In dynamic unmanned aerial vehicle (UAV) networks, localization and clustering are fundamental functions for cooperative control. this article, we propose bio-inspired (BIL) (BIC) schemes in UAV networks wildfire detection monitoring. First, develop a hybrid gray wolf optimization (HGWO) method an energy-efficient three-dimensional BIL algorithm based on the HGWO, which reduces errors, avoids f...

This work proposes a new meta-heuristic called Grey Wolf Optimizer (GWO) inspired by grey wolves (Canis lupus). The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Four types of grey wolves such as alpha, beta, delta, and omega are employed for simulating the leadership hierarchy. In addition, the three main steps of hunting, searching for prey, enc...

The computation of image segmentation has become more complicated with the increasing number of thresholds, and the option and application of the thresholds in image thresholding fields have become an NP problem at the same time. The paper puts forward the modified discrete grey wolf optimizer algorithm (MDGWO), which improves on the optimal solution updating mechanism of the search agent by th...

This study investigates a hybrid algorithm between Grey Wolf Optimization (GWO) and Cuckoo Search (CS) algorithms to find the parameters of induction motors. The motor have been estimated by using data supplied manufacturer. problem for parameter estimation is formulated as an optimization problem. Then, solved GWO based on CS parameters. Numerical results show that both are capable solving fin...

Early diagnosis of autism is extremely beneficial for patients. Traditional approaches have been unable to diagnose in a fast and accurate way; rather, there are multiple factors that can be related identifying the disorder. The gene expression (GE) individuals may one these factors, addition personal behavioral characteristics (PBC). Machine learning (ML) based on PBC GE data analytics emphasi...

Metaheuristic optimization algorithms play a crucial role in problems. However, the traditional identification methods have following problems: (1) difficulties nonlinear data processing; (2) high error rates caused by local stagnation; and (3) low classification resulting from premature convergence. This paper proposed variant based on gray wolf algorithm (GWO) with chaotic disturbance, candid...

Hybridization of two or more variants algorithms is the recent trend research field. With help a hybridized algorithm we try to find out better optimal solution and solve various optimization applications. In this paper, new approach Advancement on Grey Wolf Optimization with Fitness Based Self Adaptive Differential Evolution (AGWO-FSADE) proposed. populations are calculated using self adaptive...

Nowadays, many people worldwide suffer from brain disorders, and their health is in danger. So far, numerous methods have been proposed for the diagnosis of Schizophrenia (SZ) attention deficit hyperactivity disorder (ADHD), among which functional magnetic resonance imaging (fMRI) modalities are known as a popular method physicians. This paper presents an SZ ADHD intelligent detection resting-s...

Precise streamflow prediction is crucial in the optimization of distribution water resources. This study develops machine learning models by integrating recurrent gate unit (GRU) with bacterial foraging (BFO), gray wolf optimizer (GWO), and human group (HGO) to forecast Tra Khuc River, Vietnam. For this purpose, time series daily rainfall river flow at Son Giang station from 2000 2020 were empl...

The enhancement of photovoltaic (PV) energy systems relies on an accurate PV model. Researchers have made significant efforts to extract parameters due their nonlinear characteristics the system, and lake information from manufactures’ system datasheet. estimation using optimization algorithms is a challenging problem in which wide range research has been conducted. idea behind this challenge s...