Design of a SUMO-Based Simulator for Optimal Location of Emergency Vehicles in the Emergency Medical Systems by Antoni Mínguez, Volkan Tozan, Monica El-Assaad, Silvia Solà-Muñoz, Youcef Azeli, Luis J. de la Cruz Llopis, Xavier Jiménez-Fàbrega, Carles Galup, Raimon Dalmau, Mónica Aguilar Igartua

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Research on the Model of Industrial Interconnection Intelligent Manufacturing Supply and Demand Network and Its Robustness by Jianjia He, Tianyuan Zheng

“…The industrial interconnection intelligent manufacturing supply and demand network is the carrier for the cooperation of related enterprises, and research on its evolution helps to optimize the cooperation between enterprises. …”
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Qualitative enhancement in machining efficiency of sncm8 alloy through hybrid ann-taguchi optimization approach by Sharad Chaudhari, Neeraj Sunheriya, Jayant Giri, Mohammad Kanan, Rajkumar Chadge, T. Sathish

“…The present study optimizes hard-to-machine materials using hybrid modeling involving artificial neural networks (ANN) and the Taguchi method. …”
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Effects and Risks of Distance Learning in Higher Education by Yu. M. Tsygalov

“…However, the assessment of such training by the population and students in publications and in social networks was predominantly negative and showed that the number of emerging problems exceeds the possible benefits of the new educational technology. …”
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Sentiment Analysis of Tweets on Prakerja Card using Convolutional Neural Network and Naive Bayes by Pahlevi Wahyu Hardjita, Nurochman, Rahmat Hidayat

“…The best accuracy result in K-fold with five classes is 85.4% on the CNN model with a learning rate optimization of 0.00158. While the average accuracy on NBC only reached 75.3%…”
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Rapid Prediction of Multi-physics Coupling in Heat Pipe ReactorBased on Neural Network by ZHANG Junda, LIU Xiaojing, XIONG Jinbiao, CHAI Xiang, ZHANG Tengfei

“…Coupled with their inherent flexibility and modest training data requirements, and the capacity for targeted model optimization, it is advocated that neural network-based rapid prediction serves as a preferred methodology for addressing challenges such as core optimization in scenarios that demand large-scale computations. …”

Centralized and Decentralized Signal Control with Short-Term Origin-Destination Demand for Network Traffic by Can Zhang, Tony Z. Qiu, Amy Kim

“…Considering each intersection turning movement as a virtual link, we assign traffic demand to paths based on minimal instantaneous travel time. Then, the optimal control is formulated using a G/G/n/FIFO open queueing network model (QNM). …”
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Improved Quantile Convolutional and Recurrent Neural Networks for Electric Vehicle Battery Temperature Prediction by Andreas M. Billert, Runyao Yu, Stefan Erschen, Michael Frey, Frank Gauterin

“…The battery thermal management of electric vehicles can be improved using neural networks predicting quantile sequences of the battery temperature. …”
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Energy-Efficient User Association Strategy for Hyperdense Heterogeneous Networking in the Fifth Generation Systems by Lei Li, Hao Jin, Zhipeng Yan, Changqing Yang, Yong Wu

“…Redesigning user association strategies to improve energy efficiency (EE) has been viewed as one of the promising shifting paradigms for the fifth generation (5G) cellular networks. In this paper, we investigate how to optimize users’ association to enhance EE for hyper dense heterogeneous networking in the 5G cellular networks, where the low-power node (LPN) much outnumbers the high-power node (HPN). …”
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A Rotation Target Detection Network Based on Multi-Kernel Interaction and Hierarchical Expansion by Qi Wang, Guanghu Xu, Donglin Jing

“…To address this issue, this paper proposes a Rotation Target Detection Network based on Multi-kernel Interaction and Hierarchical Expansion (MIHE-Net) as a systematic solution. …”
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Research on Self-Diagnosis and Self-Healing Technologies for Intelligent Fiber Optic Sensing Networks by Ruiqi Zhang, Liang Fan, Dongzhu Lu

“…Furthermore, this study also proposes a robustness evaluation model based on sensor perception ability and coverage uniformity indicators, providing a theoretical basis for the self-healing capability of fiber optic sensing networks. This model aids in network topology optimization and fault recovery strategy design, contributing to the improvement of the stability and reliability of fiber optic sensing networks in practical applications.…”
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Wireless sensor network positioning technology based on improved sampling box and fuzzy reasoning by Ningyun Dan, Lun Zhao, Wenjin Pan, Yan Cai

