Decentralized Multi-Robot Navigation Based on Deep Reinforcement Learning and Trajectory Optimization by Yifei Bi, Jianing Luo, Jiwei Zhu, Junxiu Liu, Wei Li

“…Additionally, it introduces safety constraints through an artificial potential field (APF) to optimize these trajectories. Additionally, a constrained nonlinear optimization method further refines the APF-adjusted paths, resulting in the development of the GNN-RL-APF-Lagrangian algorithm. …”
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Multi-objective production scheduling optimization strategy based on fuzzy mathematics theory. by Heshuai Shen

“…Multi-objective production scheduling faces the problems of inter-objective conflicts, many uncertainty factors and the difficulty of traditional optimization algorithms to deal with complexity and ambiguity, and there is an urgent need to introduce the theory of fuzzy mathematics in order to improve the scheduling efficiency and optimization effect. …”
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Design Improvement of Permanent Magnet Motor Using Single- and Multi-Objective Approaches by Cvetkovski Goga, Petkovska Lidija

“…In this case, optimising the efficiency of the motor, reducing cogging torque, and minimising the total weight of active materials are defined as possible objective functions. Genetic algorithms are nature based algorithms that are commonly used in engineering to find optimal solutions to complex problems, including those with multiple objectives. …”
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Resource optimization for UAV relay networks based on physical-layer network coding by Junyi YANG, Bo LI, Qinyu ZHANG

“…To solve the problem of low resource utilization of the traditional two-way communication network with unmanned aerial vehicle (UAV) as relays, a resource optimization algorithm based on physical-layer network coding was proposed.Considering the transmission power constraints of the UAV relay communication network, the maximum speed constraints of the UAV and the synchronization requirements of the physical-layer network coding, a resource allocation model for joint optimization of transmission power and UAV trajectory design was formulated to minimize the system outage probability.By decoupling the original non-convex problem into two sub-problems, an iterative algorithm was proposed to realize the joint implementation of optimal trajectory design and optimal system power distribution based on the Karush-Kuhn-Tucker (KKT) conditions, Lagrangian duality method and subgradient method.Simulation results show that the proposed algorithm can significantly improve the system performance and reduce the possibility of communication interruption.…”
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Improving Efficiency of Rolling Mill Stand Electric Drives Through Load Alignment by Stanislav S. Voronin, Andrey A. Radionov, Alexander S. Karandaev, Roman A. Lisovsky, Boris M. Loginov, Mark A. Zinchenko, Vadim R. Khramshin, Ivan N. Erdakov

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Artificial intelligence for smart irrigation: Reducing water consumption and improving agricultural output by Arlanova A. A., Hojamkuliyeva B. A., Babanazarov N. Sh., Arlanov M. S.

“…Existing approaches to using artificial intelligence in agricultural technologies for predicting water needs and regulating irrigation are examined. A mathematical model based on machine learning algorithms is developed to predict the optimal water volume required for irrigation of agricultural crops. …”
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Prediction for Coastal Wind Speed Based on Improved Variational Mode Decomposition and Recurrent Neural Network by Muyuan Du, Zhimeng Zhang, Chunning Ji

“…This study proposes a systematic framework, termed VMD-RUN-Seq2Seq-Attention, for noise reduction, outlier detection, and wind speed prediction by integrating Variational Mode Decomposition (VMD), the Runge–Kutta optimization algorithm (RUN), and a Sequence-to-Sequence model with an Attention mechanism (Seq2Seq-Attention). …”
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Detection method of small size defects on pipeline weld surface based on improved YOLOv7. by Xiangqian Xu, Wenting Hou, Xing Li

“…The experimental results show that the defect detection mAP@0.5 based on the improved YOLOv7 algorithm can reach 72.2%, which is 11% higher than that of YOLOv7, and the model calculation amount and parameter amount are reduced by 75.6% and 60.3%, respectively. …”
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Research on optimization of vector control of an asynchronous motor using the analytical control system by A. N. Tsvetkov, Ngok Shi Doan, D. A. Yaroslavsky

“…The control algorithm based on determining the optimal value of the magnetic flux in the coordinates of the d - q axis to achieve low power losses, taking into account losses in the iron core and low magnetic saturations, helps to improve the efficiency of inverter control.RESULTS. …”
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Adaptive resource optimization mechanism for blockchain sharding in digital twin edge network by Li JIANG, Shengli XIE, Hui TIAN

“…To address the security and privacy issues for data sharing in digital twin edge networks, a new distributed and secure data sharing mechanism was developed by leveraging blockchain sharding.Considering dynamic and time varying features in digital twin edge networks and mapping errors of physic networks, an adaptive resource allocation model was formulated which jointly optimized cluster head selection, local base station (BS) consensus access selection, spectrum and computation consensus resources allocation, in order to maximize transactional throughput for the blockchain sharding.Moreover, a digital twin edge networks empowered two-layered proximal policy optimization (PPO) algorithm was designed to obtain the optimal solutions.Numerical results illustrate that the proposed algorithm can effectively improve the transactional throughput for the blockchain sharding.Meanwhile, it can well adapt to the mapping errors.…”
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Optimizing Fairness and Spectral Efficiency With Shapley-Based User Prioritization in Semantic Communication by Moirangthem Tiken Singh, Adnan Arif, Rabinder Kumar Prasad, Bikramjit Choudhury, Chandan Kalita, Sikdar Md. S. Askari

