Results 221 to 230 of about 190,933 (296)

Ensemble Deep Learning–Based Wind Power Forecasting With Self‐Adaptive Osprey Optimization Algorithm

Energy Science &Engineering, EarlyView.
Design of Self‐Adaptive Osprey (SAO) algorithm: The novel SAO algorithm is designed by integrating the exploration capability of the conventional Osprey algorithm by including the self‐adaptiveness for enhancing the convergence rate. Ensemble Deep Learning for wind power forecasting: The wind forecasting is employed using the proposed Ensemble learning
Johncy Bai Johnson, Sivarani Thankamony Saradha Devi, Kumar Chandrasekaran, Sourav Barua   +3 more
wiley   +1 more source

Machine Learning‐Driven Classification and Production Capacity Prediction of Tight Sandstone Reservoirs: A Case Study of the Taiyuan Formation, Ordos Basin

Energy Science &Engineering, EarlyView.
On the basis of core and log data, a Bayesian‐Optimized Random Forest model achieved 92.76% accuracy in classifying tight sandstone reservoirs. A gray relational analysis‐derived evaluation index shows > 80% consistency with actual gas zones. ABSTRACT Tight sandstone gas (TSG), an unconventional oil–gas resource, has heterogeneous reservoirs ...
Yin Yuan, Haijiao Fu, Detian Yan, Gang Wang, Shuguang Yang, Mengmeng Liu, Qingling Jiang, Xiaoming Wang, Wei Wang   +8 more
wiley   +1 more source

Robust Learning Control for Shipborne Manipulator With Fuzzy Neural Network. [PDF]

Front Neurorobot, 2019
Xu Z, Li W, Wang Y.
europepmc   +1 more source

Smart Solar Power Site Selection Through a Hybrid Computational Framework of Neuro‐Fuzzy With Genetic Algorithm Optimization

Energy Science &Engineering, EarlyView.
Solar Power plants at various locations a: Pavagada SPP, Karnataka b: Bhadla SPP, Rajasthan c: West Bengal Solar Park ABSTRACT This paper presents a new neuro‐fuzzy multi‐criteria decision‐making (MCDM) framework designed to optimize the selection of solar power plant (SPP) sites across India.
Rajkumari Malemnganbi Devi, Benjamin A. Shimray, Ingudam Chitrasen Meitei, Khelchandra Thongam, Shuma Adhikari, Anuradha Laishram, Subir Datta, Ahmed Al Mansur, Taha Selim Ustun   +8 more
wiley   +1 more source

Robust Control Using a Matrix Converter to Enhance Wind Turbine Systems

Energy Science &Engineering, EarlyView.
This study uses a more efficient and effective solution to improve the operational performance of a wind turbine‐based power system. This system uses a doubly fed induction generator and relies on a matrix converter and fractional‐order proportional–integral controller.
Sihem Ghoudelbourk, Habib Benbouhenni, Adil Yahdou, Zakaria Mohamed Salem Elbarary, Nicu Bizon   +4 more
wiley   +1 more source

Disturbance‐Resilient Voltage/Power‐Quality Management for Islanded Inverters Using Self‐Tuning Type‐3 Fuzzy Controller

Energy Science &Engineering, EarlyView.
An adaptive fuzzy controller using an interval type‐3 fuzzy logic system replaces the SMC switching term to mitigate chattering while preserving global stability for islanded inverters. Simulations show lower THD, greater robustness to disturbances and parameter variations, and improved voltage‐tracking accuracy, with applicability to other uncertain ...
Man‐Wen Tian, Jun‐Bo Mao, Nurkhat Zhakiyev, Didar Yedilkhan, Ruslan Omirgaliyev, Du Changdong, Amirhossein Khosravi Sarvenoee, Ardashir Mohammadzadeh   +7 more
wiley   +1 more source

Interpretable Tree‐Based Models for Predicting Short‐Term Rockburst Risk Considering Multiple Factors

Energy Science &Engineering, EarlyView.
Interpretable tree‐based models integrate microseismic, geological, and mining indicators to predict short‐term rockburst risk. SHAP analysis reveals the dominant role of energy‐related features and clarifies nonlinear factor interactions, enabling transparent and reliable early‐warning in deep coal mines.
Shuai Chen, Linming Dou, Atao Li, Wu Cai, Lei Zhang   +4 more
wiley   +1 more source

Electronic jelly: Engineering the mechanics of hydrogels for flexible electronics

FlexMat, EarlyView.
By unifying mechanical reinforcement strategies—double networks, structural ordering, and dynamic interactions—this review demonstrates how engineered hydrogels can transcend their fragility to achieve the strength, toughness, and reliability required for flexible electronics, including wearable sensors, energy devices, and soft robotic systems ...
Tianfu Zheng, Chongling Cheng, Dayang Wang   +2 more
wiley   +1 more source

Recent advances in multifunctional soft robots: A materials–structures–systems co‐design perspective for synergistic integration

FlexMat, EarlyView.
Abstract Soft robots, engineered from highly compliant materials, offer superior adaptability and safety in unstructured environments compared to their rigid counterparts. Recent advancements, fueled by bio‐inspiration and material programmability, have led to the rapid co‐evolution of their core modules: actuation, sensing, protection, energy, and ...
Qiulei Liu, Zicao Peng, Chong Sun, Haitao Yang   +3 more
wiley   +1 more source

Electricity Price Prediction Using Multikernel Gaussian Process Regression Combined With Kernel‐Based Support Vector Regression

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents a new hybrid model for predicting German electricity prices. The algorithm is based on a combination of Gaussian process regression (GPR) and support vector regression (SVR). Although GPR is a competent model for learning stochastic patterns within data and for interpolation, its performance for out‐of‐sample data is not ...
Abhinav Das, Stephan Schlüter, Lorenz Schneider   +2 more
wiley   +1 more source