products from different stores.
Existing deep or machine learning techniques fall short of producing accurate classification …

Climate variability creates energy demand uncertainty and complicates long-term asset
management and budget planning. Without understanding future energy demand trends …