Research on Local Obstacle Avoidance Path Planning Algorithm for Autonomous Mining Trucks by HUANG Shuai, WANG Jia, HUANG Jiade, HUANG Peng, LYU Liang

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Early warning strategies for corporate operational risk: A study by an improved random forest algorithm using FCM clustering. by Xini Fang

“…Finally, an improved RF model is constructed by optimizing the parameters of the RF algorithm. …”
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Optimizing Scheduled Train Service for Seaport-Hinterland Corridors: A Time-Space-State Network Approach by Yueyi Li, Xiaodong Zhang

“…Furthermore, an improved adaptive large neighborhood search (ALNS) algorithm is developed to enhance computational efficiency and solution quality. …”
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MSPB-YOLO: High-Precision Detection Algorithm of Multi-Site Pepper Blight Disease Based on Improved YOLOv8 by Xiaodong Zheng, Zichun Shao, Yile Chen, Hui Zeng, Junming Chen

“…Furthermore, we optimized CIOU to DIOU by integrating the center distance of bounding boxes into the loss function; as a result, the model achieved an impressive mAP@0.5 score of 96.4%. …”
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An Improved Adaptive Large Neighborhood Search Algorithm for the Heterogeneous Customized Bus Service with Multiple Pickup and Delivery Candidate Locations by Shouqiang Xue, Rui Song, Shiwei He, Jiuyu An, Youmiao Wang

“…Finally, we test the performance of the proposed model and algorithm on the numerical experiments. …”
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Optimized deep learning approach for lung cancer detection using flying fox optimization and bidirectional generative adversarial networks by Manal Abdullah Alohali, Hamed Alqahtani, Shouki A. Ebad, Faiz Abdullah Alotaibi, Venkatachalam K., Jaehyuk Cho

“…The methodology consists of three key phases: (1) Data preprocessing, where missing values are handled using the multiple imputations by chain equation (MICE) technique and feature scaling is applied using standard and min-max scalers; (2) Feature selection, where the FFXO algorithm reduces feature dimensionality to enhance classification efficiency; and (3) Lung tumor classification, utilizing Bi-GAN to improve predictive accuracy. …”
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VCNet: Optimized Deep Learning framework with deep feature extraction and genetic algorithm for multiclass rice crop disease detection by Sanam Salman Kazi, Bhakti Palkar, Dhirendra Mishra

“…It also requires fewer parameters and takes minimum training time. • The major contribution of this study is the design of an optimized, efficient and enhanced deep learning technique for multiclass rice crop disease detection embracing with batch normalization, dropout and genetic optimization algorithm to improve generalization power and restrict the overlearning capability for seen and unseen data. • Proposed VCNet, a shallow model with deep feature extraction, employs VGG16 layers for initial extraction fused with custom CNN architecture to correctly detect the challenging classes of diseases like sheath rot in multiclass classification. • The most significant observation is that VCNet accurately predicts the rice disease for each class of diseases under study whereas the existing powerful models largely misclassified for some classes of diseases in multiclass classification.…”
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Optimizing Hyperparameters in Meta-Learning for Enhanced Image Classification by Amala Mary Vincent, P. Jidesh, A. A. Bini

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Optimization of a Coupled Neuron Model Based on Deep Reinforcement Learning and Application of the Model in Bearing Fault Diagnosis by Shan Wang, Jiaxiang Li, Xinsheng Xu, Ruiqi Wu, Yuhang Qiu, Xuwen Chen, Zijian Qiao

“…By comparing the coupled neuron model optimized with a reinforcement learning algorithm, particle swarm algorithm, and quantum particle swarm algorithm, the experimental results show that the coupled neuron model optimized with a deep reinforcement learning algorithm has the optimal signal-to-noise ratio of the output signal and recognition rate of the bearing faults, which are −13.0407 dB and 100%, respectively. …”
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Application Research of Key Frames Extraction Technology Combined with Optimized Faster R-CNN Algorithm in Traffic Video Analysis by Zhi-guang Jiang, Xiao-tian Shi

