Klasifikasi Kebutuhan Jumlah Produk Makanan Customer Menggunakan K-Means Clustering dengan Optimasi Pusat Awal Cluster Algoritma Genetika by Yudi Istianto, Shofwatul 'Uyun

“…This study tries to apply data mining to classify the number of customer needs for food products using k-means clustering with optimization initial cluster center genetic algorithm. …”
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RivAIr: A custom-designed UAV-based sensor for real-time water area segmentation and surface velocity estimation by Marco La Salandra, Rosa Colacicco, Simone Panza, Giovanni Fumai, Pierfrancesco Dellino, Domenico Capolongo

“…Unlike existing methods that rely on post-processing, RivAIr is purpose-built for real-time field deployment in data-scarce or emergency scenarios.RivAIr integrates YOLOv8 with an optimized Farneback dense optical flow algorithm focused on water bodies, improving motion estimation accuracy while reducing runtime for real-time UAV processing. …”
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Exploring the Realization of Creative Dimensions within the Metaverse: The Case of Tabriz Metropolis by Saied Jaffari namvar, Hossein Nazmfar, Ibrahim Taghav

“…Based on the Aras Gray technique, regions 5, 8, and 10 were identified as the most optimal choices, while regions 6 and 9 were deemed less ideal. …”
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On Analysis of Traffic Flow Demultiplexing Effectiveness by Evgeniy P. Stepanov

“…Special attention is paid to algorithms that allow you to build routes with minimal intersections, since using the nonintersecting routes with non-optimal cost can increase the network performance. …”
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Sistem Kontrol Swarm untuk Flocking Wahana NR-Awak Quadrotor dengan Optimasi Algoritma Genetik by Endra Joelianto, Winarendra Satya Rajasa, Agus Samsi

“…The controller that is designed has many parameters, so the optimal parameter selection is very difficult. The search for optimal parameters in the swarm model controller requires optimization techniques such as the genetic algorithm (GA) to direct the search for solutions that produce the best performance. …”
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Opportunities, Challenges, and Future Directions for Generative Artificial Intelligence in Library Information Literacy Education: A Scoping Review by Fan YUAN, Jia LI

“…This methodological approach enabled a thorough exploration of current practices while identifying critical gaps in existing research. …”
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Predicting Index Trend Using Hybrid Neural Networks with a Focus on Multi-Scale Temporal Feature Extraction in the Tehran Stock Exchange by Mohammad Osoolian, Ali Nikmaram, Mahdi Karimi

“…Moreover, to further enhance the performance and resilience of the model, sophisticated feature engineering methodologies are implemented to optimize its overall functionality. ResultsThe results of the study reveal that while the hybrid neural network model, integrating CNN and LSTM components, demonstrates promising capabilities in predicting the TSE Composite Index, its accuracy falls short compared to competing models, particularly at weekly and monthly time scales. …”
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Evaluation of Neural, Systemic and Extracerebral Activations During Active Walking Tasks in Older Adults Using fNIRS by Meltem Izzetoglu, Roee Holtzer

“…Such involved designs further allowed the implementation of advanced signal processing algorithms to separate and evaluate neural, systemic and extracerebral signal contributions on the overall measurements. …”
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Atrial fibrillation and chronic kidney disease: main clinical characteristics of patients in selected subjects of the Russian Federation by M. A. Druzhilov, T. Yu. Kuznetsova, O. Yu. Druzhilova, U. D. Arustamova, D. V. Gavrilov, A. V. Gusev

“…This emphasizes the need to optimize risk stratification, ACT and algorithms for the prevention of athero­thrombotic events, as well as the development of nephro­protective strategies to reduce the rate of progression of renal dys­function in this cohort of patients.…”
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Predictive Modeling of Acute Respiratory Distress Syndrome Using Machine Learning: Systematic Review and Meta-Analysis by Jinxi Yang, Siyao Zeng, Shanpeng Cui, Junbo Zheng, Hongliang Wang

“…Early detection and accurate prediction of ARDS can significantly improve patient outcomes. While machine learning (ML) models are increasingly being used for ARDS prediction, there is a lack of consensus on the most effective model or methodology. …”
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Plastic Litter Detection in the Environment Using Hyperspectral Aerial Remote Sensing and Machine Learning by Marco Balsi, Monica Moroni, Soufyane Bouchelaghem

