Deep Reinforcement Learning for Dynamic Pricing and Ordering Policies in Perishable Inventory Management by Yusuke Nomura, Ziang Liu, Tatsushi Nishi

“…To tackle this challenge, we propose eliminating irrational actions in dynamic programming without sacrificing optimality. To solve this problem more efficiently, we also implement a deep reinforcement learning algorithm, proximal policy optimization, to solve this problem. …”
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A Design Framework for Scalable and Adaptive Multi-Agent Coordination in Dynamic Environments: Addressing Concurrent Agent and Environment Interactions by Raza Muhammad Kazim, Guoxin Wang, Zhenjun Ming, Jinhui Cao, Janet K. Allen, Farrokh Mistree

“…In this study, we explore the integration of surrogate response surface modeling (SRSM) with optimization algorithms, comparing Stochastic Gradient Descent (SGD) with a fixed learning rate, and adaptive learning rate (ALR) optimizers—including Adaptive Moment Estimation (ADAM) and Adaptive Approximate Direction Method Algorithm (AADMA)—to enhance MAS performance metrics, such as Agent Collision Rate (ACR), Agent Movement Frequency (AMF), and Task Completion Time (TCT). …”
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Learning efficient haptic shape exploration with a rigid tactile sensor array. by Sascha Fleer, Alexandra Moringen, Roberta L Klatzky, Helge Ritter

“…This environment contains a set of rigid static objects representing a selection of one-dimensional local shape features embedded in a 3D space: an edge, a flat and a convex surface. The proposed algorithm simultaneously optimizes main perception-action loop components: feature extraction, integration of features over time, and the control strategy, while continuously acquiring data online. …”
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DeepSARFlood: Rapid and automated SAR-based flood inundation mapping using vision transformer-based deep ensembles with uncertainty estimates by Nirdesh Kumar Sharma, Manabendra Saharia

“…These labels are used to train deep learning models based on Convolutional Neural Networks (CNN) and Vision Transformer (ViT) architectures, optimized through multitask learning and model soups. …”
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Machine learning analysis of thermo-bioconvection in a micropolar hybrid nanofluid-filled square cavity with oxytactic microorganisms by Ahlawat Anil, Chaudhary Shilpa, Karuppusamy Loganathan, Mohammed Salman Arafath, Kandasamy Thirumalaisamy, Thameem Basha Hayath

“…In addition, a machine learning approach was employed to accurately predict fluid transport properties using a multilayer artificial neural network structured with a feed-forward backpropagation model and optimized using the Levenberg–Marquardt algorithm. …”
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Coordinated Jamming and Poisoning Attack Detection and Mitigation in Wireless Federated Learning Networks by Sofia Barkatsa, Maria Diamanti, Panagiotis Charatsaris, Stefanos Voikos, Eirini Eleni Tsiropoulou, Symeon Papavassiliou

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Сombat wounds microflora in modern warfare by V. P. Kovalchuk, N. S. Fomina, V. M. Kondratiuk, О. О. Fomin, Y. V. Lazarenko, K. V. Gumenyuk

“…Analysis of the clonal characteristics and antibiotic resistance of the most prevalent wound pathogens among individuals injured in the Russian-Ukrainian war to support microbiota surveillance of combat wounds and optimize treatment strategies. Materials and Methods. …”
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Machine learning, clinical-radiomics approach with HIM for hemorrhagic transformation prediction after thrombectomy and treatment by Sheng Hu, Junyu Liu, Jiayi Hong, Yuting Chen, Ziwen Wang, Jibo Hu, Shiying Gai, Xiaochao Yu, Jingjing Fu

“…The support vector machine (SVM) was the optimal ML algorithm for constructing the models. …”
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Modeling the Stability of the Housing and Construction Complex Based on Organizational and Economic Interaction of Entities by N. N. Shelomentseva, O. V. Grushina

“…A genetic algorithm in MATLAB was used for this purpose. Acceptable options for all participants were selected from a set of Pareto-optimal alternatives based on the preferences of the decision-maker. …”
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MAOOA‐Residual‐Attention‐BiConvLSTM: An Automated Deep Learning Framework for Global TEC Map Prediction by Haoran Wang, Haijun Liu, Jing Yuan, Huijun Le, Weifeng Shan, Liangchao Li

“…It also includes an optimization algorithm, MAOOA, for optimizing the hyper‐parameters of the model. …”
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Spatiotemporal pattern analysis of land use in Jiangsu Province based on long-term time series remote sensing images by Zhendong Ji, Lingzhi Yin, Jinhong Wang

