Results 171 to 180 of about 230,401 (283)

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

Neuromorphic robust framework for integrated estimation and control in dynamical systems using spiking neural networks. [PDF]

Sci Rep
Ahmadvand R, Sharif SS, Banad YM.
europepmc   +1 more source

Performance Prediction of Battery Pack Throughout the Entire Lifecycle Using Monte Carlo Algorithm and Joint Simulation of Multiple Physical Fields

Energy Science &Engineering, EarlyView.
ABSTRACT This article is based on the storage test of individual batteries. We combined the data analysis with the deductive simulation to predict the health status of the entire battery pack. Besides, we combined the storage process and discharge process of the battery pack based on the single‐cell storage test.
Liteng Zeng, Chuanbo Weng, Fei Xu, Kangpei Meng   +3 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

A versatile coherent Ising computing platform. [PDF]

Light Sci Appl
Wei H, Ai C, Guo P, Jia B, Yuan L, Song H, Chen S, Cao C, Wu J, Ju C, Ma Y, Fan J, Hu M, Wang C, Wen K.   +14 more
europepmc   +1 more source

Polymer Stress‐Tensor Calculation for a Laminar Submerged Viscoelastic Jet Flow Using Different Constitutive Models

International Journal for Numerical Methods in Fluids, EarlyView.
This study presents an efficient method to compute polymer stress‐tensor components in viscoelastic laminar jet flows using models such as Oldroyd‐B, Giesekus, PTT, and FENE. By assuming a stationary and parallel flow, the methodology significantly reduces computational cost.
Rafael de Lima Sterza, Leandro Franco de Souza, Marcio Teixeira de Mendonca, Analice Costacurta Brandi   +3 more
wiley   +1 more source

Interval-aware optimal control of PMSG-based wind energy conversion systems via piecewise Chebyshev inclusion. [PDF]

Sci Rep
Razmjooy N.
europepmc   +1 more source

Local Polynomial Regression and Filtering for a Versatile Mesh‐Free PDE Solver

International Journal for Numerical Methods in Fluids, EarlyView.
A high‐order, mesh‐free finite difference method for solving differential equations is presented. Both derivative approximation and scheme stabilisation is carried out by parametric or non‐parametric local polynomial regression, making the resulting numerical method accurate, simple and versatile. Numerous numerical benchmark tests are investigated for
Alberto M. Gambaruto
wiley   +1 more source

Enhancing image based classification for crop disease detection using a multiclass SVM approach with kernel comparison. [PDF]

Sci Rep
Sridhar P, Angamuthu P.
europepmc   +1 more source

Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents an evaluation of the accuracy of machine learning (ML) techniques in forecasting the realized volatility of West Texas Intermediate (WTI) crude oil prices. We compare several ML algorithms, including regularization, regression trees, random forests, and neural networks, to several heterogeneous autoregressive (HAR) models ...
Talha Omer, Kristofer Månsson, Pär Sjölander, Gazi Salah Uddin   +3 more
wiley   +1 more source