Intelligent controllers and optimization algorithms for building energy management towards achieving sustainable development: Challenges and prospects
Buildings account for a significant amount of energy consumption leading to the issues of
global emissions and climate change. Thus, energy management in a building is …
global emissions and climate change. Thus, energy management in a building is …
Deep residual learning-based fault diagnosis method for rotating machinery
Effective fault diagnosis of rotating machinery has always been an important issue in real
industries. In the recent years, data-driven fault diagnosis methods such as neural networks …
industries. In the recent years, data-driven fault diagnosis methods such as neural networks …
Wind speed forecasting using nonlinear-learning ensemble of deep learning time series prediction and extremal optimization
As an essential issue in wind energy industry, wind speed forecasting plays a vital role in
optimal scheduling and control of wind energy generation and conversion. In this paper, a …
optimal scheduling and control of wind energy generation and conversion. In this paper, a …
A novel hybrid model based on VMD-WT and PCA-BP-RBF neural network for short-term wind speed forecasting
Y Zhang, B Chen, G Pan, Y Zhao - Energy Conversion and Management, 2019 - Elsevier
Accurate short-term wind power forecasting is significant for rational dispatching of the
power grid and ensuring the power supply quality. In order to enhance the accuracy of short …
power grid and ensuring the power supply quality. In order to enhance the accuracy of short …
Constrained population extremal optimization-based robust load frequency control of multi-area interconnected power system
This paper proposes a robust proportional-integral (PI) controller with its parameters
designed by constrained population extremal optimization for load frequency control …
designed by constrained population extremal optimization for load frequency control …
An adaptive deep reinforcement learning approach for MIMO PID control of mobile robots
Intelligent control systems are being developed for the control of plants with complex
dynamics. However, the simplicity of the PID (proportional–integrative–derivative) controller …
dynamics. However, the simplicity of the PID (proportional–integrative–derivative) controller …
Constrained multi-objective population extremal optimization based economic-emission dispatch incorporating renewable energy resources
Economic emission dispatch (EED) problem of an electrical power system can be
considered as one of the most popular constrained multi-objective optimization problems to …
considered as one of the most popular constrained multi-objective optimization problems to …
A hybrid electricity price forecasting model with Bayesian optimization for German energy exchange
H Cheng, X Ding, W Zhou, R Ding - … Journal of Electrical Power & Energy …, 2019 - Elsevier
Electricity price forecasting affects the operation of the entire electricity market and it is
extremely important to every market participant. In this paper, a novel hybrid method, with …
extremely important to every market participant. In this paper, a novel hybrid method, with …
A filter-based feature construction and feature selection approach for classification using Genetic Programming
J Ma, X Gao - Knowledge-Based Systems, 2020 - Elsevier
Feature construction and feature selection are two common pre-processing methods for
classification. Genetic Programming (GP) can be used to solve feature construction and …
classification. Genetic Programming (GP) can be used to solve feature construction and …
Evolutionary manifold regularized stacked denoising autoencoders for gearbox fault diagnosis
JB Yu - Knowledge-Based Systems, 2019 - Elsevier
Vibration signals are widely employed to fulfill gearbox fault diagnosis in real-world cases.
However, it is quite challenging to extract effective fault features from noised vibration …
However, it is quite challenging to extract effective fault features from noised vibration …