The current study introduces the hybridization of Nonlinear Sine Cosine Algorithm (NSCA) and Safe Experimentation Dynamics (SED) as a novel optimization method for model order reduction high-order single-input single-output (SISO) systems. Reciprocated synergism between both meta-heuristic algorithms is achieved by appropriating nonlinear position-updated mechanism NSCA enhanced exploration/exp...

Nowadays, improvement in power system performance is essential to obtaine economic and technical benifits. To achieve this, optimize the large number of parameters based on optimal flow(OPF). For solving OPF problem efficiently, it needs robust fast optimization techniques. This paper proposes application a newly developed hybrid Whale Sine Cosine algorithm solve OPF. It has been implemented fo...

Abstract This paper investigates the problem of incipient fault detection and diagnosis (FDD) in wind energy conversion systems (WECS) using an innovative effective approach called ensemble learning-sine cosine optimization algorithm (EL-SCOA). The evolved strategy involves two primary steps: first, a sine-cosine is used to extract optimize features order only select most descriptive ones. Seco...

Abstract The sine cosine algorithm (SCA) is a metaheuristic proposed in recent years that does not resort to nature-related metaphors but explores and exploits the search space with help of two simple mathematical functions cosine. SCA has fewer parameters structure widely used various fields. However, it tends fall into local optimality because have well-balanced exploitation exploration phase...

Hyperspectral Remote Sensing (HRS) is an emergent, multidisciplinary paradigm with several applications, which are developed on the basis of material spectroscopy, radiative transfer, and imaging spectroscopy. HRS plays a vital role in agriculture for crops type classification soil prediction. The recently artificial intelligence techniques can be used using HRS. This study develops Intelligent...

The students’ performance prediction (SPP) problem is a challenging that managers face at any institution. Collecting educational quantitative and qualitative data from many resources such as exam centers, virtual courses, e-learning systems, other not simple task. Even after collecting data, we might imbalanced missing biased different types strings, numbers, letters. One of the most common ch...

Computation of principal angles between subspaces is important in many applications, e.g., in statistics and information retrieval. In statistics, the angles are closely related to measures of dependency and covariance of random variables. When applied to column-spaces of matrices, the principal angles describe canonical correlations of a matrix pair. We highlight that all popular software code...

FFTW is an implementation of the discrete Fourier transform (DFT) that adapts to the hardware in order to maximize performance. This paper shows that such an approach can yield an implementation that is competitive with handoptimized libraries, and describes the software structure that makes our current FFTW3 version flexible and adaptive. We further discuss a new algorithm for real-data DFTs o...