KT-Deblur: Kolmogorov–Arnold and Transformer Networks for Remote Sensing Image Deblurring by Baoyu Zhu, Zekun Li, Qunbo Lv, Zheng Tan, Kai Zhang

“…Aiming to address the fundamental limitation of fixed activation functions that constrain network expressiveness in existing deep deblurring models, in this pioneering study, we introduced Kolmogorov–Arnold Networks (KANs) into the field of full-color/RGB image deblurring, proposing the Kolmogorov–Arnold and Transformer Network (KT-Deblur) framework based on dynamically learnable activation functions. …”
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Application of Ensemble Learning and VISSIM in Intersection Traffic Flow Prediction and Signal Timing Optimization by Yutong Rou, Chao Liang, Zhizhan Lu

“…By integrating the predictions with the SARSA-A2C algorithm, a hybrid strategy for predictive signal timing optimization is implemented. Using four consecutive intersections on Shanghai’s West Yan’an Road as a case study, the results, validated by model and network performance metrics, demonstrate the efficacy of the hybrid strategy: a 20.0% decrease in average stops per vehicle, an 11.7% reduction in total delay, a 15.8% decrease in total stop delay, and a 25.0% reduction in average vehicle delay. …”
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DEVELOPMENT OF NON-DESTRUCTIVE ROBOT FOR EGGPLANTS (SOLANUM MELONGENA) PEST DETECTION AND CLASSIFICATION by Mark Jayson Y. Sutayco, Eidref Simon Dela Cruz, Harold Aranza, Gian Fernan Collado, Kyle Benedict Lui

“…Effective pest monitoring is essential for farmers to detect potential crop damage, minimize the use of pesticides and insecticides, and optimize harvest yields. Deep learning techniques, such as convolutional neural networks, enable accurate pest identification and decision-making based on insect images. …”
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Real-time traffic enhancement scheduling for train communication networks based on TSN by Deqiang He, Zeqian Chen, Daliang Sun, Zhenzhen Jin, Yanjun Chen, Rui Ma, Chen Liang

“…Experimental results show that compared with the traditional constraint model, the schedulability of the model with an adaptive switch queue selection mechanism increases by 33.0%, and the maximum end-to-end delay and network jitter decrease by 19.1% and 18.6% on average respectively. …”
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Intelligent recognition of tobacco leaves states during curing with deep neural network by Qiang Xu, Yanling Zhang, Aiguo Wang, Guangqing Chen, Xianjie Cai, Shuoye Zhou, Junying Li, Baofeng Jin, Ding Yan, Jiajie Huang, Zuxiao Chen, Heng Zhang, Jianwei Wang, Weimin Guo, Jianjun Liu

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Investigation of an Optimized Linear Regression Model with Nonlinear Error Compensation for Tool Wear Prediction by Lihua Shen, Baorui Du, He Fan, Hailong Yang

“…Compared to traditional random forest and neural network models, the MSE and MAE show average reductions of 32.3% and 25.3%. …”
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Territorial Space Optimization Method Based on Multi-Objective Genetic Algorithm and FLUS Model by Lin Ge

“…The difference between the predicted and actual future spatial population values using the proposed algorithm was less than 2%, which was 56.5% lower than the other two prediction algorithms on average. The proposed land simulation model reached the highest accuracy at 100 iterations with an average fitness of <inline-formula> <tex-math notation="LaTeX">$2.4\times 10 ^{11}$ </tex-math></inline-formula>, which was 13% and 27% higher than the other two traditional neural network algorithms, respectively. …”
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Evaluating End-to-End Delay in Road-Based Routing Protocols for VANETs with Snake Optimization by Hanadi Hassan karim Al-Maliki, Hamid AL-Asadi

“… Vehicular Ad hoc Networks (VANETs) require efficient routing protocols due to their dynamic network  topologies and high mobility. …”
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A Lightweight Pavement Defect Detection Algorithm Integrating Perception Enhancement and Feature Optimization by Xiang Zhang, Xiaopeng Wang, Zhuorang Yang

