[PDF][PDF] Statistical features based approach (SFBA) for hourly energy consumption prediction using neural network
In this paper, new statistical features based approach (SFBA) for hourly energy consumption
prediction using Multi-Layer Perceptron is presented. The model consists of four stages …
prediction using Multi-Layer Perceptron is presented. The model consists of four stages …
[HTML][HTML] Short-mid term electricity consumption prediction using non-intrusive attention-augmented deep learning model
Estimates of electricity consumption (EC) can provide effective guidance for energy
allocation and energy-saving measures. For improving the accuracy of short-mid term EC …
allocation and energy-saving measures. For improving the accuracy of short-mid term EC …
Forecasting building plug load electricity consumption employing occupant-building interaction input features and bidirectional LSTM with improved swarm intelligent …
Building energy consumption prediction is an essential foundation for energy supply-
demand regulation. Among them, plug-load energy consumption in buildings accounts for …
demand regulation. Among them, plug-load energy consumption in buildings accounts for …
Bus travel speed prediction using attention network of heterogeneous correlation features
Accurate bus travel speed prediction can lead to improved urban mobility by enabling
passengers to reliably plan their trips in advance and traffic administrators to manage the …
passengers to reliably plan their trips in advance and traffic administrators to manage the …
Energy Consumption Estimation for Electric Buses Based on a Physical and Data-Driven Fusion Model
X Li, T Wang, J Li, Y Tian, J Tian - Energies, 2022 - mdpi.com
The energy consumption of electric vehicles is closely related to the problems of charging
station planning and vehicle route optimization. However, due to various factors, such as …
station planning and vehicle route optimization. However, due to various factors, such as …
Comparison of machine learning algorithms for the power consumption prediction:-case study of tetouan city–
A Salam, A El Hibaoui - 2018 6th International Renewable and …, 2018 - ieeexplore.ieee.org
Predicting electricity power consumption is an important task which provides intelligence to
utilities and helps them to improve their systems' performance in terms of productivity and …
utilities and helps them to improve their systems' performance in terms of productivity and …
DLPformer: A Hybrid Mathematical Model for State of Charge Prediction in Electric Vehicles Using Machine Learning Approaches
Y Wang, N Chen, G Fan, D Yang, L Rao, S Cheng… - Mathematics, 2023 - mdpi.com
Accurate mathematical modeling of state of charge (SOC) prediction is essential for battery
management systems (BMSs) to improve battery utilization efficiency and ensure a good …
management systems (BMSs) to improve battery utilization efficiency and ensure a good …
Estimation of energy consumption of electric vehicles using deep convolutional neural network to reduce driver's range anxiety
The goal of this work is to reduce driver's range anxiety by estimating the real-time energy
consumption of electric vehicles using deep convolutional neural network. The real-time …
consumption of electric vehicles using deep convolutional neural network. The real-time …
Predictability of Vehicle Fuel Consumption Using LSTM: Findings from Field Experiments
G Wang, L Zhang, Z Xu, R Wang, SM Hina… - … Engineering, Part A …, 2023 - ascelibrary.org
It has been well-recognized that driving behaviors significantly impact the fuel consumption
of vehicles. To explore how well deep learning methods can predict fuel consumption …
of vehicles. To explore how well deep learning methods can predict fuel consumption …
Support vector regression with fruit fly optimization algorithm for seasonal electricity consumption forecasting
G Cao, L Wu - Energy, 2016 - Elsevier
Accurate monthly electricity consumption forecasting can provide the reliable guidance for
better energy planning and administration. However, it has been found that the monthly …
better energy planning and administration. However, it has been found that the monthly …