[HTML][HTML] Forecasting: theory and practice
Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …
uncertainty that surrounds the future is both exciting and challenging, with individuals and …
[HTML][HTML] Comprehensive review of load forecasting with emphasis on intelligent computing approaches
In this paper, a comprehensive review is presented for mid-term load forecasting. The basic
loads and effective factors are studied, and then several classifications are presented for …
loads and effective factors are studied, and then several classifications are presented for …
Short-term multi-energy load forecasting for integrated energy systems based on CNN-BiGRU optimized by attention mechanism
D Niu, M Yu, L Sun, T Gao, K Wang - Applied Energy, 2022 - Elsevier
Accurate short-term multi-energy load forecasting is an essential prerequisite for ensuring
the reliable and economic operation of integrated energy systems (IES). Considering the …
the reliable and economic operation of integrated energy systems (IES). Considering the …
[BOOK][B] Practical machine learning for data analysis using python
A Subasi - 2020 - books.google.com
Practical Machine Learning for Data Analysis Using Python is a problem solver's guide for
creating real-world intelligent systems. It provides a comprehensive approach with concepts …
creating real-world intelligent systems. It provides a comprehensive approach with concepts …
Power load probability density forecasting using Gaussian process quantile regression
Y Yang, S Li, W Li, M Qu - Applied Energy, 2018 - Elsevier
Accurately predicting the power load in certain areas is of great importance for grid
management and power dispatching. A great deal of research has been conducted within …
management and power dispatching. A great deal of research has been conducted within …
[HTML][HTML] ML-based energy management of water pum** systems for the application of peak shaving in small-scale islands
This study introduces an energy management method that smooths electricity consumption
and shaves peaks by scheduling the operating hours of water pum** stations in a smart …
and shaves peaks by scheduling the operating hours of water pum** stations in a smart …
A comparative analysis of machine learning approaches for short-/long-term electricity load forecasting in Cyprus
D Solyali - Sustainability, 2020 - mdpi.com
Estimating the electricity load is a crucial task in the planning of power generation systems
and the efficient operation and sustainable growth of modern electricity supply networks …
and the efficient operation and sustainable growth of modern electricity supply networks …
A RNN based time series approach for forecasting turkish electricity load
RNN, LSTM and GRU variations have been increasing its popularity on time-series
applications. Liberalization of Turkish Electricity Market empowers the necessity of better …
applications. Liberalization of Turkish Electricity Market empowers the necessity of better …
Short-term load forecasting based on PSO-KFCM daily load curve clustering and CNN-LSTM model
C Shang, J Gao, H Liu, F Liu - Ieee Access, 2021 - ieeexplore.ieee.org
Short-term load forecasting (STLF) with excellent precision and prominent efficiency plays a
significant role in the stable operation of power grid and the improvement of economic …
significant role in the stable operation of power grid and the improvement of economic …
A hybrid forecasting model for short-term power load based on sample entropy, two-phase decomposition and whale algorithm optimized support vector regression
W Li, Q Shi, M Sibtain, D Li, DE Mbanze - IEEE access, 2020 - ieeexplore.ieee.org
To improve the accuracy and reliability of short-term power load forecasting and reduce the
difficulty caused by load volatility and non-linearity, a hybrid forecasting model (CEEMDAN …
difficulty caused by load volatility and non-linearity, a hybrid forecasting model (CEEMDAN …