Simulation-Based Design and Machine Learning Optimization of a Novel Liquid Cooling System for Radio Frequency Coils in Magnetic Hyperthermia by Serhat Ilgaz Yöner, Alpay Özcan

“…Sensitivity analysis and the ReliefF algorithm were applied for a thorough analysis. Simulation results indicate that the proposed novel liquid cooling system demonstrates higher performance compared to conventional systems that utilize direct liquid cooling, offering a computationally efficient method for pre-manufacturing design optimization of radio frequency coil cooling systems in magnetic hyperthermia applications.…”
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Early Parkinson’s disease identification via hybrid feature selection from multi-feature subsets and optimized CatBoost with SMOTE by Subhashree Mohapatra, Bhanja Kishor Swain, Manohar Mishra

“…The proposed framework leverages a strong categorical boosting (CatBoost) algorithm optimized using Grid Search Optimization (GSO). …”
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Comparing the potential of tree-based and area-based forest height metrics for aboveground biomass estimation in complex forest landscapes by Weiyan Liu, Yuling Chen, Haitao Yang, Guangcai Xu, Shiyu Yan, Lingjun Li, Ling Chen, Qinghua Guo

“…This study explores the comparative performance of tree-based and area-based forest height metrics in AGB estimation using 755 field plots across Beijing, incorporating field-measured tree diameter at breast height and LiDAR-derived tree heights. Two modeling approaches—parametric mixed-effects models (MEM) and non-parametric machine learning (ML) algorithms—were applied to evaluate predictive accuracy. …”
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Embedded Rough-Neck Helmholtz Resonator Low-Frequency Acoustic Attenuator by Xianming Sun, Tao Yu, Lipeng Wang, Yunshu Lu, Changzheng Chen

“…Moreover, by coupling the BP network with the Golden Jackal Optimization (GJO) algorithm, a BP-GJO optimization model is developed to refine the structural parameters. …”
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Domain Knowledge-Enhanced Process Mining for Anomaly Detection in Commercial Bank Business Processes by Yanying Li, Zaiwen Ni, Binqing Xiao

“…Additionally, we employed large language models (LLMs) for root cause analysis and process optimization recommendations. …”
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An Optimization Framework for Waste Treatment Center Site Selection Considering Nighttime Light Remote Sensing Data and Waste Production Fluctuations by Junbao Xia, Yanping Liu, Haozhong Yang, Guodong Zhu

“…Distinct from prior studies, this study suggests that service point waste quantities are not fixed values but rather adhere to a normal distribution within specified ranges and thus provides a more realistic simulation of fluctuations in waste production while enhancing both the robustness and predictive accuracy of the model. In conclusion, by incorporating nighttime light remote sensing data along with advanced machine learning techniques, this study markedly improves forecasting accuracy for waste production while offering effective optimization strategies for site selection and recovery route planning—thereby establishing a robust data foundation aimed at refining urban solid waste management systems.…”
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Distributionally robust optimization-based scheduling for a hydrogen-coupled integrated energy system considering carbon trading and demand response by Zhichun Yang, Lin Cheng, Huaidong Min, Yang Lei, Yanfeng Yang

“…The column-and-constraint generation (C&CG) algorithm efficiently solves the two-stage DRO model. …”
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Unveiling optimal SDG pathways: an innovative automated recommendation approach integrating graph pruning, intent graph, and attention mechanism by Qiang Wang, Zhihang Yu, Shu Wang, Yunqiang Zhu, Xiaoliang Dai, Zhiqiang Zou, Weiming Huang, Christophe Claramunt

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Six Sigma-Based Mathematical Optimization Framework for Flux-Switching Machines: A Roadmap for Quality, Performance, and Manufacturing Tolerances by Chiweta E. Abunike, Ogbonnaya I. Okoro, Sumeet S. Aphale

“…This study presents a Design for Six Sigma (DFSS) optimization framework that integrates sensitivity analysis, response surface modeling (RSM), and multi-objective genetic algorithms to address these challenges. …”
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Biomimetic Computing for Efficient Spoken Language Identification by Gaurav Kumar, Saurabh Bhardwaj

“…Further, the selection of features is performed by DBO algorithm, which removes redundant features and helps to improve efficiency and accuracy. …”
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Risk management system and intelligent decision-making for prefabricated building project under deep learning modified teaching-learning-based optimization. by Huazan Liu, Yukang He, Qichao Hu, Jianfei Guo, Lan Luo

