Hybrid multi-objective optimization of µ-synthesis robust controller for frequency regulation in isolated microgrids by Abdallah Mohammed, Ahmed Kadry, Maged Abo-Adma, Adel El Samahy, Rasha Elazab

“…The controller is optimized using multi-objective particle swarm optimization (MOPSO) and multi-objective genetic algorithm (MOGA) under inequality constraints, employing a Pareto front to identify optimal solutions. …”
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Dimensional Evolution of Intelligent Cars Human-Machine Interface considering Take-Over Performance and Drivers’ Perception on Urban Roads by Hao Yang, Yueran Wang, Ruoyu Jia

“…The evolutionary mechanism of dimensions driven by users’ perception was constructed with a genetic algorithm. After debugging the parameters of the model, we verified the rationality of the model and evolved appropriate dimensions. …”
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Analysis of ∼106 Spiral Galaxies from Four Telescopes Shows Large-Scale Patterns of Asymmetry in Galaxy Spin Directions by Lior Shamir

“…The data were annotated automatically by a fully symmetric algorithm, as well as manually through a long labor-intensive process, leading to a dataset of nearly 106 galaxies. …”
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An Automatic Detection Method of Nanocomposite Film Element Based on GLCM and Adaboost M1 by Hai Guo, Jinghua Yin, Jingying Zhao, Yuanyuan Liu, Lei Yao, Xu Xia

“…So it is possible to identify the element of film according to the Adaboost M1 algorithm of a strong classifier with ten decision tree classifiers. …”
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Markov-bridge generation of transition paths and its application to cell-fate choice by Guillaume Le Treut, Sarah Ancheta, Greg Huber, Henri Orland, David Yllanes

“…Trajectories can then be generated using a refined version of the Gillespie algorithm. We illustrate the benefits of our method by sampling trajectories in the Müller-Brown potential. …”
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Prediction Compressive Strength of Concrete Containing GGBFS using Random Forest Model by Hai-Van Thi Mai, Thuy-Anh Nguyen, Hai-Bang Ly, Van Quan Tran

“…The results show that the RF algorithm is an excellent predictor and practically used for engineers to reduce experimental cost.…”
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A Viscous Fluid Flow through a Thin Channel with Mixed Rigid-Elastic Boundary: Variational and Asymptotic Analysis by R. Fares, G. P. Panasenko, R. Stavre

“…For two different cases, we describe the order of steps of the algorithm of solving the problem and we construct the main term of the asymptotic expansion. …”
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Parallel Simulation of HGMS of Weakly Magnetic Nanoparticles in Irrotational Flow of Inviscid Fluid by Kanok Hournkumnuard, Banpot Dolwithayakul, Chantana Chantrapornchai

“…The process of high gradient magnetic separation (HGMS) using a microferromagnetic wire for capturing weakly magnetic nanoparticles in the irrotational flow of inviscid fluid is simulated by using parallel algorithm developed based on openMP. The two-dimensional problem of particle transport under the influences of magnetic force and fluid flow is considered in an annular domain surrounding the wire with inner radius equal to that of the wire and outer radius equal to various multiples of wire radius. …”
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Noise-augmented chaotic Ising machines for combinatorial optimization and sampling by Kyle Lee, Shuvro Chowdhury, Kerem Y. Camsari

“…This improves performance in combinatorial optimization, achieving algorithmic scaling comparable to probabilistic bits (p-bits). …”
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Chaos Enhanced Differential Evolution in the Task of Evolutionary Control of Selected Set of Discrete Chaotic Systems by Roman Senkerik, Ivan Zelinka, Michal Pluhacek, Donald Davendra, Zuzana Oplatková Kominkova

“…The idea was to utilize the hidden chaotic dynamics in pseudorandom sequences given by chaotic map to help differential evolution algorithm search for the best controller settings for the very same chaotic system. …”
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Potential quantum advantage for simulation of fluid dynamics by Xiangyu Li, Xiaolong Yin, Nathan Wiebe, Jaehun Chun, Gregory K. Schenter, Margaret S. Cheung, Johannes Mülmenstädt

“…Based on this, we apply a quantum algorithm for simulating the Carleman-linearized lattice Boltzmann equation and provide evidence that its cost scales logarithmically with system size compared with polynomial scaling in the best known classical algorithms. …”
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Symplectic quantization and general constraint structure of a prototypical second-class system by Ignacio S. Gomez, Vipul Kumar Pandey, Ronaldo Thibes

