Intelligent control method of robot based on angle of attack feedback for energy efficiency optimization by WANG Tianzhu, LIU Jiayin, HAN Song, CHE Honglei, SHI Congling

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Spatial–degree of freedom improvement of interference alignment in multi-input, multi-output interference channels by Yi-bing Li, Xue-ying Diao, Qian-hui Dong

“…As we know, the degree of freedom approximates the capacity of a network. To improve the achievable degree of freedom in the K -user interference network, we propose a rank minimization interference minimization algorithm. …”
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A novel trajectory learning method for robotic arms based on Gaussian Mixture Model and k-value selection algorithm. by Jingnan Yan, Yue Wu, Kexin Ji, Cheng Cheng, Yili Zheng

“…Next, k-means clustering is applied with the optimal k-value to initialize the parameters of the Gaussian Mixture Model, which are then refined and trained through the Expectation-Maximization algorithm. …”
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Seasonal optimization of solar PV tilt angles for enhanced energy efficiency in Rajasthan, India by Saaransh Choudhary, Shiv Lal, Sumit Verma

“…For this purpose, a general algorithm for the optimization of the solar tilt angle is investigated based on MATLAB software for four different locations in Rajasthan, India. …”
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Vibration Analysis and Optimization of Iron-Core Reactors Based on Fe-Based Soft Magnetic Composite Materials by Yangyang Ma, Wenle Song, Jie Gao, Yang Liu, Yilei Shang, Weimei Zhao, Fuyao Yang

“…The characteristic parameters of the improved model are identified using the particle swarm optimization–simulated annealing (PSO-SA) algorithm, with the identified root mean square error not exceeding 3.5, verifying the model’s accuracy. …”
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Bayesian Optimization-Based State-of-Charge Estimation with Temperature Drift Compensation for Lithium-Ion Batteries by Zhen-Rong Yuan, Ke-Feng Huang, Cai-Hua Xu, Jun-Chao Zou, Jun Yan

“…For this reason, this study proposes an algorithm focusing on Bayesian optimization-based adaptive extended Kalman filter (BO-AEKF) to enhance the numerical accuracy and stability of state-of-charge (SOC) estimation for lithium batteries under various operating conditions. …”
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Hybrid Hunger Games Search optimization using a neural networks approach applied to UAVs by Nadia Samantha Zuñiga-Peña, Salatiel Garcia-Nava, Norberto Hernandez-Romero, Juan Carlos Seck-Touh-Mora

“…Optimization methods like population-based algorithms are valuable when applied to multidimensional and nonlinear problems. …”
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Forecasting the vapor pressure deficit in vertical farming facilities aiming to provide optimal indoor conditions by Carlos Alejandro Perez Garcia, Dafni Despoina Avgoustaki, Enrica Santolini, Daniele Torreggiani, Thomas Bartzanas, Patrizia Tassinari, Marco Bovo

“…The model, demonstrating satisfactory performance in predicting VPD, enables optimization of indoor growth conditions, thereby improving resources use efficiency and minimizing operational costs. …”
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Solving 0-1 Knapsack and Bin Packing Problem Using Logical Social Group Optimization by Rhiddhi Prasad Das, Junali Jasmine Jena, Suresh Chandra Satapathy, Naeem M. S. Hannoon

“…This prominent research gap has been addressed in this paper by introducing Logical Social Group Optimization (LSGO), a logic-based binarized variant of Social Group Optimization (SGO) that leverages Boolean logic for improved efficiency. …”
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Toward Robust GNSS Real-Time Orbit Determination for Microsatellites Using Factor Graph Optimization by Cong Hou, Xiaojun Jin, Xiaopeng Yang, Tong Xiao

“…The simulation results reveal that FGO-RTOD reduces the Root Mean Square (RMS) of positioning error by 79.0% relative to EKF-RTOD and exhibits significantly enhanced smoothing. …”
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UV-Vis spectroscopy coupled with firefly algorithm-enhanced artificial neural networks for the determination of propranolol, rosuvastatin, and valsartan in ternary mixtures by Ahmed Serag, Maram H. Abduljabbar, Yusuf S. Althobaiti, Farooq M. Almutairi, Shaker T. Alsharif, Rami M. Alzhrani, Marwa F. Ahmed, Atiah H. Almalki

