An efficient fire detection algorithm based on Mamba space state linear attention by Yuming Li, Yongjie Wang, Xiaorui Shao, Anbo Zheng

“…Instead, it performs dimensionality reduction on input features through adaptive average pooling and utilizes the state update mechanism of the SSM module to significantly enhance feature representation and optimize information flow. Second, to address the limitations of SSM models in local feature modeling, this study incorporates the ConvNeXtV2 module to optimize the backbone network, improving the model’s ability to capture fine-grained local details and thereby strengthening its overall representation capability. …”
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Optimizing Medical IoT Disaster Management with Data Compression by Nunudzai Mrewa, Athirah Mohd Ramly, Angela Amphawan, Tse Kian Neo

“…To tackle this issue, we introduce "Beyond Orion," a novel lossless compression method designed to optimize data compression in IoT systems. The algorithm employs advanced techniques such as Lempel Ziv-Welch and Huffman encoding, while also integrating strategies like pipelining, parallelism, and serialization for greater efficiency and lower resource usage. …”
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Carbon emission forecasting in Zhejiang Province based on LASSO algorithm and grey model by HONG Jingke, DU Wei, SHAO Jin*, LAO Huimin

“…In light of these findings, It is recommended that Zhejiang Province should focus on optimizing its industrial structure, improving energy efficiency, increasing investment in low-carbon research and development, and steadily advancing the goal of "carbon peaking" .…”
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Multivariate machine learning algorithms for energy demand forecasting and load behavior analysis by Farhan Hussain, M. Hasanuzzaman, Nasrudin Abd Rahim

“…This article presents deep learning frameworks for predicting electricity demand in the Western region of Bangladesh, utilizing Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithms. Critical hyperparameters, such as the number of hidden neurons in ANN and the number of input membership functions in ANFIS, are optimized to effectively capture uncertainties in load patterns. …”
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Research on a traffic flow statistical algorithm based on YBOVDT and SAM2 by Yuanyuan Wang, Zheng Ding, Jiange Liu, Kexiao Wu, Md Sharid Kayes Dipu, Tingmei Ma, Yonghao Ma, Haiyan Zhang

“…A comparative analysis with YOLO-v3,YOLO-v5, YOLO-v6,and YOLO-v8 algorithms indicated that, while balancing spatial and temporal resource consumption and accuracy, the proposed algorithm offers higher recognition accuracy and environmental adaptability. …”
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CKRT coagulation risk prediction and nursing feedback model based on intelligent algorithms by Xianrong Xu, Mou Chen, Lvjing Chen, Kaixing Huang, Shiqi Cao, Wenwen Gao, Kang Liu, Buyun Wu, Huijuan Mao

“…Conclusion The intelligent Continuous Kidney Replacement Therapy nursing feedback model improves prediction accuracy while reducing redundant information. …”
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Automated Calibration of SWMM for Improved Stormwater Model Development and Application by Hossein Ahmadi, Durelle Scott, David J. Sample, Mina Shahed Behrouz

“…During multi-objective optimization calibration, the model achieved NSE, PBIAS, and RSR values of 0.73, 17.1, and 0.52, respectively; while the validation period recorded values of 0.86, 13.1, and 0.37, respectively. …”
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Enhancing Camera Source Identification: A Rapid Algorithm with Enhanced Discriminative Power by Zhimao Lai, Lijuan Cheng, Renhai Feng

“…Compared to the traditional brute-force search algorithm (BFSA), our method significantly reduces computational complexity in large-scale databases, optimizing from <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><mi>n</mi><mi>N</mi><mo>)</mo></mrow></semantics></math></inline-formula> to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><mi>n</mi><mo form="prefix">log</mo><mi>N</mi><mo>)</mo></mrow></semantics></math></inline-formula>, where <i>n</i> is the length of the fingerprint, and <i>N</i> is the number of fingerprints in the database. …”
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Social Media Users' Expression, Formation Mechanism, and Coping Strategies for Algorithm Aversion by Yan MOU