“…Principal Component Analysis (PCA) was applied to reduce feature dimensionality, and the Random Forest classification algorithm was optimized with Bayesian Optimization and Tree-structured Parzen Estimators (TPE) for improved performance. …”
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Preoperative MRI-based radiomics analysis of intra- and peritumoral regions for predicting CD3 expression in early cervical cancer by Rui Zhang, Chunfan Jiang, Feng Li, Lin Li, Xiaomin Qin, Jiang Yang, Huabing Lv, Tao Ai, Lei Deng, Chencui Huang, Hui Xing, Feng Wu

“…Various machine learning algorithms, including Support Vector Machine (SVM), Logistic Regression, Random Forest, AdaBoost, and Decision Tree, were used to construct radiomics models based on different ROIs, and diagnostic performances were compared to identify the optimal approach. …”
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Reliability Analysis of Three-dimensional Soil Slopes Considering Spatial Variability of Soil Parameters by Wan Yukuai, Zhou Yuqi, Shao Linlan, Wang Yuke, Zhang Fei

“…The particle swarm optimization (PSO) algorithm is refined with enhanced termination criteria and integrated with the 3D Bishop method to search for the minimum factor of safety (F). …”
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Innovative Treatment of Combat-Related Extraperitoneal Penetrating Rectal Injury with Intraluminal Vacuum Therapy: A Case Report by Yafa Shani Parnasa, Oded Cohen-Arazi, Gad Marom, Mahmoud Abu-Gazala, Noam Shussman, Miklosh Bala

“…This case highlights ILVT as a novel method for managing complicated blast-related rectal injuries. While there are limited publications on combat-related penetrating rectal injuries that provide evidence-based guidelines, we suggest an aggressive surgical approach combined with negative pressure wound therapy for optimal patient outcomes.…”
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Research and application of deep learning object detection methods for forest fire smoke recognition by Luhao He, Yongzhang Zhou, Lei Liu, Yuqing Zhang, Jianhua Ma

“…Abstract Forest fires are severe ecological disasters worldwide that cause extensive ecological destruction and economic losses while threatening biodiversity and human safety. …”
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An edge awareness-enhanced visual SLAM method for underground coal mines by Qi MU, Xin LIANG, Yuanjie GUO, Yuhao WANG, Zhanli LI

“…Specifically, images with clear textures and uniform illumination were obtained using the Retinex algorithm optimized using an adaptive gradient-domain guided filter. …”
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A combined model integrating deep learning, radiomics, and clinical ultrasound features for predicting BRAF V600E mutation in papillary thyroid carcinoma with Hashimoto’s thyroidit... by Peng-Fei Zhu, Xiao-Feng Zhang, Pu Zhou, Jiang-Yuan Ben, Hao Wang, Shu-E Zeng, Xin-Wu Cui, Ying He

“…Feature selection was performed using Pearson’s correlation coefficient, the Minimum Redundancy Maximum Relevance (mRMR) algorithm, and LASSO regression. The optimal algorithm was selected from nine machine learning algorithms for model construction, including the traditional radiomics model (RAD), the deep learning model (DL), and their fusion model (DL_RAD). …”
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Terrain and individual tree vertical structure-based approach for point clouds co-registration by UAV and Backpack LiDAR by Tingwei Zhang, Xin Shen, Lin Cao

“…., UAV LiDAR systems tend to overlook details of the tree trunk or the lower ground, while Backpack LiDAR systems struggle to capture the treetop, etc. …”
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Research on the integrated "cloud-edge-end" intelligent and precise management and control technology system for coal mine disasters by LIU Yubing, LI Yiteng, LI Zhonghui, YIN Shan, JING Chao, LI Kai, LI Zhenxing, ZHAO Shenglei, LIU Chengfei

“…Existing research mainly focuses on monitoring and early warning technologies or algorithm optimization for individual disasters, lacking a coordinated mechanism for multi-disaster monitoring and early warning, as well as disaster avoidance path planning under emergency response. …”
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Monitoring multiyear cropping patterns in the arid regions of northwestern China from 2005 to 2022 using Landsat time-series data by Yongquan Lu, Guilin Liu, Xiuyuan Zhang, Jingwen Wang, Weijia Chen, Yuecheng Li, Desheng Jiang

“…Understanding cropping patterns can help optimize crop yield while preserving ecosystems and enhancing ecological benefits. …”
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