“…This study establishes a model of prefabricated building project risk management system based on the Modified Teaching-Learning-Based-Optimization (MTLBO) algorithm and a prediction model of deep learning multilayer feedforward neural network (Backpropagation, BP neural network) to improve the requirements of risk management during the construction of large prefabricated building projects. …”
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Fine-Tuned Machine Learning Classifiers for Diagnosing Parkinson’s Disease Using Vocal Characteristics: A Comparative Analysis by Mehmet Meral, Ferdi Ozbilgin, Fatih Durmus

“…Six different machine learning classifiers, namely SVM, k-NN, DT, NN, Ensemble and Stacking models, were developed and optimized via Bayesian Optimization (BO), Grid Search (GS) and Random Search (RS). …”
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A multitasking ant system for multi-depot pick-up and delivery location routing problem with time window by Haoyuan Lv, Ruochen Liu, Jianxia Li

“…Furthermore, ignoring the potential general knowledge among different schemes leads to redundant optimization. In this work, MDPDLRPTW is modeled as a multi-transformation optimization (MTFO) problem and a novel two-stage algorithm based on multitasking ant system (MTAS) is designed to solve it. …”
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Yield prediction, pest and disease diagnosis, soil fertility mapping, precision irrigation scheduling, and food quality assessment using machine learning and deep learning algorith... by S. Ajith, S. Vijayakumar, N. Elakkiya

“…Furthermore, advancements in transfer learning and data augmentation have improved artificial intelligence adoption in regions with limited datasets. …”
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IT diagnostics of Parkinson's disease based on voice markers and decreased motor activity by U. V. Vishniakou, X. Yiwei

“…A Bayesian optimizer was also used to improve the hyperparameters of the KNN algorithm. …”
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Application of Feedforward Artificial Neural Networks to Predict the Hydraulic State of a Water Distribution Network by Leandro Evangelista, Débora Móller, Bruno Brentan, Gustavo Meirelles

“…Usually, a hydraulic model is used jointly with optimization methods, which require considerable computational effort, hindering real-time interventions. …”
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Machine Learning with Evolutionary Parameter Tuning for Singing Registers Classification by Tales Boratto, Gabriel de Oliveira Costa, Alexsandro Meireles, Anna Klara Sá Teles Rocha Alves, Camila M. Saporetti, Matteo Bodini, Alexandre Cury, Leonardo Goliatt

“…Thus, the present article proposes a novel approach that leverages the Differential Evolution (DE) algorithm to optimize hyperparameters within three selected ML models, with the aim of classifying singing-voice registers i.e., chest, mixed, and head registers). …”
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A Mixed Integer Linear Formulation and a Grouping League Championship Algorithm for a Multiperiod-Multitrip Order Picking System with Product Replenishment to Minimize Total Tardin... by Morteza Farhadi Sartangi, Ali Husseinzadeh Kashan, Hassan Haleh, Abolfazl Kazemi

“…A mixed integer linear programming formulation is proposed for this new problem. The model is optimally solved for small-size problems. …”
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AI approaches for phenotyping Alzheimer's disease and related dementias using electronic health records by Sara Knox, Stephanie Aghamoosa, Paul M. Heider, Maxwell Cutty, Andrew Wright, Dmitry Scherbakov, Gabriel Hood, Sara A. Nolin, Jihad S. Obeid

“…The study used artificial intelligence (AI)–based text classification methods to improve the detection of patients with ADRD. AI‐based models, including convolutional neural networks, outperformed the Chronic Conditions Warehouse algorithm.…”
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A hybrid AI-CFD framework for optimizing heat transfer of a premixed methane-air flame jet on inclined surfaces by Panit Kamma, Kittipos Loksupapaiboon, Juthanee Phromjan, Chakrit Suvanjumrat

“…To reduce the computational expense of these simulations, a hybrid Artificial Neural Network-Genetic Algorithm (ANN-GA) model was developed. The ANN accurately predicted thermal efficiency based on operational parameters, while the GA optimized these inputs to achieve maximum thermal efficiency of 76.9955 %, closely matching the CFD-predicted value of 70.86 % (discrepancy:6.1355 %). …”
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