This paper presents a new two-stage multi-swarm particle swarm optimizer (TMPSO), which employs the multi-swarm method and takes two-stage different search strategies in the whole iteration process.This new optimizer includes two versions: unconstrained TMPSO (uTMPSO) and constrained TMPSO (cTMPSO) for unconstrained and constrained global optimizat
In this work, we study the Chafee-Infante model with conformable fractional derivative.This model describes the energy balance between equator and pole of solar system, which transmit energy via heat diffusion.To explore the multi soliton solutions and their interaction, we implemented the new modified simple equation (NMSE) scheme.Under some condi
Combining remote-sensing data with in-situ Collections observations to achieve a comprehensive 3D reconstruction of the ocean state presents significant challenges for traditional interpolation techniques.To address this, we developed the CLuster Optimal Interpolation Neural Network (CLOINet), which combines the robust mathematical framework of the
The aim of this study was to validate the quantification of internal training load (session rating perceived exertion, sRPE) and the effect of recall timing of sRPE during high-intensity functional training (HIFT) sessions.Thirteen male HIFT practitioners (age Collections 27.2 ± 33 years, height 177.1 ± 4.0 cm, body mass 81.1 ±
Position data from real-time indoor positioning systems are increasingly used for studying individual cow behavior and social behavior in dairy herds.However, missing data challenges achieving reliable continuous activity monitoring and behavior studies.This study investigates the pattern of missing data and alternative interpolation methods in ult