Control-Oriented Real-Time Trajectory Planning for Heterogeneous UAV Formations by Weichen Qian, Wenjun Yi, Shusen Yuan, Jun Guan

“…Inspired by Model Predictive Control (MPC), in the trajectory planning stage, the method generates multi-step trajectory points using an improved artificial potential field (APF) method, estimates the actual formation trajectory using the prediction network, and optimizes the trajectory through a multi-objective particle swarm optimization (MOPSO) algorithm after evaluating the planning costs. …”
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Vibration control and noise attenuation strategies via acoustic metamaterial in railway transportation: a state-of-the-art review by Cong Wang, Guifeng Wang, Zhenyu Chen, C. W. Lim, Weiqiu Chen

“…Additionally, integrating optimization algorithms and artificial intelligence (AI) enhances AMM design precision and scalability. …”
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Smart agriculture using IoT for automated irrigation, water and energy efficiency by Subir Gupta, Subrata Chowdhury, Ramya Govindaraj, Kassian T.T. Amesho, Sumarlin Shangdiar, Timoteus Kadhila, Sioni Iikela

“…This study presents an innovative smart agriculture system that integrates Internet of Things (IoT) technologies, predictive algorithms, and automated control mechanisms to optimize irrigation and enhance resource efficiency. …”
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A Global Coverage Path Planning Method for Multi-UAV Maritime Surveillance in Complex Obstacle Environments by Yiyuan Li, Weiyi Chen, Bing Fu, Zhonghong Wu, Lingjun Hao

“…Thirdly, an improved discrete grey wolf optimizer (IDGWO) algorithm integrated with variable neighborhood search (VNS) operations is proposed to perform task assignment for multiple UAVs and achieve workload balancing. …”
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Short-term Wind Power Forecasting Based on BWO‒VMD and TCN‒BiGRU by LU Jing, ZHANG Yanru, WANG Rui

“…Short-term wind power forecasting helps improve grid stability, optimize wind farm power generation plans, and reduce operating costs, enhancing the economic benefits of wind power and supporting the goals of low-carbon development. …”
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SPECIAL CHARACTERISTICS OF AERODYNAMIC PROPERTIES OF UNMANNED AIRCRAFT WITH THE HIGH-ASPECT-RATIO WING by O. Е. Lukyanov, A. V. Ostrovoy, M. A. Mensez Soto, Y. A. Klimov, V. G. Shakhov

“…The technique is based on numerical multidisciplinary mathematical modeling using the discrete vortex method and the topology optimization algorithm based on the variable density body model. …”
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Artificial intelligence and remote patient monitoring in US healthcare market: a literature review by Ayushmaan Dubey, Anuj Tiwari

“…ABSTRACTBackground: Artificial intelligence (AI) enables remote patient monitoring (RPM) which reduces costs by triaging patients to optimize hospitalization and avoid complications. …”
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An integrated AHP-GP-GA approach for public project portfolio selection problem by A.O. Mogbojuri, O.A. Olanrewaju

“…The selection of projects via an effective methodology is rare, as numerous approaches are considered useless due to constraints on the number of projects available and the inability to identify cost-efficient initiatives. The study presents integrated models of the Analytic Hierarchy Process, Goal Programming, and Genetic Algorithm (AHP-GP-GA) by removing the bias of each model for Public PPSP and building a relationship between the developed models.The AHP method was utilized to establish project selection criteria, allocate relative priority values to stakeholders, and calculate the overall weighting of project alternatives. …”
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Energy storage efficiency modeling of high-entropy dielectric capacitors using extreme learning machine and swarm-based hybrid support vector regression computational methods by Yas Al-Hadeethi, Taoreed O. Owolabi, Mouftahou B. Latif, Bahaaudin M. Raffah, Ahmad H. Milyani, Saheed A. Tijani

“…This work employs single hidden layer extreme learning machine (ELM) algorithm and hybrid particle swarm optimization-based support vector regression (PS-SVR) for determining energy storage efficiency of high-entropy ceramics. …”
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To the analysis of methods and mechanisms of predictive modeling of onboard equipment reliability when solving problems of aircraft maintenance workload planning by B. I. Ogunvoul, V. D. Budaev, D. O. Sizikov, N. V. Gorbakon, A. V. Vlasova

“…The results of the study show that a combined approach using Poisson distribution regression and polynomial signs can significantly improve the accuracy of forecasts. This method, in particular, has demonstrated its effectiveness in modeling onboard equipment failures, which allows to optimize maintenance processes in order to reduce repair costs. …”
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An Intelligent System for Management of Medical Equipment Maintenance by Abbas Izadi, Mohamad Amin Bakhshali, Hadi Ghasemifard, Omid Sarrafzadeh

