Fast and accurate identification of pulsar signals is important for X-ray pulsar-based navigation (XNAV). Traditional signal detection technology based on FFT search epoch folding (EF) requires a very long time to obtain an appropriate signal-to-noise ratio (SNR) gain, especially weak with low photon fluxes. This paper proposes adaptive stochastic resonance (SR) method the grey wolf optimizer (...

Congestion and overloading for lines are the main problems in the exploitation of power grids. The consequences of these problems in deregulated systems can be mentioned as sudden jumps in prices in some parts of the power system, lead to an increase in market power and reduction of competition in it. FACTS devices are efficient, powerful and economical tools in controlling power flows through ...

Multilevel inverters are a new class of dc-ac converters designed for high-power medium voltage and power applications as they work at high switching frequencies in renewable by avoiding stresses like dv/dt has low harmonic distortion their output voltage. In variable speed drives generation systems, the use multilevel is obligatory. To estimate positions inverter configuration with value, fast...

Crude oil market analysis has become one of the emerging financial markets and volatility effect is paramount been considered as an issue utmost importance. This study examines dynamics this volatile crude by employing a hybrid approach based on extreme learning machine (ELM) regressor improved grey wolf optimizer (IGWO) for prophesying rate West Texas Intermediate (WTI) Brent datasets. The dat...

Abstract The continuous cone penetration test (CPT) measurements provide an advantageous liable rapid tool for stratification and soil behavior classification that can be employed in the sustainable design of infrastructures. However, CPT are often interpreted by geotechnical experts because involved complexities uncertainties. In this study, a novel type (SBT) model is developed to identify tr...

Feature selection is a fundamental pre-processing step in machine learning that aims to reduce the dimensionality of dataset by selecting most effective features from original features. This process regarded as combinatorial optimization problem, and grey wolf optimizer (GWO), novel meta-heuristic algorithm, has gained popularity feature due its fast convergence speed easy implementation. In th...

The purpose of distributed generation systems (DGS) is to enhance the distribution system (DS) performance be better known with its benefits in power sector as installing (DG) units into DS can introduce economic, environmental and technical benefits. Those obtained if DG units' site size properly determined. aim this paper studying reviewing effect connecting on transmission efficiency, reacti...

In recent years, several high-performance nature-inspired metaheuristic algorithms have been proposed. It is important to study and compare the convergence, computational burden statistical significance of these metaheuristics aid future developments. This focuses on six metaheuristics, namely, ant lion optimization (ALO), arithmetic algorithm (AOA), dragonfly (DA), grey wolf optimizer (GWO), s...

With the development of Internet and big data, more consumer behavior data are used in different forecasting problems, which greatly improve performance prediction. As main travel tool, sales automobiles will change with variations market external environment. Accurate prediction automobile can not only help dealers adjust their marketing plans dynamically but also economy transportation sector...

Mechanical vibrations have a significant impact on ride comfort; the driver is constantly distracted as result. Volumetric engine inertial unbalances and road profile irregularities create mechanical vibrations. The purpose of this study to employ optimization algorithms identify structural elements that contribute vibration propagation provide optimal solutions for reducing induced by unbalanc...