Data-Driven Robust Optimization for Solving the Heterogeneous Vehicle Routing Problem with Customer Demand Uncertainty by Jingling Zhang, Mengfan Yu, Qinbing Feng, Longlong Leng, Yanwei Zhao

“…Through test experiments, it is proved that the robust optimization model can effectively reduce the number of customers affected by the uncertainty, greatly improve customer satisfaction, and effectively reduce total cost and demonstrate that the improved algorithm also exhibits good performance.…”
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Implementation of personalized customization and enhanced experiences for cultural tourism resources using genetic algorithm-based virtual reality technology by Huiya Xing, Xiangyi Li, Min Liu, Yicong Zhong

“…By adjusting to these individual parameters, the algorithm cleverly optimizes tourist itineraries. The DDE-GA-powered VR system works better than current methods, according to experimental data, with improvements in reaction time (1.1 s), accuracy (98 %), precision (97 %), and modeling error (0.10). …”
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Flaw-YOLOv5s: A Lightweight Potato Surface Defect Detection Algorithm Based on Multi-Scale Feature Fusion by Haitao Wu, Ranhui Zhu, Hengren Wang, Xiangyou Wang, Jie Huang, Shuwei Liu

“…To elevate detection accuracy as well as shorten the computational load of the model, this paper proposes a lightweight Flaw-YOLOv5s algorithm for potato surface defect detection. …”
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Machine learning based shear strength prediction in reinforced concrete beams using Levy flight enhanced decision trees by Aybike Özyüksel Çiftçioğlu, Anıl Delikanlı, Torkan Shafighfard, Faramarz Bagherzadeh

“…The proposed method combines the structure of Decision Tree algorithm with Levy Flight, a stochastic optimization technique, to improve global search capabilities and avoid local minima. …”
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BIT*+TD3 Hybrid Algorithm for Energy-Efficient Path Planning of Unmanned Surface Vehicles in Complex Inland Waterways by Yunze Xie, Yiping Ma, Yiming Cheng, Zhiqian Li, Xiaoyu Liu

“…To address the limitations of traditional path planning algorithms in dynamic environments, the proposed BIT*+TD3 model leverages the BIT* algorithm to generate initial paths in static environments through elliptical informed sampling and heuristic search. …”
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Innovative IoT-enabled mask detection system: A hybrid deep learning approach for public health applications by Parul Dubey, Vinay Keswani, Pushkar Dubey, Gunjan Keswani, Dhananjay Bhagat

“…The novelty of the paper lies in combining AFSO with a hybrid deep learning architecture for parameter optimization and improved scalability. Performance metrics such as accuracy, sensitivity, precision, and F1-score were used to evaluate the model. …”
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Data Mining Techniques for Early Detection and Classification of Plant Diseases: An Optimization-Based Approach by Wagh Swapnil, Sharma Ruchi

“…Furthermore, low-level optimization techniques like genetic algorithms as well as particle swarm optimization are used to fine tune the specific model parameters and to reduce the computational overhead for improving the detection efficacy still more. …”
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Autonomous Maneuver Decision of UCAV Air Combat Based on Double Deep Q Network Algorithm and Stochastic Game Theory by Yuan Cao, Ying-Xin Kou, Zhan-Wu Li, An Xu

“…Then, the double deep Q network (DDQN) algorithm in reinforcement learning (RL) is introduced to train the agent by the interaction with the environment and combined with Minimax algorithm in stochastic game theory to solve the optimal value function in each specific state, and the optimal maneuver decision of UCAV is obtained. …”
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A Comparative Analysis of Hyper-Parameter Optimization Methods for Predicting Heart Failure Outcomes by Qisthi Alhazmi Hidayaturrohman, Eisuke Hanada

“…The XGBoost models exhibited moderate improvement (+0.01683) post-validation. …”
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Reliability evaluation and multi-objective optimization of combustion chamber’s key components of marine engine by Lei Hu, Wentong Wang, Xu Wang, Jianguo Yang, Yonghua Yu, Chunyang Mei

