Exploring the Impact of Local Operator Configurations in the Multi-Demand Multidimensional Knapsack Problem by José García, Ivo Cattarinich, Paola Moraga, Hernan Pinto

“…In this work, we investigate four local operator configurations—Add, Drop, Swap, and All Operator—within the Whale Optimization Algorithm framework. Our approach integrates these operators to broaden search coverage and refine candidate solutions. …”
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Experimental acoustic study of small horizontal axis wind turbines based on computational fluid dynamics and artificial intelligence approaches by M. Sadeghi malekabadi, A.R. Davari

“…In modern wind turbine design, two significant challenges arise: achieving optimal aerodynamic performance while minimizing acoustic noise emissions. …”
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A Detection and Cover Integrated Waveform Design Method with Good Correlation Characteristics and Doppler Tolerance by Haoting Guo, Fulai Wang, Nanjun Li, Zezhou Wu, Chen Pang, Lei Zhang, Yongzhen Li

“…The gradient descent algorithm is used to solve the model, and the optimized waveform with low sidelobe characteristics and multiple false target interference abilities is obtained. …”
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云南6种木本植物油脂肪酸组成分析及调和优化"Fatty acid composition analysis and blending optimization of six woody plant oils in Yunnan province" by 于雪莲1，2，杨培艺3，郭娟1，罗嘉1，张帆3YU Xuelian1，2，YANG Peiyi3，GUO Juan1，LUO Jia1，ZHANG Fan3

“…Based on the dietary fatty acid recommendation, the blending products of six woody plant oils were optimized by programming algorithm with the content of functional fatty acids as the index. …”
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Data driven models for predicting pH of CO2 in aqueous solutions: Implications for CO2 sequestration by Mohammad Rasool Dehghani, Moein Kafi, Hamed Nikravesh, Maryam Aghel, Erfan Mohammadian, Yousef Kazemzadeh, Reza Azin

“…To fill this research gap, this study developed 15 models comprising five machine learning methods: regression trees, support vector regression, Gaussian process regression, bagged trees, and boosted trees, and three optimization algorithms: random search, grid search, and Bayesian optimization. …”
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Comparative Analysis of Supervised Learning Techniques for Forecasting PV Current in South Africa by Ely Ondo Ekogha, Pius A. Owolawi

“…This work presents a comparative examination of supervised learning algorithms optimized with particle swarm optimization for estimating photovoltaic output current. …”
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Bio-Inspired Traffic Pattern Generation for Multi-AMR Systems by Rok Vrabič, Andreja Malus, Jure Dvoršak, Gregor Klančar, Tena Žužek

“…This paper proposes a bio-inspired optimization method for autonomously generating spatial movement constraints for autonomous mobile robots (AMRs). …”
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FPGA-Accelerated Sparse Subset Segmentation Using ADMM for High-Resolution Imagery by Rupali Karthikeyan, Deep Amit Lodaya, Rama Muni Reddy Yanamala, Rayappa David Amar Raj, K. Krishna Prakasha, T. Subeesh, V. Anandkumar, Archana Pallakonda

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Supervised Machine Learning Models for Predicting SS304H Welding Properties Using TIG, Autogenous TIG, and A-TIG by Subhodwip Saha, Barun Haldar, Hillol Joardar, Santanu Das, Subrata Mondal, Srinivas Tadepalli

“…A total of 80% of the collected dataset was used for training the models, while the remaining 20% was reserved for testing their performance. …”
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Highly Versatile FPGA-Implemented Cyber Coherent Ising Machine by Toru Aonishi, Tatsuya Nagasawa, Toshiyuki Koizumi, Mastiyage Don Sudeera Hasaranga Gunathilaka, Kazushi Mimura, Masato Okada, Satoshi Kako, Yoshihisa Yamamoto

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Robust and Unified Semi-Supervised Unmixing of Hyperspectral Imaging for Linear and Multilinear Models by Daniel Ulises Campos-Delgado, Juan Nicolas Mendoza-Chavarria, Omar Gutierrez-Navarro, Laura Quintana-Quintana, Raquel Leon, Samuel Ortega, Himar Fabelo, Carlos Lopez, Marylene Lejeune, Gustavo M. Callico

“…All scripts for the proposed algorithms are freely available in <uri>https://github.com/Nicothe4th/ESSEAE-NESSEAE</uri>.…”
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Response mitigations of adjacent structure with MPTMD under real and stochastic excitations by Mohammad Alibabaei Shahraki

“…The performance of the MPTMD system is optimized using the Particle Swarm Optimization (PSO) algorithm. …”
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A Deformation Prediction Model for Concrete Dams Based on RSA-VMD-AttLSTM by Pei Liu, Hao Gu, Chongshi Gu, Yanbo Wang

“…This model utilizes the RSA to optimize the parameters K and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>α</mi></semantics></math></inline-formula> of the VMD algorithm. …”
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Construction cost prediction model for agricultural water conservancy engineering based on BIM and neural network by Kun Han, Tieliang Wang, Wenhe Liu, Chunsheng Li, Xiaochen Xian, Yingying Yang

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User scheduling and power allocation strategy for cell-free networks based on federated learning by WANG Huahua, HUANG Yexia, LI Ling

“…Simulation results demonstrate that compared to other comparison algorithms, the proposed algorithm achieves a 47.19% increase in downlink throughput, a 22.60% increase in uplink throughput, and a 57.33% reduction in FL task time consumption, while minimizing time overhead for achieving the same model accuracy…”
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Neural Architecture Search for Generative Adversarial Networks: A Comprehensive Review and Critical Analysis by Abrar Alotaibi, Moataz Ahmed

“…Neural Architecture Search (NAS) has emerged as a pivotal technique in optimizing the design of Generative Adversarial Networks (GANs), automating the search for effective architectures while addressing the challenges inherent in manual design. …”
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Improving quantum metrology protocols with programmable photonic circuits by de las Heras Alberto Muñoz, Porras Diego, González-Tudela Alejandro

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Simulation of Patch Field Effect in Space-Borne Gravitational Wave Detection Missions by Mingchao She, Xiaodong Peng, Li-E Qiang

“…These results establish a foundation for optimizing mitigation strategies against patch-induced noise in future space missions.…”
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Coordinated Truck Loading and Routing Problem: A Forestry Logistics Case Study by Cristian Oliva, Manuel Cepeda, Sebastián Muñoz-Herrera

“…The results show that an Ant Colony System (ACS–CTLRP) algorithm reduces total distance traveled by 23%, travel time by 22%, and the number of trucks used by 13 units, while increasing fleet utilization from 54% to 83%. …”
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State-of-the-Art Fault Detection and Diagnosis in Power Transformers: A Review of Machine Learning and Hybrid Methods by Lebo Dina Mashifane, Bongumsa Mendu, Bessie Baakanyang Monchusi

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