Smart and intelligent energy monitoring systems: A comprehensive literature survey and future research guidelines

T Hussain, FU Min Ullah, K Muhammad… - … Journal of Energy …, 2021 - Wiley Online Library
Computationally intelligent energy forecasting methods for appropriate energy management
at the consumer/producer side have a positive impact on the preservation of energy and …

Medical appliances energy consumption prediction using various machine learning algorithms

K Pagar, T Jain, H Kumar, A Bhardwaj… - Blockchain and Deep …, 2023 - Wiley Online Library
One of the greatest inventions of the 19th century was electricity, which now has become an
important part of our day‐to‐day life. However, many sources of electricity are exhaustible …

[PDF][PDF] 综合岭回归和 SARIMA 方法在桥梁健康监测数据分析中的应用

谌桢文, 常军 - 科学技术与工程, 2023 - stae.com.cn
摘要桥梁健康监测系统的实测数据普遍存在缺失问题, 为了保证桥梁监测数据的完整性,
更好地预测桥梁未来的健康状况, 提出了一种具有样本内和样本外预测能力的组合模型 …

Dynamic Breakdown Characteristics of GIS Disconnecting Switch Operation and Its Calculation of Operating Overvoltage in SF6/N2 Medium

WU **xiu, LI Yuanfang, Y **n… - Power System …, 2023 - epjournal.csee.org.cn
From the perspective of engineering application, the SF 6/N 2 mixture gas is still the most
effective alternative to the pure SF 6 gas. To provide a reference for the insulation …

LSTM-Based Deep Learning Model for Energy Management

S Hegde, SV Budihal, SV Siddamal - International Conference on …, 2023 - Springer
Smart home devices and its applications have a great potential in successfully predicting the
electricity consumption across households. The proposed framework comprises of a …

An Integrated Prediction Model for Building Energy Consumption: A Case Study

T Hu, Z Ding - … on Advancement of Construction Management and …, 2019 - Springer
As a large energy consumer, the building sector accounts for 30–40% of energy
consumption and around 40% of carbon emissions. How to improve energy efficiency in the …