Study on the anti-penetration randomness of metal protective structures based on optimized artificial neural network by Lan Liu, Weidong Chen, Shengzhuo Lu, Yanchun Yu, Mingwu Sun

“…Abstract In order to study the Anti-Penetration Randomness of Metal Protective Structures (APRMPS) for the penetration probabilities of Metal Protective Structures under the action of the basic random variables, this paper analyzes the candidates for the basic random variables and the random response of APRMPS, and, on the basis of the improvement of Genetic Algorithm, proposes Dynamic Lifecycle Genetic Algorithm, including its main processes of the optimization of Back Propagation Neural Network. …”
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A Prototype of Automotive 77 GHz Radar by O. I. Bureneva, I. G. Gorbunov, G. V. Komarov, A. A. Konovalov, M. S. Kupriyanov, Yu. A. Shichkina

“…Automotive radars are the main tools for providing traffic safety. The development of such radars involve a number of technical difficulties due to the manufacture of high-precision extremely high-frequency (EHF) printed circuit boards. …”
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Computational complexity when constructing rational plans for program execution in a given field of parallel computers by V. M. Bakanov

“…The main method for developing PPE plans was the construction, analysis, and purposeful transformation of the stacked-parallel form (SPF) of information graphs of algorithms (IGA). …”
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Distribution Network Security Situation Awareness Method Based on the Distribution Network Topology Layered Model by Yuhong Ouyang, Man Li, Wenqian Kang, Xiangbei Che, Ruixian Ye

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The Conformal Finite-Difference Time-Domain Simulation of GPR Wave Propagation in Complex Geoelectric Structures by Man Yang, Hongyuan Fang, Dazhong Chen, Xueming Du, Fuming Wang

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Enhancing MPPT optimization with hybrid predictive control and adaptive P&O for better efficiency and power quality in PV systems by Benabdallah Naima, Belabbas Belkacem, Tahri Ahmed, Habib Benbouhenni, Bouddou Riyadh, Heroual Samira, Zaidi Sarra, Z. M. S. Elbarbary, Salman Arafath Mohammed

“…Despite these numerous benefits, the stability and quality of power are the main drawbacks facing these energy systems. Boost converters are used to maximize the power output of the photovoltaic system and power the load. …”
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Short-Term Power Load Forecasting Using an Improved Model Integrating GCN and Transformer by Man Wu, Wanyi Feng, Xinya Li, Yunan Liu, Chuxin Cao

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A new smart charging electric vehicle and optimal DG placement in active distribution networks with optimal operation of batteries by Bilal Naji Alhasnawi, Marek Zanker, Vladimír Bureš

“…In order to reduce MGs' reliance on the main grid, this study first proposes a smart charging method for PHEVs that maximizes the utilization of RERs and DERs while minimizing the amount of energy taken from the main grid. …”
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Machine Learning in the National Economy by Azamjon A. Usmonov

“…The paper provides recommendations for developing machine learning infrastructure, investing in research, and training professionals, which can contribute to economic growth and increase the country’s competitiveness.Materials and methods: Various methods and approaches to examine machine learning in the national economy were used in this paper. The main methods include an analysis of scientific literature, statistical data analysis, modeling using machine learning algorithms, and practical implementation of economic models with programming languages such as Python and machine learning libraries.To analyze economic data, methods such as linear regression, decision trees, and neural networks were selected, as they effectively predict changes in key macroeconomic indexes such as GDP, inflation, exchange rates, and unemployment levels. …”
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Methodology for Building a Prototype System for Complex Data Analysis of Thematic Sites by I. I. Piletski, M. P. Batura, N. A. Volarava

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Improving Search Accuracy in Large-Scale Biased Multiobjective Optimization Through Local Search by Feng Yin, Bin Cao

“…To address this issue, we propose a three-particle-based local search method (TPS) for multiobjective evolutionary algorithms (MOEAs). The main concept is to use three particles to maintain three equidistant values of a decision variable and gradually approach the local optimal value by adaptively adjusting their differences. …”
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Design and Analysis of a Hybrid MPPT Method for PV Systems Under Partial Shading Conditions by Oğuzhan Timur, Bayram Kaan Uzundağ

“…The classical Maximum Power Point Tracking (MPPT) algorithm fails to determine the global maximum operating point to prevent power losses under partial shading conditions. …”
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Integration of AI in Self-Powered IoT Sensor Systems by Cosmina-Mihaela Rosca, Adrian Stancu

“…The conclusions drawn from these results underscore the need for an interdisciplinary approach and detailed exploration of ML algorithms to be adapted to the hardware infrastructures of autonomous sensors. …”
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Voltage Regulation Strategies in Photovoltaic-Energy Storage System Distribution Network: A Review by Qianwen Dong, Xingyuan Song, Chunyang Gong, Chenchen Hu, Junfeng Rui, Tingting Wang, Ziyang Xia, Zhixin Wang

“…At the same time, this paper discusses the advantages and limitations of centralized, distributed, multi-timescale, voltage-reactive joint optimization and other regulation methods and focuses on the analysis of heuristic algorithms and algorithms based on deep reinforcement learning in the voltage regulation of the relevant research progress. …”
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10 MW FOWT Semi-Submersible Multi-Objective Optimization: A Comparative Study of PSO, SA, and ACO by Souleymane Drabo, Siqi Lai, Hongwei Liu, Xiangheng Feng

“…This novel framework enables highly efficient 3D plots, an optimization loop, and the automatic and comparative output of solutions. Python, the main interface, integrated PyMAPDL and Pymoo for intricate modeling and simulation tasks. …”
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Delineation of Optimized Single and Multichannel Approximate DA-Based Filter Design Using Influential Single MAC Strategy for Trans-Multiplexer by Britto Pari James, Leung Man-Fai, Mariammal Karuthapandian, Vaithiyanathan Dhandapani

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Truck Lifting Accident Detection Method Based on Improved PointNet++ for Container Terminals by Yang Shen, Xintai Man, Jiaqi Wang, Yujie Zhang, Chao Mi

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Palmitoylation-related gene ZDHHC22 as a potential diagnostic and immunomodulatory target in Alzheimer’s disease: insights from machine learning analyses and WGCNA by Sanying Mao, Xiyao Zhao, Lei Wang, Yilong Man, Kaiyuan Li

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Elucidating the role of KCTD10 in coronary atherosclerosis: Harnessing bioinformatics and machine learning to advance understanding by Xiaomei Hu, Fanqi Liang, Man Zheng, Juying Xie, Shanxi Wang

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Prediction of successful weaning from renal replacement therapy in critically ill patients based on machine learning by Qiqiang Liang, Xin Xu, Shuo Ding, Jin Wu, Man Huang

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