Optimization of Sparse Concentric Ring Arrays for Low Sidelobe by Kesong Chen, Yafei Li, Jiajia Shi

“…The MGA uses real number to code the optimization variable, and it reduces the complexity of coding and improves the search efficiency. …”
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Research and Design of an Active Light Source System for UAVs Based on Light Intensity Matching Model by Rui Ming, Tao Wu, Zhiyan Zhou, Haibo Luo, Shahbaz Gul Hassan

“…Extensive qualitative and quantitative experiments confirm that the UAV active light source system based on light intensity matching proposed in this paper effectively enhances the effectiveness and robustness of vision-based tracking for multi-UAVs, particularly in complex and variable environments. This research provides an efficient and computationally effective solution for vision-based multi-UAV systems, further enhancing the visual tracking capabilities of multi-UAVs under complex conditions.…”
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Unsupervised selective labeling for semi-supervised industrial defect detection by Jian Ge, Qin Qin, Shaojing Song, Jinhua Jiang, Zhiwei Shen

“…This has motivated a shift towards semi-supervised learning (SSL), which leverages labeled and unlabeled data to improve learning efficiency and reduce annotation costs. This work proposes the unsupervised spectral clustering labeling (USCL) method to optimize SSL for industrial challenges like defect variability, rarity, and complex distributions. …”
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Cognitive ability and motor performances in the elderly by Jovanović Stevan S., Stojanović-Jovanović Biljana N., Pavlović Aleksandra M., Milošević Radovan Lj., Pavlović Dragan M.

“…Executive functions and language correlated most significantly with physical strength. …”
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Pilot study evaluating lipoma reduction with injected physiologic ice slurry by Kristen K. Arango, Cheryl A. London, William M. Karlin, Jacqueline Milton Hicks

“…Future studies could explore using coolants with more sustained coolant function and multiple injections to promote more efficient tumor reduction.…”
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Implementation of Fuzzy Logic Scheme for Assessment of Power Transformer Oil Deterioration Using Imprecise Information by Zuhaib Nishter, Fangzong Wang

“…This research aims to analyze the implementation of a fuzzy logic-based approach in improving the diagnosis of power transformer oil deterioration, which is critical for maintaining the efficient performance and operational life of transformers. …”
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…Timely identification is crucial for efficient intervention, as untreated diabetic retinopathy can progress to irreversible vision loss. …”
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Reconstruction of reservoir rock using attention-based convolutional recurrent neural network by Indrajeet Kumar, Anugrah Singh

“…This deep learning method is computationally efficient, fast, and reliable for synthetic image realizations. …”
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Deep Multi-Component Neural Network Architecture by Chafik Boulealam, Hajar Filali, Jamal Riffi, Adnane Mohamed Mahraz, Hamid Tairi

“…The architecture’s efficiency is further demonstrated by its reduced trainable parameters and robust handling of multimodal and variable-length inputs, making it a versatile solution for classification tasks.…”
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APPLICATION OF HYBRID RANDOM SEARCH METHOD TO OPTIMISATION OF ENGINEERING SYSTEMS’ PARAMETERS by A. V. Panteleev, D. A. Rodionova

“…These problems belong to the class of constrained global optimization problems, where the level surface of the objective function has uneven relief and there is a large number of variables. …”
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Color image hybrid noise filtering algorithm based on deep convolution neural network by Yongfei Yu, Yuanjian Yan

“…Then, the probability density function and noise probability density function of Gaussian noise are calculated to determine the hybrid noise feature points of color image. …”
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A DQN-Based Algorithm for Operational Optimization of Freight Trains in Long Steep Downhill Sections by HE Zhiyu, LI Yinan, LI Hui, JI Zhijun

“…The study employed the batch collection of training samples utilizing experience replay and a double-network mechanism, along with the preprocessing of neural network state inputs, and the investigation into feasible regions within the action space using a variable ε-greedy strategy. A loss function based on the value function was then constructed, and network parameters were updated iteratively by a batch gradient descent method. …”
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Numerical solutions for fractional optimal control problems using Mü‎‎‎‎‎‎‎ntz-Legendre polynomials by Mohammad Sahabi, Allahbakhsh Yazdani Cherati

“…To achieve this, stable and efficient methods for calculating the fractional integral and derivative operators of Müntz-Legendre functions based on three-term recurrence formulas and Jacobi-Gauss quadrature rules are presented. …”
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A non-dominated sorting based multi-objective neural network algorithm of ethylene glycol hydrogenation reactor in energy reduction by Fakhrony Sholahudin Rohman, Sharifah Rafidah Wan Alwi, Dinie Muhammad, Muhamad Nazri Murat, Ashraf Azmi

“…Artificial intelligence (AI) can be applied to various ethylene glycol (EG) production aspects to improve efficiency, quality, and overall process optimization. …”
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Modeling Spatial Data with Heteroscedasticity Using PLVCSAR Model: A Bayesian Quantile Regression Approach by Rongshang Chen, Zhiyong Chen

“…Through an approximation of the nonparametric functions with free-knot splines, we develop a Bayesian sampling approach that can be applied by the Markov chain Monte Carlo (MCMC) approach and design an efficient Metropolis–Hastings within the Gibbs sampling algorithm to explore the joint posterior distributions. …”
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Weather Phenomena Monitoring: Optimizing Solar Irradiance Forecasting With Temporal Fusion Transformer by Xinyang Hu

“…The proposed model decomposes the raw solar irradiance sequence into intrinsic mode functions using VMD and optimizes the TFT using the variable screening network and GRU-based encoder-decoder. …”
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Optimizing Constrained Engineering Optimization Problems Using Improved Mountain Gazelle Optimizer by Vu Hong Son Pham, Nghiep Trinh Nguyen Dang, Van Nam Nguyen

“…This study introduces a novel approach to engineering design optimization through the development of an improved mountain gazelle optimizer (iMGO) that incorporates variable neighborhood search (VNS) techniques. The enhanced algorithm effectively addresses engineering optimization challenges by identifying optimal design solutions within specified constraints. …”
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Effect of a mix of condense and hydrolysable tannins feed additive on lactating dairy cows’ services per conception and days open by Alejandro R Castillo, Julio A Di Rienzo, Damiano Cavallini

“…Services per conception was modeled as a Poisson count using a generalized linear model with log link function. Days open was modeled with a generalized linear model for a gamma variable with log link function. …”
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VHR Multispectral Satellite Image Classification with Kolmogorov-Arnold Networks for Urban Applications by M. Fawzy, M. Fawzy, Á. Barsi

“…The Kolmogorov-Arnold Network (KAN) is a computational framework rooted in the Kolmogorov-Arnold representation theorem, which states that any continuous function of multiple variables can be expressed as a superposition of univariate functions. …”
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Proportional Topology Optimization algorithm with virtual elements for multi-material problems considering mass and cost constraints by Minh Tuan Tran, Minh Ngoc Nguyen

“…., the derivative of the objective function with respect to design variables. Instead, the amount of material distributed into each element is determined proportionally to the contribution of that element to the objective function. …”
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