“…The experimental results show that the key frame extraction technology combined with the optimized Faster R-CNN algorithm model greatly improves the accuracy of detection and reduces the leakage. …”
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An unmanned intelligent inspection technology based on improved reinforcement learning algorithm for power large-area multi-scene inspection by Enmin Wang, Xin Meng, Jinglong Yu, Jiechang Wang, Liang Yin

“…Consequently, this study investigates a multi scene unmanned intelligent patrol technology for power large area, based on an improved reinforcement learning algorithm. The unmanned intelligent patrol model is designed according to the patrol UAVs, wireless charging piles distributed in appropriate locations, and the targets to be patrolled (i.e., multiple scenes within a large power area). …”
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Prediction and optimization of hardness in AlSi10Mg alloy produced by laser powder bed fusion using statistical and machine learning approaches by İnayet Burcu Toprak

“…This study highlights the importance of integrating Machine Learning and statistical analysis methods for the effective modeling and optimization of LPBF processes. The findings contribute significantly to the literature and serve as a valuable reference for future research aimed at improving LPBF process efficiency and performance.…”
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A Q-Learning Crested Porcupine Optimizer for Adaptive UAV Path Planning by Jiandong Liu, Yuejun He, Bing Shen, Jing Wang, Penggang Wang, Guoqing Zhang, Xiang Zhuang, Ran Chen, Wei Luo

“…To address these issues, this paper proposes an algorithm named QCPO, which integrates CPO with Q-learning to improve UAV path optimization performance. …”
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Global optimization of economic load dispatch in large scale power systems using an enhanced social network search algorithm by Mohamed H. Hassan, Salah Kamel, Francisco Jurado, Umberto Desideri

“…The primary goal is to improve the algorithm's ability to explore global search possibilities while avoiding being trapped in locally optimal solutions. …”
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Multi mobile agent itinerary planning based on network coverage and multi-objective discrete social spider optimization algorithm by Zhou-zhou LIU, Shi-ning LI

“…The multi mobile agent collaboration planning model was constructed based on the mobile agent load balancing and total network energy consumption index.In order to prolong the network lifetime,the network node dormancy mechanism based on WSN network coverage was put forward,using fewer worked nodes to meet the requirements of network coverage.According to the multi mobile agent collaborative planning technical features,the multi-objective discrete social spider optimization algorithm (MDSSO) with Pareto optimal solutions was designed.The interpolation learning and exchange variations particle updating strategy was redefined,and the optimal set size was adjusted dynamically,which helps to improve the accuracy of MDSSO.Simulation results show that the proposed algorithm can quickly give the WSN multi mobile agent path planning scheme,and compared with other schemes,the network total energy consumption has reduced by 15%,and the network lifetime has increased by 23%.…”
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Quantum-inspired robust optimization for coordinated scheduling of PV-hydrogen microgrids under multi-dimensional uncertainties by Yunxiao Bai, Yu Sui, Xiaoyu Deng, Xiangbing Wang

“…Stress-testing under scenarios such as 48-hour grid failure, signal-based cyberattacks, and 40% PV output curtailment reveals substantial gains: operational costs are reduced by 9.3%, resilience scores improve by over 20% in adverse conditions, and convergence speed increases by 42% relative to classical optimization. …”
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Application of Multi-Strategy Controlled Rime Algorithm in Path Planning for Delivery Robots by Haokai Lv, Qian Qian, Jiawen Pan, Miao Song, Yong Feng, Yingna Li

“…This research addresses the robot path planning problem, aiming to enhance delivery efficiency and reduce operational costs through systematic improvements to the RIME optimization algorithm. …”
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Numerical Design Structure Matrix–Genetic Algorithm-Based Optimization Method for Design Process of Complex Civil Aircraft Systems by Qiucen Fan, Yanlong Han, An Zhang, Wenhao Bi

“…The algorithm NSGA-II is improved and verified with the flight control system design as a case study. …”
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Deep Learning–Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization by Dawen Wu, Yanfei Li, Zeyi Yang, Teng Yin, Xiaohang Chen, Jingyu Liu, Wenyi Shang, Bin Xie, Guoyuan Yang, Haixian Zhang, Longqian Liu

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Underwater image dehazing using a hybrid GAN with bottleneck attention and improved Retinex-based optimization by Amandeep Kaur, Shalli Rani, Mohammad Shabaz

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