Nowadays, time-series modelling techniques are widely used for prediction and forecasting
of non-stationary data's. The study analyses the continuous one-year ambient noise data …

Climate change and Energy are the prominent topics addressed by researchers in the 21st
century. One of the concerns shown by the researchers is the amount of CO2 emitted by …

This study proposes a hybrid prediction model using sparrow search algorithm (SSA) to
optimize the convolutional neural network (CNN) and support vector machine (SVM), in …

Air pollution is a widespread problem in India. The study focuses on forecasting the air
quality index (AQI) using time series modeling techniques for the most polluted area of …

This paper presents application of an improved Harmony Search (HS) technique and
Charged System Search algorithm (CSS) to estimate transport energy demand in Iran …

The relationship between energy consumption and supply is a primary factor in the planning
and operation of power systems. Brazil is experiencing major problems with the energy …

Estimation of solar energy is essential for the identification of suitable locations for solar-
based energy systems and their optimal sizing. In this work, capability of adaptive neuro …

Purpose For decades, continuous research work is going on to maximize the power
harvested from the sun; however, there is only a limited analysis on exploiting the microwatt …

ABSTRACT A reliable occupancy prediction model plays a critical role in improving the
performance of energy simulation and occupant-centric building operations. In general …

This study analyzes the impact of employing different features on the performance of future
occupancy prediction models. The aim is to identify the most effective predictor variables for …