Advanced Interpretation of Bullet-Affected Chest X-Rays Using Deep Transfer Learning by Shaheer Khan, Nirban Bhowmick, Azib Farooq, Muhammad Zahid, Sultan Shoaib, Saqlain Razzaq, Abdul Razzaq, Yasar Amin

“…Special deep learning algorithms went through a process of optimization before researchers improved their ability to detect and place objects. …”
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YOLO11-ARAF: An Accurate and Lightweight Method for Apple Detection in Real-World Complex Orchard Environments by Yangtian Lin, Yujun Xia, Pengcheng Xia, Zhengyang Liu, Haodi Wang, Chengjin Qin, Liang Gong, Chengliang Liu

“…In response to the insufficient recognition performance and poor generalization capacity of existing detection algorithms under unstructured orchard scenarios, we constructed a customized apple image dataset captured under varying illumination conditions and introduced an improved detection architecture, YOLO11-ARAF, derived from YOLO11. …”
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A New Efficient Classifier for Bird Classification Based on Transfer Learning by Lesia Mochurad, Stanislav Svystovych

“…An optimal model architecture was built using the transfer learning approach. …”
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Tracking and Disturbance Suppression of the Radio Telescope Servo System Based on the Equivalent-Input-Disturbance Approach by Lei Yang, Na Wang, Zhiyong Liu, Ning Li

“…The algorithm consists of the equivalent-input-disturbance (EID) approach and the optimal control method. …”
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Deep Reinforcement Learning-Based Attention Decision Network for Agile Earth Observation Satellite Scheduling by Dongning Liu, Guanghui Zhou

“…Moreover, a start-time-shift-based local search is proposed to improve the observation plan generated by the ADN model. …”
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Research on the Application of Artificial Intelligence in Quantitative Investment: Implementation Scenarios, Practical Challenges, and Future Trends by Chen Boshan

“…Second, the research focuses on key AI applications in quantitative investment, including multi-factor model optimization, high-frequency market risk management, multimodal data integration, and algorithmic trading enhancement. …”
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Enhanced YOLO11 for lightweight and accurate drone-based maritime search and rescue object detection. by Beigeng Zhao, Jiawen Zhao, Rui Song, Lizhi Yu, Xia Zhang, Jiren Liu

“…In the lightweight complexity range, the proposed model achieves a relative accuracy improvement of 20.85% to 43.70% compared to these state-of-the-art methods. …”
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Hybridisation of artificial neural network with particle swarm optimisation for water level prediction by Sarah J. Mohammed, Salah L. Zubaidi

“…Data pre-treatment methods are utilised for improving raw data quality and detect the optimal predictors. …”
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A framework for detecting and predicting highway traffic anomalies via multimodal fusion and heterogeneous graph neural networks. by Shaowei Sun, Mingzhou Liu

“…Experimental results demonstrate that the model performs well in various scenarios, showing significant improvement in accuracy and stability over existing models like AGC-LSTM and AttentionDeepST. …”
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A data-driven state identification method for intelligent control of the joint station export system by Guangli Xu, Yifu Wang, Zhihao Zhou, Yifeng Lu, Liangxue Cai

“…In this paper, a combination of Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO) is proposed to optimize the Backpropagation Neural Network (BP) model (PSO-GWO-BP) and a pressure drop prediction model for the joint station export system is established using PSO-GWO-BP. …”
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Unsignalized intersection vehicle platoon formation scheduling method based on mixed traffic by Junfeng Jiang, Yikang Rui, Bin Ran

“…In deciding the passing order, we propose the Mixed Platoon Scheduling Model (MPSM) to improve the traffic safety and efficiency of unsignalized intersections in mixed traffic environments and to obtain the optimal vehicle passing order without collisions. …”
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Hybrid Recurrent Neural Network and Decision Tree Scheduling for Energy-Efficient Resource Allocation in Cloud Computing by Sefati Seyed Salar, Vulpe Alexandru, Popovici Eduard, Fratu Octavian

