Comparison of K-Nearest Neighbors and Naive Bayes Classifier Algorithms in Sentiment Analysis of 2024 Election in Twitter (X) by Lola Enjelia, Yana Cahyana, Rahmat, Deden Wahiddin

“…This study compares the performance of the K-Nearest Neighbors (K-NN) and Naive Bayes Classifier (NBC) algorithms in sentiment analysis of the 2024 Regional Election (Pilkada) based on Indonesian local data sourced from platform X. …”
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A modified TOPSIS algorithm for the assessment of sports quality in higher education using circular pythagorean fuzzy information by Jiapeng Li, Yitong Zhang

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AI-Based Prediction of Warpage in Organic Substrates by Jingyi Zhao, Meiying Su, Rui Ma

“…Therefore, investigating the effects of material types and structural layouts on warpage is essential for design optimization. However, traditional experimental approaches incur high costs, while case-by-case finite element method (FEM) modeling presents computational bottlenecks. …”
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A Centralized–Distributed Joint Routing Algorithm for LEO Satellite Constellations Based on Multi-Agent Reinforcement Learning by Licheng Xia, Baojun Lin, Shuai Zhao, Yanchun Zhao

“…In MARL-JR, ground stations initialize Q-tables and upload them to satellites, reducing onboard computational overhead while enhancing routing performance. Compared to traditional centralized algorithms, MARL-JR achieves faster link-state awareness and adaptation; compared to distributed algorithms, it delivers superior initial performance due to optimized pre-training. …”
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Comparison of K-Means and K-Medoids Algorithms for Clustering Poverty Data in South Sumatra Using DBI Evaluation by M. Dandi Akhda, Ken Ditha Tania

“…The superiority of K-Means is due to the homogeneous and minimal outlier characteristics of the dataset, which makes the centroid approach more optimal than medoids in K-Medoids. With these results, K-Means was chosen as the best algorithm for clustering poverty data in the region. …”
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Combining the Improved RGB Water-Filling Algorithm With Penumbra Removal Technique for Shadow Removal From Digitized Images by You-Chang Liu, Cheng-Ta Chuang

“…The proposed method introduces an RGB water-filling algorithm specifically designed to address soft shadows, optimized with matrix operations and a streamlined processing workflow that substantially enhance the computational efficiency over existing methods. …”
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Enhancing Security and Privacy in 5G Device-to-Device Communication: A Secure Gale-Shapley Algorithm Approach by Musaad Alruwaili, Junghwan Kim, Jared Oluoch

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Application of SMOTE-ENN Method in Data Balancing for Classification of Diabetes Health Indicators with C4.5 Algorithm by Bakti Putra Pamungkas, Muhammad Jauhar Vikri, Ita Aristia Sa'ida

“…Therefore, further exploration of other balancing techniques and algorithms is needed to obtain more optimal classification results on unbalanced data.…”
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Improving the performance of machine learning algorithms for detection of individual pests and beneficial insects using feature selection techniques by Rabiu Aminu, Samantha M. Cook, David Ljungberg, Oliver Hensel, Abozar Nasirahmadi

“…The concept of explainable artificial intelligence was adopted by incorporating permutation feature importance ranking and Shapley Additive explanations values to identify the feature set that optimized a model's performance while reducing computational complexity. …”
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Comparative Model Efficiency Analysis Based on Dissimilar Algorithms for Image Learning and Correction as a Means of Fault-Finding by Joe Benganga, Tshepo Kukuni, Ben Kotze, Lepekola Lenkoe

“…The results demonstrate that VGG16 performed better in terms of data accuracy than both the testing and training models, while the Resnet_50 algorithm performed poorly in terms of the loss encountered compared to the other three algorithms.…”
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Smart Electric Vehicle Charging Algorithm to Reduce the Impact on Power Grids: A Reinforcement Learning Based Methodology by Federico Rossi, Cesar Diaz-Londono, Yang Li, Changfu Zou, Giambattista Gruosso

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Leveraging genetic algorithms and neural networks for stiffness and weight optimisation of an unmanned aerial vehicle (UAV) support arm by Iuri H. Müller, José Humberto S. Almeida Jr, Sandro C. Amico, Maikson L.P. Tonatto

“…NSGA-II then generates a Pareto front, from which an optimal design is selected and fabricated using fused filament fabrication (FFF) with polylactide (PLA). …”
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A Metaheuristic Framework for Cost-Effective Renewable Energy Planning: Integrating Green Bonds and Fiscal Incentives by Juan D. Saldarriaga-Loaiza, Johnatan M. Rodríguez-Serna, Jesús M. López-Lezama, Nicolás Muñoz-Galeano, Sergio D. Saldarriaga-Zuluaga

“…To do this, we use three optimization techniques to identify solutions that lower electricity generation costs: Teaching Learning, Harmony Search, and the Shuffled Frog Leaping Algorithm. …”
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Improvement of the TEB Algorithm for Local Path Planning of Car-like Mobile Robots Based on Fuzzy Logic Control by Lei Chen, Rui Liu, Daiyang Jia, Sijing Xian, Guo Ma

“…TEB (timed elastic band) can efficiently generate optimal trajectories that match the motion characteristics of car-like robots. …”
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Applying machine learning algorithms to explore the impact of combined noise and dust on hearing loss in occupationally exposed populations by Yong Li, Xin Sun, Yongtao Qu, Shuling Yang, Yueyi Zhai, Yan Qu

“…Chi-square and Mann-Whitney U tests examined variables, and multivariate logistic regression determined ONIHL risk factors. Machine learning algorithms like Logistic Regression and Random Forest were developed, optimized, and evaluated. …”
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BSDR: A Data-Efficient Deep Learning-Based Hyperspectral Band Selection Algorithm Using Discrete Relaxation by Mohammad Rahman, Shyh Wei Teng, Manzur Murshed, Manoranjan Paul, David Brennan

“…The algorithm employs discrete relaxation, transforming the discrete problem of band selection into a continuous optimization task, which enables gradient-based search across the spectral dimension. …”
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K-Means Clustering Algorithm Measuring the Satisfaction Level of MNC TV Muslim I'murojaah Program Viewers by Herayati Herayati, Andronias Siregar, Hariyanto Hariyanto

“…Recommendations for program improvement include enhancing image and sound quality, ensuring that the equipment and technology used can produce optimal quality. …”
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What Influences Low-cost Sensor Data Calibration? - A Systematic Assessment of Algorithms, Duration, and Predictor Selection by Lu Liang, Jacob Daniels

“…We further assessed the training sample size effect to understand the optimal duration of field calibration for achieving good accuracy. …”
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High-fidelity learning-based motion cueing algorithm by bypassing worst-case scenario-based tuning technique by Mohammad Reza Chalak Qazani, Houshyar Asadi, Zoran Najdovski, Shehab Alsanwy, Muhammad Zakarya, Furqan Alam, Hassen M. Ouakad, Chee Peng Lim, Saeid Nahavandi

“…Data samples are regenerated to cover various motion signal levels, and three classical washout filters are tuned to extract optimal motion signals. A multilayer perceptron (MLP) is trained with these extracted datasets, forming an AI-based MCA that provides high-fidelity driving motions for any scenario while optimising the platform workspace. …”
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An Assembled Feature Attentive Algorithm for Automatic Detection of Waste Water Treatment Plants Based on Multiple Neural Networks by Cong Li, Zhengchao Chen, Zhuonan Huang, Yue Shuai, Shaohua Wang, Xiangkun Qi, Jiayi Zheng

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