4.7 Article

Power plant turbine power trend prediction based on continuous prediction and online oil monitoring data of deep learning

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Green & Sustainable Science & Technology

Anomaly detection and condition monitoring of wind turbine gearbox based on LSTM-FS and transfer learning

Yongchao Zhu et al.

Summary: This study proposes a novel method for operational state prediction of wind turbine generators (WTGs) using limited monitoring data and fault information. The proposed method combines long short-term memory, fuzzy synthesis, and feature-based transfer learning to address the discrepancy in data distribution among the WTGs. Experimental results demonstrate that the proposed method can sensitively detect potential faults in advance and achieve high accuracy.

RENEWABLE ENERGY (2022)

Review Chemistry, Multidisciplinary

An Overview of Variants and Advancements of PSO Algorithm

Meetu Jain et al.

Summary: Particle swarm optimization (PSO) is a popular swarm-based optimization technique that is inspired by nature. It has gained attention from researchers in various fields due to its flexibility and easy implementation. Since its origin in 1995, researchers have improved and extended PSO, and made significant progress in theoretical analysis.

APPLIED SCIENCES-BASEL (2022)

Article Energy & Fuels

Power prediction of a wind farm cluster based on spatiotemporal correlations

Jiaan Zhang et al.

Summary: This paper proposes a new method based on spatiotemporal correlations to improve the accuracy of power prediction in wind farm clusters by analyzing the relationships and characteristics among wind farms in the cluster and using neural networks for prediction. This method has been validated using actual operating data from wind farm clusters in North China, demonstrating its feasibility and effectiveness in providing a high-precision approach to future wind farm cluster power predictions.

APPLIED ENERGY (2021)

Article Telecommunications

Malicious Traffic classification Using Long Short-Term Memory (LSTM) Model

K. Naresh Kumar Thapa et al.

Summary: This paper proposes a novel solution based on artificial intelligence perspective, developing a new malicious classification system using LSTM model. Experimental results demonstrate that the proposed model outperforms the state-of-the-art models in terms of accuracy and throughput, with an increase of 5% in accuracy and overall accuracy reaching 99.5%.

WIRELESS PERSONAL COMMUNICATIONS (2021)

Review Computer Science, Artificial Intelligence

Deep belief network based intrusion detection techniques: A survey

Insoo Sohn

Summary: With the increase in IoT devices, the amount of personal and sensitive data flowing through global networks has grown rapidly, making cybersecurity a crucial issue for future network evolution. Deep learning techniques, particularly deep belief networks (DBN), have become key solutions in detecting malicious attacks.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

Article Thermodynamics

Prediction of electricity generation from a combined cycle power plant based on a stacking ensemble and its hyperparameter optimization with a grid-search method

Zhijian Qu et al.

Summary: Electric power plays a significant role in society, and predicting power generation is crucial for electric power planning and energy utilization. A reliable forecasting model is necessary for accurate planning of electricity generation. This study aims to develop effective solutions for full-load power generation prediction of combined cycle power plants and proposes a method that provides more accurate predictions compared to traditional machine learning methods and other ensemble methods.

ENERGY (2021)

Article Computer Science, Information Systems

Short-Term Photovoltaic Power Prediction Based on Similar Days and Improved SOA-DBN Model

Wei Hu et al.

Summary: The study introduced a photovoltaic power prediction model based on similar days and a seagull optimization algorithm, and experimental results confirmed the high accuracy of the model.

IEEE ACCESS (2021)

Article Computer Science, Artificial Intelligence

Investigating the impact of data normalization on classification performance

Dalwinder Singh et al.

APPLIED SOFT COMPUTING (2020)

Article Engineering, Marine

An improved control-limit-based principal component analysis method for condition monitoring of marine turbine generators

Kun Yang et al.

JOURNAL OF MARINE ENGINEERING AND TECHNOLOGY (2020)

Article Engineering, Electrical & Electronic

Short Term Prediction of Photovoltaic Power Based on FCM and CG-DBN Combination

ZhengMing Li et al.

JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY (2020)

Article Automation & Control Systems

Multiscale Convolutional Neural Networks for Fault Diagnosis of Wind Turbine Gearbox

Guoqian Jiang et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2019)

Article Energy & Fuels

On the Assessment of a Numerical Weather Prediction Model for Solar Photovoltaic Power Forecasts in Cities

Harold Gamarro et al.

JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME (2019)

Review Computer Science, Artificial Intelligence

A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures

Yong Yu et al.

NEURAL COMPUTATION (2019)

Article Engineering, Multidisciplinary

Online Monitoring of Welding Status Based on a DBN Model During Laser Welding

Yanxi Zhang et al.

ENGINEERING (2019)

Article Engineering, Mechanical

Online Monitoring and Control of Flow rate in Oil Pipelines Transportation System by using PLC based Fuzzy-PID Controller

E. B. Priyanka et al.

FLOW MEASUREMENT AND INSTRUMENTATION (2018)

Article Engineering, Mechanical

Prediction of wear trend of engines via on-line wear debris monitoring

Wei Cao et al.

TRIBOLOGY INTERNATIONAL (2018)

Article Computer Science, Information Systems

Distributed Abnormal Behavior Detection Approach Based on Deep Belief Network and Ensemble SVM Using Spark

Naila Marir et al.

IEEE ACCESS (2018)

Article Thermodynamics

A combined multivariate model for wind power prediction

Tinghui Ouyang et al.

ENERGY CONVERSION AND MANAGEMENT (2017)

Review Engineering, Mechanical

Lubricating oil conditioning sensors for online machine health monitoring - A review

Xiaoliang Zhu et al.

TRIBOLOGY INTERNATIONAL (2017)

Article Computer Science, Artificial Intelligence

Tutorial on practical tips of the most influential data preprocessing algorithms in data mining

Salvador Garcia et al.

KNOWLEDGE-BASED SYSTEMS (2016)

Article Engineering, Electrical & Electronic

Day-Ahead Power Output Forecasting for Small-Scale Solar Photovoltaic Electricity Generators

Yue Zhang et al.

IEEE TRANSACTIONS ON SMART GRID (2015)

Article Engineering, Electrical & Electronic

Monthly electric energy demand forecasting based on trend extraction

Eva Gonzalez-Romera et al.

IEEE TRANSACTIONS ON POWER SYSTEMS (2006)

Article Computer Science, Artificial Intelligence

Learning to forget: Continual prediction with LSTM

FA Gers et al.

NEURAL COMPUTATION (2000)