“…Abstract As the wireless sensor network technology develops, precise positioning has become the key to achieving effective monitoring and data collection. …”
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BPDM-GCN: Backup Path Design Method Based on Graph Convolutional Neural Network by Wanwei Huang, Huicong Yu, Yingying Li, Xi He, Rui Chen

“…It uses graph convolutional networks to detect changes in network topology, aiming to optimize data transmission delay and bandwidth occupancy within the network topology. …”
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MFA-SCDNet: A Semantic Change Detection Network for Visible and Infrared Image Pairs by Xingyu Li, Jiulu Gong, Jianxiong Wen, Zepeng Wang

“…The proposed architecture operates through three principal technical components: An infrared feature enhancement module that transforms infrared inputs into three-channel representations through spectral domain adaptation, enhancing the network’s perception of both high-frequency and low-frequency information in images; an encoder–decoder structure that simultaneously extracts modality-specific features and common features through adversarial learning; and a synergistic information fusion mechanism that integrates semantic recognition with change detection through multi-task optimization. …”
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RMIS-Net: a fast medical image segmentation network based on multilayer perceptron by Binbin Zhang, Guoliang Xu, Yiying Xing, Nanjie Li, Deguang Li

“…This architecture achieves significant parameter reduction while enhancing local feature representation through optimized shift operations. The network incorporates layer normalization and dropout regularization to ensure training stability, complemented by Gaussian error linear unit (GELU) activation functions for improved non-linear modeling. …”
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Multi-Class Intrusion Detection in Internet of Vehicles: Optimizing Machine Learning Models on Imbalanced Data by Ágata Palma, Mário Antunes, Jorge Bernardino, Ana Alves

“…Using hyperparameter optimization with Optuna, we achieved significant improvements in detection accuracy and robustness. …”
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Communication optimization method of digital-analog hybrid simulation system based on min-cut partition by Li Yiyuan, Mu Qing, Xue Wei

“…The algorithm is based on the min-cut partition and effectively solves the optimal mapping of sub-networks of unequal sizes on heterogeneous cluster systems. …”
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Trust-based energy-efficient routing protocol for Internet of things–based sensor networks by Muhammad Ilyas, Zahid Ullah, Fakhri Alam Khan, Muhammad Hasanain Chaudary, Muhammad Sheraz Arshed Malik, Zafar Zaheer, Hamood Ur Rehman Durrani

“…It outperforms most of its counterpart protocols such as fuzzy logic–based unequal clustering and ant colony optimization–based routing hybrid, Artificial Bee Colony-SD, enhanced three-layer hybrid clustering mechanism and energy aware multi-hop routing in terms of network lifetime, network throughput, average energy consumption and packet latency.…”
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STNet: Prediction of Underwater Sound Speed Profiles with an Advanced Semi-Transformer Neural Network by Wei Huang, Junpeng Lu, Jiajun Lu, Yanan Wu, Hao Zhang, Tianhe Xu

“…The proposed network architecture incorporates an optimized self-attention mechanism to effectively capture long-range temporal dependencies within historical sound velocity time-series data, facilitating an accurate estimation of current SSPs or prediction of future SSPs. …”
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A joint optimization method of multi backhaul link selection and power allocation in 6G by Qingyang LI, Xueting LI, Xiaorong ZHU

“…Aiming at the problem of limited single backhaul link capability of base stations in hotspot areas of the 6G system, a joint optimization method was proposed for multi-backhaul link selection and power allocation in an elastic coverage system, so that the data packets can select the appropriate backhaul link and transmission power according to their service characteristics and link conditions.Firstly, the transmission delay of data packets on the small cell sub-queue was analyzed by using queuing theory.Then, the optimization objective was modeled with the maximum delay tolerance elasticity value.Finally, the optimization problem were solved by the Hungarian algorithm and the Lagrangian duality and gradient descent method.The simulation results show that, compared with the traditional algorithm, the algorithm proposed reduces the average delay of URLLC (ultra-reliable and low-latency communication) service data packets and eMBB (enhanced mobile broadband) service data packets by 17% and 14% respectively, and effectively improves the network transmission rate.…”
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