Actually, path planning is one of the most crucial aspects mobile robots study. The primary goal this research to develop a solution issues that occur when “mobile robot” operates in static environment. problem handled by finding collision-free meets given criteria for shortest distance with quite smoothness path. Two nature-inspired metaheuristic algorithms are used computation. By leading hyb...

The Grey Wolf Optimizer (GWO) has emerged as one of the most captivating swarm intelligence methods, drawing inspiration from hunting behavior wolf packs. GWO’s appeal lies in its remarkable characteristics: it is parameter-free, derivative-free, conceptually simple, user-friendly, adaptable, flexible, and robust. Its efficacy been demonstrated across a wide range optimization problems diverse ...

Wireless sensor networks (WSN) have been recently gaining traction for many applications in monitoring and surveillance systems the physical world specifically agriculture, healthcare, smart cities. Many clustering routing approaches introduced to reduce consumption of energy WSNs increase lifetime network. In this study, we propose an improved version grey wolf optimizer (GWO), a nature-inspir...

The operation of PV systems can experience uniform (UIC) and partial insolation (PSC) that depends on its environment. Many MPPT algorithm has been proposed in literature such as P&O, many metaheuristics PSO GWO. Those only work at a certain environmental condition. P&O UIC but fail to track maximum power PSC hence reducing efficiency system when it is experiencing PSC. GWO the change s...

The data classification method based on support vector machine (SVM) has been widely used in various studies as a non-linear, high precision, and good generalization ability learning method. Among them, the kernel function its parameters have great impact accuracy. In order to find optimal improve accuracy of SVM, this paper proposes multi-classification gray wolf algorithm optimized SVM(GWO-SV...

Accurate photovoltaic (PV) power prediction plays an increasingly crucial role to maintain the safety and reliability of grid operation. However, fluctuation non-stationarity PV make it a challenging task optimize accurate results. This paper presents novel model which is combination Hodrick–Prescott (HP) filter, optimized variational mode decomposition (OVMD), enhanced emotional neural network...

The Controlled Source Audio-frequency Magnetotellurics (CSAMT) is a geophysical method utilizing artificial electromagnetic signal source to estimate subsurface resistivity structures. One-dimensional (1D) inversion modelling of CSAMT data non-linear and the solution can be estimated by using global optimization algorithms. Particle Swarm Optimization (PSO) Grey Wolf Optimizer (GWO) are well-kn...

Evolutionary Population Dynamics (EPD) refers to eliminating poor individuals in nature, which is the opposite of survival fittest. Although this method can improve median whole population meta-heuristic algorithms, it suffers from exploration capability handle high-dimensional problems. This paper proposes a novel EPD operator search process. In other words, as primary mainly improves fitness ...

It is extremely critical for an emergency response to quickly and accurately use source term estimation (STE) in the event of hazardous gas leakage. To determine appropriate algorithm, four swarm intelligence optimization (SIO) algorithms including Gray Wolf optimizer (GWO), particle (PSO), genetic algorithm (GA) ant colony (ACO) are selected be applied STE. After calculation, all can obtain le...

Abstract This paper describes the novel scientific contribution of a modified hybrid grey wolf optimization‐fuzzy logic controller (GWO‐FLC) based on maximum power point tracking (MPPT) for photovoltaic (PV) system. The GWO eliminates lower rank ( δ ) and lowest Ψ wolves, which provides rapid search method to track global (GMPP) in lesser period. GWO‐FLC MPPT technique GMPP with zero oscillatio...