4.6 Article

Ultra Short-Term Wind Power Forecasting Based on Sparrow Search Algorithm Optimization Deep Extreme Learning Machine

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 Computer Science, Information Systems

Multi-objective prediction intervals for wind power forecast based on deep neural networks

Min Zhou et al.

Summary: Wind power forecast plays a critical role in modern power systems, and this paper proposes a novel interval forecast model based on LSTM to construct prediction intervals effectively. An improved PI evaluation criterion and a multi-objective optimization framework are introduced to investigate the relationship between PI estimation error and average width. The proposed model and algorithm's effectiveness is demonstrated through experiments on real world wind power dataset.

INFORMATION SCIENCES (2021)

Article Chemistry, Physical

Optimal parameter identification of PEMFC stacks using Adaptive Sparrow Search Algorithm

Yanlong Zhu et al.

Summary: A new optimization algorithm called Adaptive Sparrow Search Algorithm (ASSA) is proposed for optimal model parameters identification of proton exchange membrane fuel cell (PEMFC) stacks. The algorithm has been applied to three case studies and shown to have the best efficiency and accuracy among the compared methods.

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY (2021)

Article Green & Sustainable Science & Technology

Day-Ahead Wind Power Forecasting Based on Wind Load Data Using Hybrid Optimization Algorithm

Guangyu Qin et al.

Summary: This study proposes a hybrid optimization algorithm to improve wind power forecasting accuracy, combining VMD, mRMR, LSTM, and FA algorithms to decompose sequences, analyze correlations, optimize parameters, and combine forecasting results for better prediction performance.

SUSTAINABILITY (2021)

Article Engineering, Electrical & Electronic

Optimal brain tumor diagnosis based on deep learning and balanced sparrow search algorithm

Tingting Liu et al.

Summary: In this study, MRI techniques are used for diagnosing brain tumors, focusing on tumor segmentation, feature extraction, and optimized CNN classification using the BSSA algorithm. The results show that the proposed method achieves high accuracy of 93.65% and specificity of 65.07% in tumor diagnosis, demonstrating significant improvements over competing methods.

INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY (2021)

Article Engineering, Multidisciplinary

A Regional Wind Power Probabilistic Forecast Method Based on Deep Quantile Regression

Yixiao Yu et al.

Summary: This article introduces a nonparametric probabilistic method for regional wind power forecast, which uses quantile regression neural networks (QRNN) and deep quantile regression to handle massive data. The model's performance is enhanced by applying local-connected methods and a ramp function, with test results demonstrating its effectiveness.

IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS (2021)

Article Computer Science, Information Systems

Short-Term Wind Power Prediction Based On Particle Swarm Optimization-Extreme Learning Machine Model Combined With Adaboost Algorithm

Guoqing An et al.

Summary: This paper proposes a wind power prediction model that combines Adaboost algorithm with extreme learning machine optimized by particle swarm optimization (PSO-ELM). The model is validated using measured data from a wind turbine in Turkey, showing higher prediction accuracy and better generalization ability compared to current wind power prediction methods.

IEEE ACCESS (2021)

Article Computer Science, Information Systems

Fault Diagnosis of Wind Turbines Based on a Support Vector Machine Optimized by the Sparrow Search Algorithm

Wumaier Tuerxun et al.

Summary: Fault diagnosis technology is crucial for the safe and stable operation of wind turbines, with support vector machines being a popular intelligence method in this field. The use of the sparrow search algorithm to optimize SVM parameters has resulted in the SSA-SVM model having high accuracy and optimization ability in wind turbine fault diagnosis.

IEEE ACCESS (2021)

Article Computer Science, Information Systems

Wind Power Forecasting Using Attention-Based Recurrent Neural Networks: A Comparative Study

Bin Huang et al.

Summary: Wind power is an efficient renewable resource, but accurately forecasting wind power generation can be challenging. This article explores the use of artificial recurrent neural networks in wind power forecasting, emphasizing the importance of utilizing attention mechanisms to capture spatial-temporal patterns in historical data.

