Zobrazeno 1 - 10
of 117
pro vyhledávání: '"Suheel Abdullah"'
Autor:
Muhammad Usman Riaz, Suheel Abdullah Malik, Amil Daraz, Hasan Alrajhi, Ahmed N. M. Alahmadi, Abdul Rahman Afzal
Publikováno v:
Energies, Vol 17, Iss 20, p 5040 (2024)
The primary goal of a power distribution system is to provide nominal voltages and power with minimal losses to meet consumer demands under various load conditions. In the distribution system, power loss and voltage uncertainty are the common challen
Externí odkaz:
https://doaj.org/article/3d0aa9a21d2f4aba80fd5aea933829f6
Autor:
Amil Daraz, Irfan Ahmed Khan, Abdul Basit, Suheel Abdullah Malik, Salman A. AlQahtani, Guoqiang Zhang
Publikováno v:
Heliyon, Vol 10, Iss 6, Pp e28073- (2024)
Recent widespread connections of renewable energy resource (RESs) in place of fossil fuel supplies and the adoption of electrical vehicles in place of gasoline-powered vehicles have given birth to a number of new concerns. The control architecture of
Externí odkaz:
https://doaj.org/article/5996f593b88b4cbeb6b738d20a40bc9a
Autor:
Farhan Zafar, Suheel Abdullah Malik, Tayyab Ali, Amil Daraz, Abdul Rahman Afzal, Farkhunda Bhatti, Irfan Ahmed Khan
Publikováno v:
PLoS ONE, Vol 19, Iss 2 (2024)
Externí odkaz:
https://doaj.org/article/1e0a7f189ff44e4994d23791e2c23cd2
Autor:
Ghulam Fareed Laghari, Suheel Abdullah Malik, Irfan Ahmed Khan, Amil Daraz, Salman A. AlQahtani, Hayat Ullah
Publikováno v:
IEEE Access, Vol 11, Pp 38485-38501 (2023)
This paper presents a pragmatic approach established on the hybridization of nature-inspired optimization algorithms and Bernstein Polynomials (BPs), achieving the optimum numeric solution for Nonlinear Optimal Control Problems (NOCPs) of dynamical s
Externí odkaz:
https://doaj.org/article/54cceb5e9f7b4bd3b3bb8a5fb0ac489c
Autor:
Hayat Ullah, Muhammad Amir, Muhammad Iqbal, Suheel Abdullah Malik, Muhammad Mohsin Khan Jadoon
Publikováno v:
IEEE Access, Vol 11, Pp 7551-7563 (2023)
In this work a new thresholding function referred to as ’mixture model shrinkage’ (MMS) based on the minimization of a convex cost function is proposed. Normally, thresholding functions underestimate larger signal amplitudes during the de-noising
Externí odkaz:
https://doaj.org/article/31ec75bcb6f348f4bf2cea1b06b6fd34
Autor:
Amil Daraz, Suheel Abdullah Malik, Ahmad Taher Azar, Sheraz Aslam, Tamim Alkhalifah, Fahad Alturise
Publikováno v:
IEEE Access, Vol 10, Pp 43514-43527 (2022)
The interconnection of renewable energy systems, which are complex nonlinear systems, often results in power fluctuations in the interconnection line and high system frequency due to insufficient damping in extreme and dynamic loading situations. To
Externí odkaz:
https://doaj.org/article/af221d9b260942c89e21a48ac668fda9
Autor:
Ghulam Fareed Laghari, Suheel Abdullah Malik, Amil Daraz, Azmat Ullah, Tamim Alkhalifah, Sheraz Aslam
Publikováno v:
IEEE Access, Vol 10, Pp 50298-50313 (2022)
In this paper, a heuristic scheme based on the hybridization of Bernstein Polynomials (BPs) and nature-inspired optimization techniques is presented to achieve the numerical solution of Nonlinear Optimal Control Problems (NOCPs) efficiently. The solu
Externí odkaz:
https://doaj.org/article/3d4efdd469104f608b2a318301df3c73
Publikováno v:
Frontiers in Energy Research, Vol 10 (2023)
Automatic generation control (AGC) in modern power systems (PS) is difficult because the output power of many power resources is intermittent, and the load and system parameters vary widely. In this paper, a novel control scheme known as the wavelet
Externí odkaz:
https://doaj.org/article/ebaa87c663904cc7a116f14843440a85
Publikováno v:
IEEE Access, Vol 9, Pp 18962-18973 (2021)
The existence of pulmonary nodules exhibits the presence of lung cancer. The Computer-Aided Diagnostic (CAD) and classification of such nodules in CT images lead to improve the lung cancer screening. The classic CAD systems utilize nodule detector an
Externí odkaz:
https://doaj.org/article/837b2c167e224f03a13c468c91e2113e
Publikováno v:
IEEE Access, Vol 9, Pp 113415-113427 (2021)
The Pulmonary nodule indicates the presence of lung cancer. The deep convolutional neural networks (DCNNs) have been widely used to classify the pulmonary nodule as benign or malignant. However, an individual learner usually performs unsatisfactorily
Externí odkaz:
https://doaj.org/article/e74b37b421c54e798a30fa3730dc983e