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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Validation of an AI-Assisted Terrain-Aided Navigation Algorithm Using Real-World Flight Test Instrumentation Data by Ümit Can Bekar, Bilgehan Tanyeri, Ibrahim Enes Uslu, Nuri Arda Gungor, Gokhan Inalhan

“…A significant development is the AI model’s capacity to independently alternate between the resource-intensive search algorithm and a set of filters, thereby maintaining navigational accuracy while facilitating in-flight execution without supplementary hardware requirements. …”
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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

“…Data clustering is done by both algorithms and then the performance value is Evaluated using Davies Bouldin Index DBI shows that K-Means gives better results, with a lower DBI value (0.204 at K=5) while K-Medoids has a DBI value of 0.239 at K=5, which indicates more compact and separated clusters. …”
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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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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

“…The ANN predicts mass and stiffness with over 99% accuracy while reducing computational time by 95% compared to full FE simulations. …”
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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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K-Means Clustering Algorithm Measuring the Satisfaction Level of MNC TV Muslim I'murojaah Program Viewers by Herayati Herayati, Andronias Siregar, Hariyanto Hariyanto

“…The results of the first cluster iteration distance calculation consisted of 84 viewers who were very satisfied, while the second cluster consisted of 16 viewers with relatively low satisfaction levels. …”
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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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Identifying candidate biomarkers for detecting bronchogenic carcinoma stages using metaheuristic algorithms based on information fusion theory by Bagher Khalvati, Kaveh Kavousi, Amir Hosein Keyhanipour, Masoud Arabfard

“…To identify robust biomarkers, we applied eight metaheuristic algorithms for feature selection, combined with four classification methods and two data fusion techniques to optimize performance. …”
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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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Hybrid Metaheuristic Model for Optimal Economic Load Dispatch in Renewable Hybrid Energy System by D. Blandina Miracle, R. K. Viral, P. M. Tiwari, Mohit Bansal

“…In particular, the cost function of POCSO is 6.25%, 6%, 11.7%, 36%, 27%, and 46.42% better than the cost function of whale optimization algorithm (WOA), elephant herd optimization (EHO), moth-flame optimization (MFO), dragonfly algorithm (DA), sealion optimization (SLnO), CSO, and PSO methods, respectively. …”
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Multiple-to-single maximum power point tracking for empowering conventional MPPT algorithms under partial shading conditions by Njimboh Henry Alombah, Ambe Harrison, Wulfran Fendzi Mbasso, Hamid Belghiti, Hilaire Bertrand Fotsin, Pradeep Jangir, Saad F. Al-Gahtani, Z. M. S. Elbarbary

“…By eliminating oscillations and hotspot risks through voltage regulation, the framework retains algorithmic simplicity while enhancing performance under complex shading scenarios. …”
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Integrating Genetic Algorithm and Geographically Weighted Approaches into Machine Learning Improves Soil pH Prediction in China by Wantao Zhang, Jingyi Ji, Binbin Li, Xiao Deng, Mingxiang Xu

“…This study integrates Geographic Weighted Regression (GWR) with three ML models (Random Forest, Cubist, and XGBoost) and designs and develops three geographically weighted machine learning models optimized by Genetic Algorithms to improve the prediction of soil pH values. …”
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