IEEE ACCESS (2021)

Article Automation & Control Systems

Detection of COVID-19 Enhanced by a Deep Extreme Learning Machine

Aaqib Inam et al.

Summary: The outbreak of COVID-19 has had a significant impact worldwide. Diagnosis remains a challenge as there are currently no approved antiviral drugs and vaccines have only recently become available in some countries.

INTELLIGENT AUTOMATION AND SOFT COMPUTING (2021)

Article Computer Science, Information Systems

DMPPT Control of Photovoltaic Microgrid Based on Improved Sparrow Search Algorithm

Jianhua Yuan et al.

Summary: The study proposed a distributed maximum power point tracking method based on the sparrow search algorithm to solve the power mismatch loss issue in photovoltaic microgrid systems. By improving the algorithm with a center of gravity reverse learning mechanism and introducing a learning coefficient, it can track the maximum power point more accurately and quickly.

IEEE ACCESS (2021)

Article Computer Science, Information Systems

Intelligent Software-Defined Network for Cognitive Routing Optimization Using Deep Extreme Learning Machine Approach

Fahd Alhaidari et al.

Summary: As network systems become more complex and heterogeneous, the need for greater intelligence to effectively prepare, control, maintain, and optimize networks is highlighted. SDN offers new possibilities for intelligence in networks, simplifying the application of machine learning strategies with its characteristic features.

CMC-COMPUTERS MATERIALS & CONTINUA (2021)

Article Computer Science, Information Systems

Deep extreme learning machine with leaky rectified linear unit for multiclass classification of pathological brain images

Deepak Ranjan Nayak et al.

MULTIMEDIA TOOLS AND APPLICATIONS (2020)

Article Green & Sustainable Science & Technology

Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm

Ling-Ling Li et al.

JOURNAL OF CLEANER PRODUCTION (2020)

Article Computer Science, Artificial Intelligence

Hourly day-ahead wind power forecasting with the EEMD-CSO-LSTM-EFG deep learning technique

A. Shobana Devi et al.

SOFT COMPUTING (2020)

Article Computer Science, Artificial Intelligence

Modelling, simulation, and optimization of diabetes type II prediction using deep extreme learning machine

Abdur Rehman et al.

JOURNAL OF AMBIENT INTELLIGENCE AND SMART ENVIRONMENTS (2020)

Article Green & Sustainable Science & Technology

Photovoltaic Power Prediction Using Artificial Neural Networks and Numerical Weather Data

Javier Lopez Gomez et al.

SUSTAINABILITY (2020)

Article Engineering, Multidisciplinary

Applying GMDH neural network to estimate the thermal resistance and thermal conductivity of pulsating heat pipes

Mohammad Hossein Ahmadi et al.

ENGINEERING APPLICATIONS OF COMPUTATIONAL FLUID MECHANICS (2019)

Article Green & Sustainable Science & Technology

The impact of wind field spatial heterogeneity and variability on short-term wind power forecast errors

Mao Yang et al.

JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY (2019)

Article Green & Sustainable Science & Technology

Prediction of ultra-short-term wind power based on BBO-KELM method

Jun Li et al.

JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY (2019)

Article Computer Science, Information Systems

Optimization of LMBP high-speed railway wheel size prediction algorithm based on improved adaptive differential evolution algorithm

Yu Zhang et al.

INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS (2019)

Article Engineering, Electrical & Electronic

Ultra-short-term forecast of wind speed and wind power based on morphological high frequency filter and double similarity search algorithm

D. Y. Hong et al.

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2019)

Article Thermodynamics

Applicability of connectionist methods to predict thermal resistance of pulsating heat pipes with ethanol by using neural networks

Mohammad Hossein Ahmadi et al.

INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER (2018)

Article Green & Sustainable Science & Technology

Short-Term Wind Electric Power Forecasting Using a Novel Multi-Stage Intelligent Algorithm

Haoran Zhao et al.

SUSTAINABILITY (2018)

Article Engineering, Electrical & Electronic

A Fingerprint Method for Indoor Localization Using Autoencoder Based Deep Extreme Learning Machine

Zahra Ezzati Khatab et al.

IEEE SENSORS LETTERS (2018)