“…Secondly, the dynamic upsampling module DySample is introduced into the efficient feature pyramid, constructing a new feature fusion pyramid (Generalized Dynamic Sampling Feature Pyramid Network, GDSFPN) to optimize the multi-scale feature fusion effect. …”
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End-to-end feature fusion for jointly optimized speech enhancement and automatic speech recognition by Mohamed Medani, Nasir Saleem, Fethi Fkih, Manal Abdullah Alohali, Hela Elmannai, Sami Bourouis

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Deep Learning Strategies for Intraday Optimal Carbon Options Trading with Price Impact Considerations by Qianhui Lai, Qiang Yang

“…This paper solves the optimal trading problem of carbon options with a deep learning approach. …”
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Robot Trajectory Tracking Control Based on Neural Networks and Sliding Mode Control by Yuyun Liang

“…Compared with the existing method, the trajectory deviation of the research method was smaller than that of the reference trajectory, and the robot motion was more stable. For average errors (instantaneous optimal control method), the average errors of lateral displacement, longitudinal displacement, and displacement offset angle of the comparison method were 0.99cm, 0.62cm, and 0.0211rad, respectively. …”
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Optimizing colorectal polyp detection and localization: Impact of RGB color adjustment on CNN performance by Jirakorn Jamrasnarodom, Pharuj Rajborirug, Pises Pisespongsa, Kitsuchart Pasupa

“…Using datasets from Harvard Dataverse for training and internal validation, and LDPolypVideo-Benchmark for external validation, RGB color adjustments were applied, and YOLOv8s was used to develop models. Bayesian optimization identified the best RGB adjustments, with performance assessed using mean average precision (mAP) and F1-scores. …”
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An optimal weighting-based hybrid classifier for Children's congenital heart diseases signal processing by Morteza Ebrahimpour, Mehdi Khashei

“…Notably, the proposed method also outperforms CNN-LSTM-SVM combinations that use conventional weighting strategies such as Simple Average (SA), Majority Voting (MV), and metaheuristic optimization algorithms. …”
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Research of neural network algorithms for recognizing railway infrastructure objects in video images by E.V. Medvedeva, A.A. Perevoshchikova

“…The experimental studies conducted are aimed at increasing the efficiency of algorithms for object detection and segmentation through the use of data augmentation methods and additional preprocessing, as well as selecting an architecture and optimal network hyperparameters. The detection algorithm works in real time, achieving an average accuracy of 64% for 11 object classes according to the mAP metric. …”
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Hybrid Optimization Method for Social Internet of Things Service Provision Based on Community Detection by Bahar Allakaram Tawfeeq, Amir Masoud Rahmani, Abbas Koochari, Nima Jafari Navimipour

“…IGBSA‐CD more rapidly produces solutions that are near‐optimal with average success rates of over 96.3% for different sample sizes. …”
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Comparative analysis of FACT devices for optimal improvement of power quality in unbalanced distribution systems by Ahmed M. Elkholy, Dmitry I. Panfilov, Ahmed E. ELGebaly

“…The performance of the IEEE-13 bus imbalanced distribution model is investigated using the Newton-Raphson method. To improve network asymmetry, an optimization analysis is carried out to ascertain how each proposed device will work. …”
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Optimal Parking Slots Reservation and Allocation Problem for Periodic Parking Platforms with Preference Constraints by Xianmin Song, Tianshu Zhan, Haitao Li, Bo Liu, Yunxiang Zhang, Xin Liu

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Distributed Downlink Power Control by Message-Passing for Very Large-Scale Networks by Illsoo Sohn

“…Downlink power control is revisited by assuming very large-scale networks. In very large-scale networks, conventional centralized power control schemes quickly become impractical owing to the huge computational burden and limited backhaul capacity. …”
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Performance Analysis of the Sleep Mode in WiMAX 2 Networks with Multimedia Application by Shunfu Jin, Wuyi Yue, Xiaofei Zhang

“…We also develop a cost function to determine the optimal length of the sleep cycle in order to maximize the energy saving ratio while satisfying the Quality of Service (QoS) constraint on the average response time of data packets. …”
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