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 (...

The efficiency of a photovoltaic (PV) system under partial shading conditions (PSCs) is primarily determined by how the PV panels are connected to load. Various architectures have been developed improve power processing capability and thus conversion efficiency. In this article, central string architecture considered, performance characteristics obtained using optimization techniques such as gr...

The optimization of screening parameters will directly improve the performance vibration screens, which has been a concern industry. In this work, discrete element model wet sand and gravel particles is established, process simulated using method (DEM). efficiency time are used as evaluation indices, including amplitude, frequency, direction angle, screen surface inclination, long short half-ax...

The data distribution of the vibration signal under different speed conditions gearbox is different, which leads to reduced accuracy fault diagnosis. In this regard, paper proposes a deep transfer diagnosis algorithm combining adaptive multi-threshold segmentation and subdomain adaptation. First all, in acquisition stage, non-contact, easy-to-arrange, low-cost sound pressure sensor used collect...

In this work, a new metaheuristic algorithm, namely the hybrid pelican Komodo algorithm (HPKA), has been proposed. This is developed by hybridizing two shortcoming algorithms: Pelican Optimization Algorithm (POA) and Mlipir (KMA). Through hybridization, proposed designed to adapt advantages of both POA KMA. Several improvisations regarding are as follows. First, replaces randomized target with ...

Abstract In the field of transformer fault diagnosis, there are many diagnostic methods. These methods either not high accuracy or used too long. this paper, a dimension learning-based hunting (DLH) search strategy optimization grey wolf algorithm support vector machine (DLH-GWO-SVM) model was proposed. process initializing population, logistic chaotic mapping to improve quality initial positio...

Grey Wolf Optimizer (GWO) is a nature-inspired swarm intelligence algorithm that mimics the hunting behavior of grey wolves. GWO, in its basic form, real coded needs modifications to deal with binary optimization problems. In this paper, previous work on binarization GWO are reviewed, and classified respect their encoding scheme, updating strategy, transfer function. Then, we propose novel (nam...