“…Several algorithms for spectrum calibration, feature selection, and classification were optimized and compared to obtain an optimal solution that has high-quality results under cross-validation. …”
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The potentials of vehicle-grid integration on peak shaving of a community considering random behavior of aggregated vehicles by Yalun Li, Kun Wang, Chaojie Xu, Yu Wu, Liguo Li, Yuejiu Zheng, Shichun Yang, Hewu Wang, Minggao Ouyang

“…In a typical residential community with 100 EVs per 1000 people, disorderly charging increases the peak load by 17.1%, while VGI, with a participation ratio of 30%, reduces the load range by 74.8%. …”
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Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics by Xiao Li, Bo Wang, Xiaocong Li, Juan He, Yue Shi, Rui Wang, Dongwei Li, Ding Haitao, Ding Haitao

“…Machine learning algorithms were subsequently used to identify the optimal combination of diagnostic biomarkers. …”
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A Synergistic Approach to Colon Cancer Detection: Leveraging EfficientNet and NSGA-II for Enhanced Diagnostic Performance by Noushin Saba, Afia Zafar, Mohsin Suleman, Kainat Zafar, Shahneer Zafar, Adil Ali Saleem, Hafeez Ur Rehman Siddiqui, Muhammad Iqbal, Syed Sajid Ullah

“…We employed EfficientNet, a state-of-the-art convolutional neural network, to extract intricate features from histopathological images, alongside the Non-dominated Sorting Genetic Algorithm II for optimal feature selection. This hybrid approach significantly enhances diagnostic performance while reducing computational complexity. …”
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An enhanced substation equipment detection method based on distributed federated learning by Zhuyun Li, Qiutong Qin, Yingyi Yang, Xiaoming Mai, Yuya Ieiri, Osamu Yoshie

“…For FL, the Federated Adaptive (FedAdp) algorithm reduces communication rounds by 62% compared to Federated Averaging (FedAvg), maintaining near-centralized accuracy while preserving data locality. …”
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Hyperspectral imaging combined with residual-attention-net for spectral-spatial feature fusion in liver disease diagnosis by Yunze Li, Jingjing Wang, Miaoqing Zhao, Jinlin Deng, Chongxuan Tian, Qize Lv, Yifei Liu, Kun Ru, Wei Li

“…We incorporated band selection techniques, including the Norris derivative and the Successive Projections Algorithm (SPA), and optimized the data processing workflow. …”
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Capacity Estimation of Lithium-Ion Battery Systems in Fuel Cell Ships Based on Deep Learning Model by Xiangguo Yang, Jia Tang, Qijia Song, Yifan Liu, Lin Liu, Xingwei Zhou, Yuelin Chen, Telu Tang

“…A TCN-BiGRU model is then developed, with hyperparameters determined by the Kepler optimization algorithm (KOA). Cells from a battery pack under consistent conditions are used for training, while other cells in the same pack serve as the test set. …”
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Constrained Cross Entropy Localization Technique for Wireless Sensor Networks by Mohammad Abdul Azim, Zeyar Aung, Weidong Xiao, Vinod Khadkikar

“…Addressing the challenges in cross entropy (CE) localization utilizing cross entropy optimization technique in turn minimizes the localization error with a reasonable processing cost and provides a balance between the algorithmic runtime and error. …”
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Short-Term Scheduling of Pump Station-integrated Cascade Hybrid Pumped Storage Systems by QIAN Jun, TAN Qiaofeng, WEN Xin, ZHENG Mingfen, SHEN Yanqing

“…The traditional step-by-step optimization algorithm was improved to solve this model. …”
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Hot deformation physical mechanisms and a unified constitutive model of a solid solution Ti55511 alloy deformed in the two-phase region by Huijie Zhang, Y.C. Lin, Gang Su, Yongfu Xie, Wei Qiu, Ningfu Zeng, Song Zhang, Guicheng Wu

“…Material constants are determined using a genetic algorithm (GA), and the experimental data align well with the predicted data. …”
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