“…An experimental design of 25 samples was employed as a calibration set, and a central composite design of 20 samples was used as a validation set. The firefly algorithm (FA) was evaluated as a variable selection procedure to optimize the developed ANN models resulting in simpler models with improved predictive performance as evident by lower relative root mean square error of prediction (RRMSEP) values compared to the full spectrum ANN models. …”
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Does mean arterial pressure augmentation improve neurological recovery of blunt spinal cord injuries: an EAST multicenter trial by Jeffry Nahmias, Ryan Peter Dumas, Brian Daley, Dalier R Mederos, Bradley M Dennis, Michael Steven Farrell, Stephanie Scott, Gregory Schaefer, Asanthi Ratnasekera, Alison Smith, Scott Armen, Joshua Hill, Carlos H Palacio, Caitlin Anne Fitzgerald, Stephanie Doris, Claudia Alvarez, John D Berne, Lindsey Perea, Aimee LaRiccia, James Bardes, Bhairav Shah, Tanisha Kashikar, Erik Teicher, Jennifer Huber, Malia Eischen, H Akin Erol, Lauren Colom, Melissa Moncrief, William DeVoe, William Brigode, Melissa Linskey Dougherty, Emily Alberto, Stephen Gadomski, Salina Wydo, Jennifer Schweinsburg, M Chance Spalding

“…Patients were divided into two groups: neurological improvement and no improvement, based on their change in ASIA score from arrival to hospital discharge.Results A total of 19 centers contributed 222 patients of those, 164 had pre-ASIA and post-ASIA scores. …”
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Enhancing shear strength predictions of UHPC beams through hybrid machine learning approaches by Sanjog Chhetri Sapkota, Ajad Shrestha, Moinul Haq, Satish Paudel, Waiching Tang, Hesam Kamyab, Daniele Rocchio

“…This study proposes hybrid ML models that integrate three nature inspired metaheuristic algorithms—Giant Armadillo Optimization (GOA), Spotted Hyena Optimization (SHO) and Leopard seal optimization (LSA)- Extreme Gradient Boosting (XGB) to predict the shear strength of UHPC beams. …”
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Chaotic billiards optimized hybrid transformer and XGBoost model for robust and sustainable time series forecasting by Reham H. Mohammed, Asmaa Mohamed El-saieed

“…The use of CBO ensures efficient convergence with minimal parameter tuning, making the model suitable for large-scale datasets compared to conventional optimizers, including Adam, Particle Swarm Optimization (PSO) and Genetic Algorithms (GA). …”
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An Intelligent Path Planning System for Urban Airspace Monitoring: From Infrastructure Assessment to Strategic Optimization by Qianyu Liu, Wei Dai, Zichun Yan, Claudio J. Tessone

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A Data Resource Trading Price Prediction Method Based on Improved LightGBM Ensemble Model by Wan Nie, Bingliang Shen, Desheng Li

“…To address the key challenges of limited practical application, high implementation difficulty, and poor generalization capability in existing theoretical models for data resource pricing, this study employs generative adversarial network (GAN) to augment the dataset and constructs a DRV-LightGBM model based on a Bayesian parameter optimization algorithm that maximizes the coefficient of determination (<inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula>) to predict data resource transaction prices and provide post-hoc explanations for the prediction model. …”
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Optimization of air conditioning mechanical ventilation using simulated annealing for enhanced energy efficiency and cost reduction by Enio Pedone Bandarra Filho, Gleyzer Martins, Muhammad Bilal Riaz, Sardar Muhammad Bilal, Oscar Saul Hernandez Mendonza

“…The methodology integrates principles of fluid mechanics with computational modeling to perform mass and pressure balances, combined with a simulated annealing algorithm for system optimization. The results demonstrate notable reductions in energy consumption, installation costs, and root mean square deviation of airflow rates from design targets. …”
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Advancing In Vivo Molecular Bioimaging With Optimal Frequency Offset Selection and Deep Learning Reconstruction for CEST MRI by Adarsha Bhattarai, Chathumi Samaraweera, Mariano Uberti, Aditya N. Bade, Yutong Liu, Dongming Peng

“…Firstly, we use an optimization algorithm to identify a set of optimal sparse frequency offsets for data collection. …”
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Comparative Study on Hyperparameter Tuning for Predicting Concrete Compressive Strength by Jeonghyun Kim, Donwoo Lee

“…This study assesses the impact of hyperparameter optimization algorithms on the performance of machine learning-based concrete compressive strength prediction models. …”
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Study on the parameters of the matrix NTRU cryptosystem by LI Zichen, WU Qinghao, SONG Jiashuo, PENG Haipeng

“…With the rapid development of quantum computers， post-quantum cryptography has emerged as a prominent area of research in cryptography.ObjectivesIn order to avoid the decryption failure in matrix NTRU as NTRU， the Matrix NTRU algorithm was optimized.MethodsBased on the method of constraining the parameter space in congruent cryptographic algorithms， a method for optimal selection of the parameter space of matrix NTRU cryptographic regimes was proposed. …”
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