“…We apply the Dirac–Bergmann algorithm in its full generality unraveling a total of 4m second-class constraints and obtain the corresponding Dirac brackets algebra in phase space. …”
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Intelligent phase imaging guided by physics models by Zhen LIU, Hao ZHU, You ZHOU, Zhan MA, Xun CAO

“…Implicit neural representation characterizes the mapping between the signal’s coordinate to its attributes, and has been widely used in the optimization of inverse problems by embedding the physics process into the loss function.However, the implicit neural representation is suffering the low convergence speed and accuracy from the random initialization of the network parameters.The meta-learning algorithm for providing implicit neural representation with a strong prior of network parameters was proposed, thus enhancing the optimization efficiency and accuracy for solving inverse problems.To address the important issue of lens less phase imaging, an intelligent method on phase imaging was proposed based on the snapshot lens less sensing model.By embedding the optical diffraction propagation theory into the design of loss function for implicit neural representation, the dependency of large-scale labelled dataset in traditional deep learning-based methods was eliminated and accurate phase image from a single diffraction measurement image was provided.Furthermore, the meta-learning model was introduced for initializing network to further improve the efficiency and accuracy of network training.Numerical simulation results show that the proposed method can achieve a PSNR improvement of more than 11 dB compared to the conventional method.The experimental results in real data show that the phase image reconstructed by the proposed method is clearer and has fewer artifacts.…”
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Detection and Prediction of Internal-Caused Fire in Tunnel Cable by an Equivalent Transient Thermal Circuit Model by Yanwen Wang, Xuran Zhang, Le Wang, Yinsheng Wang

“…The maximum relative errors of the transient thermal circuit model and the trisection transient thermal circuit model are less than 10% when comparing the experimental data with the calculation results, and the average relative error of the calculated value of trisection transient thermal circuit model is 1.08% after layered optimization. The algorithm model can satisfy the requirement for early detection and prediction in the very early stage of cable internal-caused fire.…”
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Mathematical modelling and dynamic optimization of phase-locked loop systems using hybrid PSO-gradient descent approach by Mrinal Kanti Rajak, Rajen Pudur

“…The proposed model combines a state-space representation of PLL dynamics with an innovative dual-optimization algorithm integrating Particle Swarm Optimization (PSO) and Gradient Descent (GD). …”
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Modules Identification in Gene Positive Networks of Hepatocellular Carcinoma Using Pearson Agglomerative Method and Pearson Cohesion Coupling Modularity by Jinyu Hu, Zhiwei Gao

“…A Pearson agglomerative clustering algorithm is employed to build a clustering tree, where dotted lines cut the tree from bottom to top leading to a number of subsets of the modules. …”
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Optimal Design and Acoustic Assessment of Low-Vibration Rotor Blades by G. Bernardini, E. Piccione, A. Anobile, J. Serafini, M. Gennaretti

“…Blade shape and structural properties are the design parameters to be identified within a binary genetic optimization algorithm under aeroelastic stability constraint. The process exploits an aeroelastic solver that is based on a nonlinear, beam-like model, suited for the analysis of arbitrary curved-elastic-axis blades, with the introduction of a surrogate wake inflow model for the analysis of sectional aerodynamic loads. …”
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Headway Optimisation for Metro Lines Based on Timetable Simulation and Simulated Annealing by Yong Cui, Qing Yu, Chenyang Wang

“…Several different optimisation algorithms, including grid search, Monte Carlo, and simulated annealing, are developed and compared. …”
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Addressing Technical Challenges in Large Language Model-Driven Educational Software System by Nacha Chondamrongkul, Georgi Hristov, Punnarumol Temdee

“…This paper tackles these challenges by proposing tactics to improve system integration, enhance explainability through metadata and an algorithm process, ensure response consistency via regression testing, and facilitate efficient autoscaling through an event-driven microservice architecture. …”
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Simulated Annealing Technique for Routing in a Rectangular Mesh Network by Noraziah Adzhar, Shaharuddin Salleh

“…While classical Dijkstra’s algorithm guarantees to find shortest path for a single net, each routed net will form obstacles for later paths. …”
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