Results 91 to 100 of about 81,531 (237)

Learning enhancement of radial basis function network with particle swarm optimization [PDF]

, 2008
Back propagation (BP) algorithm is the most common technique in Artificial Neural Network (ANN) learning, and this includes Radial Basis Function Network.
Sultan Noman, Qasem Mohammed
core  

A Rapid Post‐Disaster Restoration Method for Networked Microgrids Based on Adaptive Quantum Particle Swarm Optimization

Energy Science &Engineering, EarlyView.
To enhance the power restoration speed of networked microgrids (NMGs) after extreme natural disasters and reduce the power outage of the system, this paper proposes a rapid post‐disaster restoration method for NMGs based co‐optimization of fault repair and load restoration.
Yunfan Zhang, Qiang Li, Jun Zhang, Chaohuang Xu   +3 more
wiley   +1 more source

Optimasi Training Neural Network Menggunakan Hybrid Adaptive Mutation PSO-BP

Jurnal EECCIS (Electrics, Electronics, Communications, Controls, Informatics, Systems), 2015
Optimization of training neural network using particle swarm optimization (PSO) and genetic algorithm (GA) is a solution backpropagation’s problem. PSO often trapped in premature convergent (convergent at local optimum) and GA takes a long time to ...
Salnan Ratih Asriningtias, Harry Soekotjo Dachlan, Erni Yudaningtyas   +2 more
doaj   +1 more source

Tumor‐educated platelets in cancer diagnostics and prognostics: A critical appraisal and roadmap for clinical translation

International Journal of Cancer, EarlyView.
Abstract Tumor‐educated platelets (TEPs) are emerging as a compelling frontier in liquid biopsy, functioning as dynamic, systemic sensors that sequester and process tumor‐derived biomolecules. This interaction imprints an integrated molecular signature of malignancy—spanning the transcriptome, proteome, lipidome, and crucially, the captured genome ...
Whi‐An Kwon, Min‐Kyung Lee, Eunyong Ahn, Heeyeon Kim, Yong Sang Song, Taejin Ahn   +5 more
wiley   +1 more source

Solving two-dimensional packing problem using particle swarm optimization

Computer Assisted Methods in Engineering and Science, 2017
Particle swarm optimization is one of the evolutionary computations which is inspired by social behavior of bird flocking or fish schooling. This research focuses on the application of the particle swarm optimization to two-dimensional packing problem ...
Young-Bin Shin, Eisuke Kita
doaj   +1 more source

Rheological Characterization and Multi‐Regime Viscosity Modeling of Diluted Polyethylene Mixtures

Polymer Engineering &Science, EarlyView.
This study maps the flow behavior of low‐density polyethylene in a recycling solvent from dilute solutions to entangled melts. By integrating time–concentration and time–temperature superposition, and coupling three complementary rheometry methods, a unified semiempirical model accurately predicts steady‐shear viscosity over nine decades of viscosity ...
Johannes Krug, Ernst Georg Viehböck, Alexander Hammer, Ursula Steiner, Christof Murnig, Martin Reichel, Christian Paulik, Gerald Berger‐Weber   +7 more
wiley   +1 more source

A Novel Crow Swarm Optimization Algorithm (CSO) Coupling Particle Swarm Optimization (PSO) and Crow Search Algorithm (CSA). [PDF]

Comput Intell Neurosci, 2021
Jia YH, Qiu J, Ma ZZ, Li FF.
europepmc   +1 more source

Kajian terhadap ketahanan hentaman ke atas konkrit berbusa yang diperkuat dengan serat kelapa sawit [PDF]

, 2013
Konkrit berbusa merupakan sejenis konkrit ringan yang mempunyai kebolehkerjaan yang baik dan tidak memerlukan pengetaran untuk proses pemadatan. Umum mengenali konkrit berbusa sebagai bahan binaan yang mempunyai sifat kekuatan yang rendah dan lemah
Hassan, Hashimah Kho
core  

Physics‐Informed Neural Networks for Battery Degradation Prediction Under Random Walk Operations

Quality and Reliability Engineering International, EarlyView.
ABSTRACT This study addresses the challenge of predicting the state of health (SoH) and capacity degradation in Battery Energy Storage Systems (BESS) under highly variable conditions induced by frequent control adjustments. In environments where random walk behavior prevails due to stochastic control commands, conventional estimation methods often ...
Alaa Selim, Huadong Mo, Hemanshu Pota, Daoyi Dong   +3 more
wiley   +1 more source

Memes Evolution in a Memetic Variant of Particle Swarm Optimization

Mathematics, 2019
In this work, a coevolving memetic particle swarm optimization (CoMPSO) algorithm is presented. CoMPSO introduces the memetic evolution of local search operators in particle swarm optimization (PSO) continuous/discrete hybrid search spaces.
Umberto Bartoccini, Arturo Carpi, Valentina Poggioni, Valentino Santucci   +3 more
doaj   +1 more source