Prediction of Chemical Gas Emissions Based on Ecological Environment by Guobin Chen, Shijin Li

“…With the serious pollution of the ecological environment, there are a large number of harmful gases in the chemical gases emitted by the industry. Relevant intelligent chemical algorithms control the emission of chemical gases, which can effectively reduce emissions and predict emissions more accurately. …”
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Deep Reinforcement Learning in Multi-UAV Air Combat Maneuver Decision-Making: A Review of Key Techniques in Practice and Future Prospects by Fang Siyu, Zhang Zhenhua, Niu Jinglong, Bian Jiang, Xu Changyi, Wu Yuhu

“…Aimed at providing practical optimization suggestions or basic entry-level guidance for researchers in this field, this paper focuses on the key technologies involved in multi-UAV air combat from a practical perspective, including improvements in deep reinforcement learning algorithms, the design of efficient training methods, and the construction of multi-UAV combat environments. …”
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Can Knowledge Distillation Enable Seismic Interpolation, Super-Resolution, and Denoising Simultaneously? by Benwen Zhang, Linrong Wang

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Quantum Conformal Prediction for Reliable Uncertainty Quantification in Quantum Machine Learning by Sangwoo Park, Osvaldo Simeone

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A Real-Time Signal Measurement System Using FPGA-Based Deep Learning Accelerators and Microwave Photonic by Longlong Zhang, Tong Zhou, Jie Yang, Yin Li, Zhiwen Zhang, Xiang Hu, Yuanxi Peng

“…To address this, this paper develops two accelerators, as the core of the signal measurement system, for intelligent signal processing. Firstly, by introducing the idea of automated framework, we propose a simplest deep neural network (DNN)-based hardware structure, which automatically maps algorithms to hardware modules, supports configurable parameters, and has the advantage of low latency, with an average inference time of only 3.5 μs. …”
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Overcoming the Barriers That Obscure the Interlinking and Analysis of Clinical Data Through Harmonization and Incremental Learning by Vasileios C. Pezoulas, Konstantina D. Kourou, Fanis Kalatzis, Themis P. Exarchos, Evi Zampeli, Saviana Gandolfo, Andreas Goules, Chiara Baldini, Fotini Skopouli, Salvatore De Vita, Athanasios G. Tzioufas, Dimitrios I. Fotiadis

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Hybrid ACO Routing Protocol for Mobile Ad Hoc Networks by D. Rupérez Cañas, A. L. Sandoval Orozco, L. J. García Villalba, P.-S. Hong

“…Specifically we design a novel routing algorithm based on Ant Colony Optimization (ACO) which uses the concepts of Swarm Intelligence and analyzes the behavior of ants at the time of obtaining the food. …”
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An efficient approach towards index structures for skyline queries by Huaiguang Song, Zhongbo Wu, Binglei Guo, Zhao Wu, Min Wang

“…This query represents a multi-objective optimization approach that is used extensively in various areas such as data analysis, decision support, and intelligent recommendation systems. …”
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Research on Behavior Recognition and Online Monitoring System for Liaoning Cashmere Goats Based on Deep Learning by Geng Chen, Zhiyu Yuan, Xinhui Luo, Jinxin Liang, Chunxin Wang

“…This study introduces detection algorithms and develops the Liaoning Cashmere Goat Online Behavior Detection System, offering an effective solution for intelligent goat management.…”
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Research on adversarial attacks and defense performance of image classification models for automated driving systems by TANG Jun, HUANG Wenjing, LI Shuang, WU Zili

“…Then, sensitivity analyses were carried out across different regions and examples to identify attack mechanisms using three adversarial interpretation algorithms: LRP, Grad-CAM, and LIME. Based on these analysis results, optimization algorithms such as swarm intelligence defense and adversarial training were adopted to verify the classification performance of the model following adversarial training. …”
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Research on equipment layout of multi-layer circular manufacturing cell based on NSGA III. by Yanlin Zhao

“…With the continuous advancement of global intelligent manufacturing, MCMC has emerged as a viable solution, with several smart factories already implementing this model. …”
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A High-Feasibility Real-Time Trajectory-Planning Method for Parafoils Based on a Flexible Dynamic Model by Jiaming Yu, Hao Sun, Qinglin Sun, Mingwei Sun, Zengqiang Chen

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Development and Practice of Cloud Collaborative Platform for Downhole Measurement Tools by Che Yang, Yuan Guangjie, Qian Hongyu, Du Weiqiang, Wang Chenlong, Ding Jiping

“…In the paper， based on the remote operation requirements of coreless magnetic steering tool， a platform architecture of five modules， including simulation rehearsal， virtual training， remote operation， smart tool and intelligent decision， was designed in detail， achieving a whole process digitization from predrilling risk assessment and in-drilling acquisition and processing to post-drilling feedback and optimization， and a visual interface was developed. …”
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Solar Agro Savior: Smart Agricultural Monitoring Using Drones and Deep Learning Techniques by Manu Mundappat Ramachandran, Bisni Fahad Mon, Mohammad Hayajneh, Najah Abu Ali, Elarbi Badidi

“…The machine learning algorithm, particularly recurrent neural networks, which is a pioneer with agriculture and pest control, is incorporated for intelligent monitoring systems. …”
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A Task Offloading and Resource Allocation Strategy Based on Multi-Agent Reinforcement Learning in Mobile Edge Computing by Guiwen Jiang, Rongxi Huang, Zhiming Bao, Gaocai Wang

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Bioinformatic Analysis of Complex In Vitro Fertilization Data and Predictive Model Design Based on Machine Learning: The Age Paradox in Reproductive Health by Myrto A. Lantzi, Eleni Papakonstantinou, Dimitrios Vlachakis

“…This study encompasses statistical analysis techniques and artificial intelligence algorithms for the correlation of variables, such as patient characteristics, the history of pregnancies, and the clinical and embryological parameters. …”
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Stability Analysis of Neural Networks-Based System Identification by Talel Korkobi, Mohamed Djemel, Mohamed Chtourou

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Electric Vehicle Routing with Time Windows and Charging Stations from the Perspective of Customer Satisfaction by Yasin Ünal, İnci Sarıçiçek, Sinem Bozkurt Keser, Ahmet Yazıcı

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Recent advances in machine learning applications for MXene materials: Design, synthesis, characterization, and commercialization for energy and environmental applications by Sodiq Abiodun Kareem, Makinde Akindeji Ibrahim, Justus Uchenna Anaele, Olajesu Favor Olanrewaju, Emmanuel Omosegunfunmi Aikulola, Michael Oluwatosin Bodunrin

“…Techniques such as genetic algorithms, evolutionary algorithms, and Bayesian optimization accelerate the discovery of novel MXene phases tailored for specific uses. …”
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Electric Vehicle Charging Load Forecasting Based on K-Means++-GRU-KSVR by Renxue Shang, Yongjun Ma

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