Results 201 to 210 of about 194,690 (288)

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

A hybrid fuzzy-PIDD² control strategy for coordinated LFC and AVR in renewable-integrated multi-area power systems. [PDF]

Sci Rep
Omar MHT, Hamdy RA, Kotb H.
europepmc   +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

Fuzzy-logic-controlled DVR for enhancing the fault resilience of wind energy conversion systems. [PDF]

Sci Rep
Nori AM, Abdulabbas AK, Al Garni HZ, Mbasso WF, Alruwaili M, ELrashidi A.   +5 more
europepmc   +1 more source

Identifying Faults in Power Transformers Based on Machine‐Learning Algorithms Compared With Other Techniques

Energy Science &Engineering, EarlyView.
General framework of ensemble learning technique for transformer fault diagnostics compared with traditional dissolved gas analysis methods. ABSTRACT This paper implemented a comprehensive variety of modern machine‐learning techniques, which were demonstrated to be effective in handling complex tabular data, generating accurate predictions, and ...
Osama E. Gouda, Nourhan Ramadan, Matti Lehtonen, Mohamed M. F. Darwish   +3 more
wiley   +1 more source

Integrating Lyapunov based backstepping and neuro fuzzy logic with sliding mode control for precise trajectory tracking of differential drive robots. [PDF]

Sci Rep
Xu P, Maghsoudniazi M, Maghsoudniazi Y.
europepmc   +1 more source

Integrating General and Vocational Education to Sustain and Renew Traditional Chinese Culture: A Case Study of Chongqing Three Gorges Vocational College

Future in Educational Research, EarlyView.
ABSTRACT This study investigates how a Chinese higher vocational college can align skills training with the inheritance and innovative development of fine traditional Chinese culture. Grounded in perspectives that view vocational education as cultural transmission and identity work and informed by the lenses of general‐vocational integration and ...
Yuchang Xu, Dequan Zhu, Jiancheng Tan, Xue Pan, Fukui Zhao, Dufan Cao, Ning Wang, Ying Tang   +7 more
wiley   +1 more source

A novel intuitionistic fuzzy Yager aggregation framework for decision making in green supply chains. [PDF]

Sci Rep
Kumar Y, Ramalingam S, Zegeye GB.
europepmc   +1 more source

Financial time series forecasting with machine learning techniques:A survey [PDF]

, 2010
Finnie, Gavin, Krollner, Bjoern, Vanstone, Bruce   +2 more
core  

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