[HTML][HTML] Challenges associated with Hybrid Energy Systems: An artificial intelligence solution
MR Maghami, AGO Mutambara - Energy Reports, 2023 - Elsevier
Abstract Hybrid Energy Systems (HES) combine multiple energy sources to maximize
energy efficiency. Due to the unpredictability and dependence on the weather, integrating …
energy efficiency. Due to the unpredictability and dependence on the weather, integrating …
Hybrid attention-based temporal convolutional bidirectional LSTM approach for wind speed interval prediction
BS Bommidi, V Kosana, K Teeparthi… - … Science and Pollution …, 2023 - Springer
Precise wind speed prediction is crucial for the management of the wind power generation
systems. However, the stochastic nature of the wind speed makes optimal interval prediction …
systems. However, the stochastic nature of the wind speed makes optimal interval prediction …
Data Analysis of Decision Support for Sustainable Welfare in The Presence of GDP Threshold Effects: A Case Study of Interactive Data Exploration
Energy usage and GDP have been the subject of numerous studies over the past decades. It
has been overlooked by previous studies that energy consumption correlates with economic …
has been overlooked by previous studies that energy consumption correlates with economic …
Experimental and numerical analysis of the energy performance of a water/soil exchanger coupled to a cooling floor for North Africa
This paper presents an experimental and numerical study on the energy performance of a
water/soil heat exchanger coupled to a cooling floor. The system shows two galvanized steel …
water/soil heat exchanger coupled to a cooling floor. The system shows two galvanized steel …
[PDF][PDF] A Deep Learning Prediction Model to Predict Sustainable Development in Saudi Arabia
F Aljuaydi, B Behera, A Elshewey… - Applied Mathematics & …, 2024 - naturalspublishing.com
This paper introduces a novel deep learning model specifically designed for predicting
climate change in Saudi Arabia until the year 2030. The proposed model, called CNN …
climate change in Saudi Arabia until the year 2030. The proposed model, called CNN …
DCNN‐GCM: A Deep CNN and Granger Causality Models for Forecasting Welfare Level of Energy‐Producing Countries and Evaluating the Relationship between …
N Hoseinbor, SN Mousavi… - … Problems in Engineering, 2022 - Wiley Online Library
From the beginning of creation, human beings have realized the importance of energy for
survival. They have always devoted a significant part of their energy to provide the required …
survival. They have always devoted a significant part of their energy to provide the required …
A Novel Method to Detect Partial Shadow Effects in Perovskite-Based Simulated Solar Cell System Faults
A Sharifi Miavaghi, A Esmaeili - Micromachines, 2023 - mdpi.com
When a fault occurs in photovoltaic systems, a human expert should be present at the scene
and perform tests to determine the location and type of the fault. In such a situation, in order …
and perform tests to determine the location and type of the fault. In such a situation, in order …
[PDF][PDF] Energy Reports
MR Maghami, AGO Mutambara - 2022 - researchgate.net
abstract Hybrid Energy Systems (HES) combine multiple energy sources to maximize
energy efficiency. Due to the unpredictability and dependence on the weather, integrating …
energy efficiency. Due to the unpredictability and dependence on the weather, integrating …
[PDF][PDF] Research Article DCNN-GCM: A Deep CNN and Granger Causality Models for Forecasting Welfare Level of Energy-Producing Countries and Evaluating the …
N Hoseinbor, SN Mousavi, A Aminifard - 2022 - academia.edu
From the beginning of creation, human beings have realized the importance of energy for
survival. ey have always devoted a significant part of their energy to provide the required …
survival. ey have always devoted a significant part of their energy to provide the required …