Energy forecasting
-
Short-term prediction of regional energy consumption by metaheuristic optimized deep learning models
Modern civilization is heavily dependent on energy, which burdens the energy sector. Therefore, a highly accurate energy consumption forecast is essential to provide valuable information for efficient energy distribution and storage. This study proposed a hybrid deep learning model, called I-CNN-JS, by incorporating a jellyfish search (JS) algorithm into an ImageNetwinning convolutional neural network (I-CNN) to predict weekahead energy consumption.
6p 
vibenya
31-12-2024
6
2
Download
-
Climate change has had significant impacts on the global climate, affecting the operational efficiency of buildings. This study employs future climate prediction methods based on the latest IPCC scenarios, using General Circulation Models (GCMs) to forecast climate conditions in three regions of Vietnam.
6p vibenya
31-12-2024
4
2
Download
-
The purpose of the thesis is described as follows: To develop an independent simulation model for IEEE 803.2az Energy Efficient Ethernet Standards with Active and Idle modes of operations; To design and simulate a traffic source generator with exponentially distributed inter-arrival periods, and forecast the duration of the next idle periods, based in the distribution of packet arrivals; To extend the simulation of Dynamic power management in Access networks with the inclusion of prioritized traffic, which changes the duration of low power modes;…
141p runthenight07
01-03-2023
11
3
Download