“…Constrained multi-objective optimization of reliability is conducted through contrastive analysis of different optimization algorithms. …”
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Comparison between logistic regression and machine learning algorithms on prediction of noise-induced hearing loss and investigation of SNP loci by Jie Lu, Xinhao Lu, Yixiao Wang, Hengdong Zhang, Lei Han, Baoli Zhu, Boshen Wang

“…Compared to conventional LR, the evaluated ML models Generalized Regression Neural Network (GRNN), Probabilistic Neural Network (PNN), Genetic Algorithm-Random Forests (GA-RF) demonstrate superior performance and were considered to be the optimal models for processing large-scale SNP loci dataset. …”
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Enhanced 3-D Reconstruction Method for Polarimetric Coherent Optimal-Based Tomographic SAR by Shuhang Dong, Zekun Jiao, Liangjiang Zhou, Xiaolan Qiu, Qiancheng Yan

“…However, in the practical application, there are relatively few models and algorithms for full-polarized SAR joint 3-D imaging. …”
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Review of Demand Response-based Optimal Scheduling of Electric and Thermal Integrated Energy Systems by Jingshan MO, Guangxian YAN, Na SONG, Mingyang YUAN

“…Artificial intelligence algorithms are primarily divided into methods based on group optimization problems and machine learning algorithms. …”
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Lightweight Anomaly-Based Detection Using Cuckoo Search Algorithm and Decision Tree to Mitigate Man-in-the-Middle Attacks in DNS by Ramahlapane Lerato Moila, Mthulisi Velempini

“…By integrating the Cuckoo Search Algorithm, the scheme minimizes false positives while improving the detection rate. …”
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Generalizable Solar Irradiance Prediction for Battery Operation Optimization in IoT-Based Microgrid Environments by Ray Colucci, Imad Mahgoub

“…We evaluated five popular machine learning algorithms and applied ensemble methods, achieving a substantial improvement in predictive accuracy. …”
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Conversion Prediction in Google Search Ads Keyword Selection Using the K-Nearest Neighbor and C4.5 Algorithms by Muhammad Sya'ban Harahap, Alva Hendi Muhammad

“…This study was conducted to analyze and compare the effectiveness of two algorithms—K-Nearest Neighbor (K-NN) and C4.5—in predicting keyword conversion on the Google Ads platform. …”
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A hybrid critical channels and optimal feature subset selection framework for EEG fatigue recognition by Hanying Guo, Siying Chen, Yongjiang Zhou, Ting Xu, Yuhao Zhang, Hongliang Ding

“…Abstract Fatigue driving is one of the potential factors threatening road safety, and monitoring drivers’ mental state through electroencephalography (EEG) can effectively prevent such risks. In this paper, a new model, DE-GFRJMCMC, is proposed for selecting critical channels and optimal feature subsets from EEG data to improve the accuracy of fatigue driving recognition. …”
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An Efficient Algorithm for Extracting Railway Tracks Based on Spatial-Channel Graph Convolutional Network and Deep Neural Residual Network by Yanbin Weng, Meng Xu, Xiahu Chen, Cheng Peng, Hui Xiang, Peixin Xie, Hua Yin

“…This is a 3.17% improvement over the original U-Net model, indicating excellent performance in railway track segmentation. …”
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ML-Based Self-Optimization Handover Technique for Beyond 5G Mobile Network by Saddam Alraih, Rosdiadee Nordin, Asma Abu-Samah, Ibraheem Shayea, Nor Fadzilah Abdullah

“…Furthermore, ML-SOHOT achieves an average HO performance improvement of up to 96% compared to competitive algorithms from the literature. …”
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Wide Bandwidth Inverse Synthetic Aperture Radar Imaging and Cross-Range Scaling via Modified Polar Format Algorithm by Rongzhen Du, Lei Liu, Yinyin Jiang, Xiangyong Cao, Xueru Bai, Feng Zhou

“…Traditional algorithms model rotation as a polynomial to compensate for these errors, but this approach becomes computationally intensive and less accurate with higher bandwidths. …”
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