“…The Shapley-based approach outperforms established methods, including the Hungarian algorithm, reinforcement learning algorithms like Deep Q-Network (DQN) and Proximal Policy Optimization (PPO), as well as conventional 4G and 5G resource allocation strategies. …”
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A hybrid Bayesian network-based deep learning approach combining climatic and reliability factors to forecast electric vehicle charging capacity by David Chunhu Li

“…This architecture uses extensive transaction data and climate analysis to build a detailed model of EV charging pile reliability. Additionally, two algorithms are designed to assess the usage and reliability of charging stations. …”
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INNOVATIVE MECHANISMS FOR IMPLEMENTING STATE ECONOMIC POLICY FOR POST-WAR RECONSTRUCTION OF UKRAINE: QUANTUM TRANSFORMATIONS AS A DRIVER OF DEVELOPMENT by Oleksiy Shkuratov, Liudmila Antonova, Roman Dzyuba

“…The quantum transformation of Ukraine's economy in the conditions of post-war recovery can become an important component of the state investment policy, which will stimulate innovative development and increase the country's competitiveness in the international arena. …”
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Disturbance Observer-Based Optimal Active Suspension Control for Vehicle-Trailer Systems by Yonghwan Jeong

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Point Data Registration With the Multi-Object, Cardinalized Optimal Linear Assignment Metric by Pablo A. Barrios, Vicente Guzman, Martin D. Adams, Claudio A. Perez

“…The Iterative Closest Point (ICP) algorithm and its variants were initially used to solve such problems and since then, various global methods have been proposed to improve registration when data outliers exist. …”
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Optimal relay selection for full duplex SWIPT-NOMA systems with maximal throughput by Taoshen LI, Anni SHI, Zhe WANG, Lu HE

“…To improve the performance of 5G communication system, a full duplex Internet of things (IoT) relay system model was built by introducing the non-orthogonal multi-access (NOMA) technology.For the relay system of simultaneous wireless information and power transfer (SWIPT), it was considered that the relay node can harvest the energy of the source node, the self-interference signal of the loop channel and the free energy access point (EAP), and NOMA technology was used to forward the source node signal and its own signal to different destination nodes.Based on the model, a power distribution collaboration SWIPT relay selection strategy was proposed to optimize system throughput.Firstly, the problem model was established based on the constraints of communication quality of service and transmission power of source nodes.And then, the original nonlinear 0-1 programming problem was converted into a pair of coupling optimization problem by mathematical transformation, and the optimal relay selection of outer optimization problem was solved based on the optimal solution of the internal optimization problem.Finally, an optimal relay selection algorithm was used to maximize system throughput.Simulation results show that the proposed model and strategy are superior to the traditional maximum-minimum relay selection schemes in terms of throughput gain, and the consideration of EAP can significantly improve the interrupt performance.…”
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Optimal relay selection for full duplex SWIPT-NOMA systems with maximal throughput by Taoshen LI, Anni SHI, Zhe WANG, Lu HE

“…To improve the performance of 5G communication system, a full duplex Internet of things (IoT) relay system model was built by introducing the non-orthogonal multi-access (NOMA) technology.For the relay system of simultaneous wireless information and power transfer (SWIPT), it was considered that the relay node can harvest the energy of the source node, the self-interference signal of the loop channel and the free energy access point (EAP), and NOMA technology was used to forward the source node signal and its own signal to different destination nodes.Based on the model, a power distribution collaboration SWIPT relay selection strategy was proposed to optimize system throughput.Firstly, the problem model was established based on the constraints of communication quality of service and transmission power of source nodes.And then, the original nonlinear 0-1 programming problem was converted into a pair of coupling optimization problem by mathematical transformation, and the optimal relay selection of outer optimization problem was solved based on the optimal solution of the internal optimization problem.Finally, an optimal relay selection algorithm was used to maximize system throughput.Simulation results show that the proposed model and strategy are superior to the traditional maximum-minimum relay selection schemes in terms of throughput gain, and the consideration of EAP can significantly improve the interrupt performance.…”
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Improving meningitis surveillance and diagnosis with machine learning: Insights from São Paulo. by Audêncio Victor, Diego Augusto Medeiros Santos, Eduardo Koerich Nery, Danilo Pereira Mori, Pamella Cristina de Carvalho Lucas, Denise Cammarota, Guillermo Leonardo Florez Montero, Fabiano Novaes Barcellos Filho, Ana Lúcia Frugis Yu, Telma Regina Marques Pinto Carvalhanas

“…These techniques can be integrated into public health protocols to improve meningitis outbreak responses and optimize patient treatment.…”
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Stowage Plan Based Slot Optimal Allocation in Rail-Water Container Terminal by Yanjing Li, Xiaoning Zhu, Li Wang, Xi Chen

“…To obtain an efficient and reasonable solution for slot allocation in rail-water container terminals, this paper develops storage optimal allocation model 1 to improve the yard space utilization, which is solved by a heuristic algorithm based on Tabu search. …”
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Hybrid Optimization Machine Learning Framework for Enhancing Trust and Security in Cloud Network by Himani Saini, Gopal Singh, Amrinder Kaur, Sunil Saini, Niyaz Ahmad Wani, Vikram Chopra, Zahid Akhtar, Shahid Ahmad Bhat

“…To strengthen trust evaluation, the framework combines an optimized Levenberg algorithm with the Firefly Algorithm. …”
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