“…These insights are invaluable for improving and optimizing algorithms to ensure that they not only meet user expectations, but also enhance their overall experience and satisfaction. …”
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Signal Timing Optimization Model for Intersections in Traffic Incidents by Jiawen Wang, Jiayu Hang, Xizhao Zhou

“…The proposed method is capable of improving the signalized intersection throughput while preventing the congestion from spreading to the upstream intersection.…”
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Optimization of surgical treatment of abdominal hernias in patients with obesity by V. I. Belokonev, V. P. Zakharov, D. B. Grachev, S. Y. Pushkin, Z. V. Kovaleva, D. S. Pushkina

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Marine fish species recognition based on improved YOLOv5s by ZHANG Haifeng, LU Xinchun, FENG Bo, YANG Jin

“…ObjectiveIn order to improve the recognition accuracy of different kinds of marine fish, an improved YOLOv5s marine fish species recognition method was proposed.MethodsK⁃means++algorithm was used to cluster the real frames of marine fish, and more matching anchor frames were obtained with the self built data set. …”
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Control Optimization of Steam Boilers via Reinforcement Learning by Emmanuel Okafor, Maad Alowaifeer

“…Extensive experimental validation confirms the superiority of hybrid controllers, achieving significantly faster settling times, peak overshoot reductions to <inline-formula> <tex-math notation="LaTeX">$(\leq 2\%)$ </tex-math></inline-formula>, and lower error metrics than MRAC alone. While optimized PID serves as a baseline, hybrid controllers consistently achieve faster settling times and improved robustness under most nonlinear operating conditions. …”
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A New Approach to Circulatory System-Based Optimization for the Shape and Sizing Design of Truss Structures by Ibrahim Behram Ugur, Sadik Ozgur Degertekin

“…This paper presents a new approach to the circulatory system-based optimization algorithm called NCSBO. The proposed method incorporates an adaptive parameter-tuning strategy and a refined mutation approach to improve the performance of optimizing the shape and size of truss structures. …”
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Optimization of PID Controllers Using Groupers and Moray Eels Optimization with Dual-Stream Multi-Dependency Graph Neural Networks for Enhanced Dynamic Performance by Vaishali H. Kamble, Manisha Dale, R. B. Dhumale, Aziz Nanthaamornphong

“…Additionally, it minimizes overshoot to 1.5% and reduces the steady-state error to just 0.005 V, demonstrating superior accuracy and efficiency compared to existing methods. These improvements demonstrate the system’s ability to deliver optimal performance while effectively adapting to dynamic environments, showcasing its superiority over existing techniques.…”
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Engine Optimization Model for Accurate Prediction of Friction Model in Marine Dual-Fuel Engine by Mina Tadros

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Machine Learning for Decision Support and Automation in Games: A Study on Vehicle Optimal Path by Gonçalo Penelas, Luís Barbosa, Arsénio Reis, João Barroso, Tiago Pinto

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Nonlinear waveform optimization for wireless power transfer systems by Lina Yuan, Huajun Chen, Maoxue Hu, Jing Gong

“…We develop single-user and multi-user algorithms that maximize the output DC voltage of the weighted and/or minimum moment antennas by optimizing waveform design. …”
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An Automated Framework for Streamlined CFD-Based Design and Optimization of Fixed-Wing UAV Wings by Chris Pliakos, Giorgos Efrem, Dimitrios Terzis, Pericles Panagiotou

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Performance assessment of basalt fibre concrete under freeze-thaw cycles using hybrid long short-term memory models by Qingguo Yang, Honghu Wang, Qigui Yi, Liuyuan Zeng, Rui Xiang, Longfei Guan, Jiawei Cheng, Keling Chen, Yunhao Li

“…The two modified particle swarm optimization algorithms showed notable improvements: AsyLnCPSO performed well on the training set but exhibited limited adaptability to overall data variations, while the GA-HIDMS-PSO excelled in high-dimensional and complex constraint problems, demonstrating the strongest stability with a fitting accuracy of 0.938, significantly improving the prediction accuracy of concrete performance under FTCs. …”
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