“…Efficient resource allocation in cloud computing is critical for optimizing execution time, minimizing delays, and improving system reliability. …”
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A dual input dual spliced network with data augmentation for robust modulation recognition in communication countermeasures by Wang Guan

“…Feature extraction in the transform domain of the dataset can, to a certain extent, improve the modulation recognition accuracy. However, it significantly prolongs the algorithm’s running time. …”
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Real-Time Common Rust Maize Leaf Disease Severity Identification and Pesticide Dose Recommendation Using Deep Neural Network by Zemzem Mohammed Megersa, Abebe Belay Adege, Faizur Rashid

“…The optimal model recognizes CRMD and classifies it according to scientifically established severity levels. …”
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Balancing Predictive Performance and Interpretability in Machine Learning: A Scoring System and an Empirical Study in Traffic Prediction by Fabian Obster, Monica I. Ciolacu, Andreas Humpe

“…As Machine Learning algorithms become increasingly embedded in decision-making processes, particularly for traffic management and other high-level commitment applications, concerns regarding the transparency and trustworthiness of complex ‘black-box’ models have grown. …”
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Day-Ahead Scheduling of IES Containing Solar Thermal Power Generation Based on CNN-MI-BILSTM Considering Source-Load Uncertainty by Kun Ding, Yalu Sun, Boyang Chen, Jing Chen, Lixia Sun, Yingjun Wu, Yusheng Xia

“…The validity of the proposed model is verified by algorithm prediction simulation and day-ahead scheduling experiments under different configurations.…”
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Adaptive variable channel heat dissipation control of ground control station under various work modes by Dexin Wang, Jiali Tao, Jin Lei, Xinyan Qin, Yanqi Wang, Jie Song, Tianming Feng, Yujie Zeng

“…This research introduces an Adaptive Variable Channel Control (AVCC) cooling approach using the Deep Reinforcement Learning Soft Actor-Critic (SAC) algorithm. The primary contributions of this paper include: (1) the design of a distributed cooling module featuring multiple cooling fans, which enables a variable channel cooling structure; (2) the development of a multi-module temperature control platform that simulates the heat generation conditions of each module under six work modes, providing a training environment for the cooling control algorithm; (3) the formulation of a model-free control method based on the SAC algorithm, AVCC, to optimize the cooling efficiency and endurance of the GCS. …”
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Maximum power point tracking control for mechanical rectification wave energy converter by Jianan Xu, Yanpeng Zhao, Yong Zhan, Yansong Yang

“…In order to improve the power generation efficiency, the maximum power point tracking control algorithm is designed based on the admittance differentiation method. …”
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A survey on resource allocation in backscatter communication networks by Yongjun XU, Haoke YANG, Yinghui YE, Qianbin CHEN, Guangyue LU

“…With the development of Internet of things (IoT) technology, wireless networks have the characteristics of massive user access, high power consumption, and high capacity requirements.In order to meet the transmission requirements and reduce energy consumption, backscatter communication technology was considered to be one of the most effective solutions to the above problems.In the fact of complex network scenarios, the improvement of spectrum efficiency, system capacity, and energy management has become an urgent problem of resource allocation areas in backscatter communications.For this problem, resource allocation algorithms in backscatter communications were surveyed.Firstly, the basic concept and different network architectures of backscatter communication were introduced.Then, resource allocation algorithms in backscatter communication networks were analyzed according to different network types, optimization objectives, and the number of antennas.Finally, the challenges and future research trends of resource allocation problems in backscatter communication networks were prospected.…”
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Research on multi-attribute controller for virtual data domain based on software definition network by Jianmin Wang, Bo Zhang, Tongrang Fan, Zijian Fu, Wenbin Zhao

“…Based on software definition network, this article proposes a framework for building virtual data domain, which establishes a multi-attribute decision model by network nodes for optimizing the deployment of control layer, so as to realize large-scale deployment. …”
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