Short-Term Load Forecasting for Electrical Power Distribution Systems Using Enhanced Deep Neural Networks by Shewit Tsegaye, Sanjeevikumar Padmanaban, Lina Bertling Tjernberg, Kinde Anlay Fante

“…This represents a 7.486% improvement over the prediction obtained using only LSTM model. …”
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Faults Detection and Diagnosis of a Large-Scale PV System by Analyzing Power Losses and Electric Indicators Computed Using Random Forest and KNN-Based Prediction Models by Yasmine Gaaloul, Olfa Bel Hadj Brahim Kechiche, Houcine Oudira, Aissa Chouder, Mahmoud Hamouda, Santiago Silvestre, Sofiane Kichou

“…Accurate and reliable fault detection in photovoltaic (PV) systems is essential for optimizing their performance and durability. This paper introduces a novel approach for fault detection and diagnosis in large-scale PV systems, utilizing power loss analysis and predictive models based on Random Forest (RF) and K-Nearest Neighbors (KNN) algorithms. …”
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Bond behavior of galvanized iron fiber reinforced concrete with recycled coarse aggregate and model prediction using machine learning by Md. Jahidul Islam, Ummul Wara Labiba, Tasfiah Faisal Chowdhury, Md. Shahjalal, Tanvir Mustafy, Tanvir Hassan Tusher

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Multi-Agent Mapping and Tracking-Based Electrical Vehicles with Unknown Environment Exploration by Chafaa Hamrouni, Aarif Alutaybi, Ghofrane Ouerfelli

“…When rapid deliveries are required, the algorithm prioritizes faster routes, whereas, for flexible schedules, it optimizes energy conservation. …”
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SC-Route: A Scalable Cross-Layer Secure Routing Method for Multi-Hop Inter-Domain Wireless Networks by Yanbing Li, Yang Zhu, Shangpeng Wang

“…Second, we introduce a cross-layer information fusion mechanism that allows nodes to adapt routing costs in real time under heterogeneous network conditions, thereby improving path reliability and load balancing. …”
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Evaluation method for gas pre-extraction status in coal seam boreholes based on semi-supervised learning by YAN Li, WEN Hu, WANG Zhenping, JIN Yongfei

“…The application results from the 215 working face of the Huangling No. 2 Coal Mine in Shaanxi Province showed that the maximum validity clustering rate (MVCR) and adjusted rand index (ARI) of SSGMM and SSK-Means reached 82.64% and 85.83%, respectively, significantly outperforming conventional clustering methods. After optimization through a dynamic feedback mechanism, boreholes initially classified as "poor" showed an improvement of 5.26% to 5.80% in extraction efficiency, achieving a 100% remediation rate.…”
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Lossless Compression with Trie-Based Shared Dictionary for Omics Data in Edge–Cloud Frameworks by Rani Adam, Daniel R. Catchpoole, Simeon J. Simoff, Zhonglin Qu, Paul J. Kennedy, Quang Vinh Nguyen

“…The preprocessed data are subsequently transmitted to the cloud, where advanced compression algorithms, such as Zstd, GZIP, Snappy, and LZ4, further compress them. …”
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Robust Framework for PMU Placement and Voltage Estimation of Power Distribution Network by Nida Khanam, Mohd. Rihan, Salman Hameed

“…The framework improves network observability with a minimum of PMUs, lowering deployment costs while retaining excellent estimation accuracy. …”
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Electric Vehicle Cluster and Scheduling Strategy Based on Dynamic Game by LI Shuai, DING Xiying, JIANG Hongfa

“…The upper layer takes the peak shaving demand and peak shaving cost of distribution system operator (DSO) as the optimization objectives, and uses an improved multi-objective particle swarm optimization algorithm to obtain the game strategy set of DSO. …”
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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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