Results 31 to 40 of about 529 (161)

Improvement of the Seagull Optimization Algorithm and Its Application in Path Planning

Journal of Physics: Conference Series, 2022
Abstract Seagull Optimization Algorithm (SOA) is an emerging intelligent optimization algorithm proposed in recent years. This paper proposes an improvement in the SOA based on Levy flight(LSOA), which aims to solve the problems of decreasing exploration ability and easing to fall into local extreme values in the late stage of SOA.
Jing Chen, Xin Chen, Zaifei Fu
openaire   +1 more source

A Novel Hybrid Classification Method Based on the Opposition-Based Seagull Optimization Algorithm [PDF]

IEEE Access, 2020
In practice, classification problems have appeared in many scientific fields, including finance, medicine and industry. It is critically important to develop an effective and accurate classification model. Although numerous useful classifiers have been proposed, they are unstable, sensitive to noise and slow in computation. To overcome these drawbacks,
He Jiang 0003, Ye Yang, Weiying Ping, Yao Dong 0002   +3 more
openaire   +2 more sources

Optimal Parameter Estimation Methodology of Solid Oxide Fuel Cell Using Modern Optimization

Mathematics, 2021
An optimal parameter estimation methodology of solid oxide fuel cell (SOFC) using modern optimization is proposed in this paper. An equilibrium optimizer (EO) has been used to identify the unidentified parameters of the SOFC equivalent circuit with the ...
Hesham Alhumade, Ahmed Fathy, Abdulrahim Al-Zahrani, Muhyaddin Jamal Rawa, Hegazy Rezk   +4 more
doaj   +1 more source

Linear Antenna Array Synthesis by Modified Seagull Optimization Algorithm

The Applied Computational Electromagnetics Society Journal (ACES), 2022
This paper presents a study of linear antenna array (LAA) synthesis with a seagull optimization algorithm (SOA) to achieve radiation patterns having low maximum sidelobe levels (MSLs) with and without nulls. The SOA is a new optimization technique based on the moving and attacking behaviors of the seagull in the nature.
Erhan Kurt, Suad Basbug, Kerim Guney
openaire   +2 more sources

A Comparative Study of Six Hybrid Prediction Models for Uniaxial Compressive Strength of Rock Based on Swarm Intelligence Optimization Algorithms

Frontiers in Earth Science, 2022
Uniaxial compressive strength (UCS) is a significant parameter in mining engineering and rock engineering. The laboratory rock test is time-consuming and economically costly.
Yu Lei, Shengtao Zhou, Xuedong Luo, Shuaishuai Niu, Nan Jiang   +4 more
doaj   +1 more source

Power generation cost minimization of the grid-connected hybrid renewable energy system through optimal sizing using the modified seagull optimization technique

Energy Reports, 2020
A hybrid renewable power system is studied in this paper. This system is composed of PV panels, wind turbines, inverter, rectifier, electrolyzer, and fuel cell such that it prioritizes storing excess energy by converting it to hydrogen and using it later
Gang Lei, Heqing Song, Dragan Rodriguez
doaj   +1 more source

Multilevel Threshold Segmentation of Skin Lesions in Color Images Using Coronavirus Optimization Algorithm

Diagnostics, 2023
Skin Cancer (SC) is among the most hazardous due to its high mortality rate. Therefore, early detection of this disease would be very helpful in the treatment process.
Yousef S. Alsahafi, Doaa S. Elshora, Ehab R. Mohamed, Khalid M. Hosny   +3 more
doaj   +1 more source

Research on the purification mechanism of heavy metal pollution by biochar composites driven by degree learning [PDF]

E3S Web of Conferences
This paper proposes an innovative approach by integrating deep learning technology, specifically employing the GRU recurrent neural network model based on the Seagull optimization algorithm, to enhance the accuracy of predicting biochar performance.
Dai Anran, Jia Luxia, Zhan Aoli, Zhang Xiuze   +3 more
doaj   +1 more source

Analysis and Classification of Partial Shading Conditions in Photovoltaic Arrays

Energy Science &Engineering, EarlyView.
This study presents new mathematical models for describing P–V curve extrema under different shading scenarios and applies machine learning classifiers that use features derived from P–V characteristics for accurate fault identification. ABSTRACT With the escalating global transition toward renewable energy, ensuring the operational stability and ...
Hamid Reza Parsa, Mohammad Sarvi
wiley   +1 more source

Edge‐Channel Aggregation Network and Two‐Stage Fine Tuning Scheme for Handwritten Dongba Character Recognition

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Handwritten Dongba Character Recognition (HDCR) contains a large number of visually similar characters with subtle and fragile edge cues, posing severe challenges to feature learning. To address this issue, an Edge Channel Aggregation Network (EdgeCANet) model is proposed.
Xiali Li, Yang Xiao, Xiaojun Bi, Yanlong Luo   +3 more
wiley   +1 more source