“…Results: The results demonstrate that the proposed system can accurately predict equipment failures, schedule maintenance tasks efficiently, and manage spare parts inventory effectively. This improves equipment availability and reliability, reduces maintenance costs, and ensures that spare parts are available when needed without incurring excessive inventory costs.Conclusion:Overall, the proposed intelligent system for managing medical equipment maintenance is an effective solution for healthcare facilities to optimize maintenance operations, reduce costs, and ensure patient safety.…”
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Digital Transformation in Aftersales and Warranty Management: A Review of Advanced Technologies in I4.0 by Vicente González-Prida, Carlos Parra Márquez, Pablo Viveros Gunckel, Fredy Kristjanpoller Rodríguez, Adolfo Crespo Márquez

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Application of SHAP and Multi-Agent Approach for Short-Term Forecast of Power Consumption of Gas Industry Enterprises by Alina I. Stepanova, Alexandra I. Khalyasmaa, Pavel V. Matrenin, Stanislav A. Eroshenko

“…It can enable the safe operation of critical infrastructure, for instance, adjusting the operation modes of self-generation units and energy-storage systems, optimizing the power consumption schedule, and reducing electricity and power costs. …”
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Research on 3D Obstacle Avoidance Path Planning for Apple Picking Robotic Arm by Xinyan Chen, Chun Lu, Ziliang Guo, Chengkai Yin, Xuanbo Wu, Xiaolan Lv, Qing Chen

“…The experimental results show that compared to RRT* and IRRT*, the average path cost of the optimization algorithm is reduced by 31.565 mm and 14.935 mm and the average search time is reduced by 7.18 s and 4.33 s. …”
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Multidisciplinary Collaborative Reliability Analysis of the Gear Reducer based on Inverse Reliability Strategy by Wang Liangliang, Peng Jinshuan, Shao Yiming

“…To overcome the high computational cost of reliability analysis,a reliability analysis method which combines the multidisciplinary genetic algorithm collaborative optimization（ GA- CO） based on the inverse reliability strategy（ IRS） is proposed（ IRS- GA- CO）. …”
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Joint Allocation of Power and Subcarrier for Low Delay and Stable Power Line Communication by Zhixiong Chen, Zhihui Yang, Zeng Dou

“…Finally, the performance of the algorithm is compared and analyzed by simulation. The results show that the proposed algorithm can reduce the rate fluctuation and improve the system delay performance and deterministic transmission ability under the condition of ensuring the average rate optimization.…”
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Performance evaluation of an adopted model based on big-bang big-crunch and artificial neural network for cloud applications by Pradeep Rawat, Robin Singh Bhadoria, Punit Gupta, Priti Dimri, G. P. Saroha

“…Cloud can accomplish this using efficient scheduling algorithm. This article focuses on task scheduling policy which aims to improve the performance in real-time with the least execution time, network cost and execution cost-effective at the same time. …”
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Bilevel Programming Model of Urban Public Transport Network under Fairness Constraints by Jingjing Hao, Xinquan Liu, Xiaojing Shen, Nana Feng

“…The results showed that (1) the travel cost deprivation coefficient of the three groups declined from 33.42 to 26.51, with a decrease of 20.68%; the Gini coefficient of the road area declined from 0.248 to 0.030, with a decrease of 87.76%; it could be seen that the transportation equity feeling of low-income groups and objective resource allocation improved significantly; (2) before the optimization of public transport network, the sharing rate of cars, buses, and bicycles was 42%, 47%, and 11%, respectively; after the optimization, the sharing rate of each mode was 7%, 82%, and 11%, respectively. …”
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Multi-Depot Pickup and Delivery Problem with Resource Sharing by Yong Wang, Lingyu Ran, Xiangyang Guan, Yajie Zou

“…Resource sharing (RS) integrated into the optimization of multi-depot pickup and delivery problem (MDPDP) can greatly reduce the logistics operating cost and required transportation resources by reconfiguring the logistics network. …”
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Research on the cooperative offloading strategy of sensory data based on delay and energy constraints by Peiyan YUAN, Saike SHAO, Ran WEI, Junna ZHANG, Xiaoyan ZHAO

“…The edge offloading of the internet of things (IoT) sensing data was investigated.Multiple edge servers cooperatively offload all or part of the sensing data initially sent to the cloud center, which protects data privacy and improves user experience.In the process of cooperative offloading, the transmission of the sensing data and the information exchange among edge servers will consume system resources, resulting in the cost of cooperation.How to maximize the offloading ratio of the sensing data while maintaining a low collaboration cost is a challenging problem.A joint optimization problem of sensing data offload ratio and cooperative scale satisfying the constraints of network delay and system energy consumption was formulated.Subsequently, a distributed alternating direction method of multipliers (ADMM) via constraint projection and variable splitting was proposed to solve the problem.Finally, simulation experiments were carried out on MATLAB.Numerical results show that the proposed method improved the network delay and energy consumption compared to the fairness cooperation algorithm (FCA), the distributed optimization algorithm (DOA), and multi-subtasks-to-multi-servers offloading scheme (MTMS) algorithm.…”
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