Integration of Distributed Energy Resources in Unbalanced Networks Using a Generalized Normal Distribution Optimizer by Laura Sofía Avellaneda-Gómez, Brandon Cortés-Caicedo, Oscar Danilo Montoya, Jesús M. López-Lezama

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Dynamic Trajectory Control and User Association for Unmanned-Aerial-Vehicle-Assisted Mobile Edge Computing: A Deep Reinforcement Learning Approach by Libo Wang, Xiangyin Zhang, Kaiyu Qin, Zhuwei Wang, Hang Yin, Jiayi Zhou, Deyu Song

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Tabular transformer generative adversarial network for heterogeneous distribution in healthcare by Ha Ye Jin Kang, Minsam Ko, Kwang Sun Ryu

“…Thus, the TT-GAN exhibited considerable potential in healthcare, demonstrating its ability to generate artificial data that closely resembled real healthcare datasets. The ability of the algorithm to handle different types of mixed variables efficiently, including polynomial, discrete, and continuous variables, demonstrated its versatility and practicality in health care research and data synthesis.…”
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Planning Flexible Bus Service as an Alternative to Suspended Bicycle-Sharing Service: A Data-Driven Approach by Yujia Wang, Yuan Tian, Binyu Yang, Jian Wang, Xiaowei Hu, Shi An

“…Firstly, an FFBS trip path reconstruction algorithm consists of fine-grained road network modelling and trajectory matching is proposed. …”
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A Phase Error Compensation Method for High-Rise Targets in High-Resolution SAR Images by JiaDong Deng, Wei Yang, HongCheng Zeng, YaMin Wang, Jiayi Guo, Wei Xiong, Min Liu, Jie Chen, Wei Liu

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A Machine Learning Aided Reference-Tone-Based Phase Noise Correction Framework for Fiber-Wireless Systems by Guo Hao Thng, Said Mikki

“…In recent years, the research involving the use of machine learning in the field of communication networks have shown promising results, in particular, improving receiver sensitivity against noise and link impairment. …”
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Scientific and Engineering Proposals for Improving the Noise Immunity of Receiving Multi-Position Signals in Channels with Variable Parameters by M. R. Bibarsov, S. V. Dvornikov, A. F. Kryachko, A. V. Pshenichnikov

“…The study was conducted using the methods of noise immunity research, as well as communication theory and signal theory.Results. …”
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Modeling New Nature of Extraction and State Identification of Vibration Shock Signals From Hydroelectric Generating Units Using LCGSA Optimized RBF Combined With CEEMDAN Sample Ent... by Xiang Li, Yun Zeng, Jing Qian, Boyi Xiao, Neng Fei, Fang Dao, Yidong Zou

“…This paper introduces a novel fault diagnosis approach that leverages a wavelet threshold algorithm for initial signal preprocessing and enhances the Radial Basis Function (RBF) neural network with an optimized Gravitational Search Algorithm (GSA). …”
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Equivalence of the schemes of programs based on the algebraic approach to setting the semantics of programming languages by Y. P. Korablin

“…The paper aimed at developing an effective algorithm for studying equivalence (nonequivalence) of program schemes of sequential programming languages.Methods. …”
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THE LGORITHMIC BASICS OF MEASUREMENTS by A. A. Moskvitin, A. B. Cheboksary, A. V. Duplishchev

“…The research is based on the principle of phenomenological symmetry of Yu.I. …”
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Simultaneous Optimization of Network Reconfiguration and Soft Open Points Placement in Radial Distribution Systems Using a Lévy Flight-Based Improved Equilibrium Optimizer by Ridha Djamel Mohammedi, Djamal Gozim, Abdellah Kouzou, Mustafa Mosbah, Ahmed Hafaifa, Jose Rodriguez, Mohamed Abdelrahem

“…This research paper focuses on the application of a new method for the simultaneous reconfiguration and the optimum placing of Soft Open Points (SOPs) in Radial Distribution Systems (RDS). …”
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Efficient Equivalence Checking Technique for Some Classes of Finite-State Machines by Vladimir A. Zakharov

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Active Equalization Strategy for Lithium-Ion Battery Packs Based on Multilayer Dual Interleaved Inductor Circuits in Electric Vehicles by Xu Lei, Jianping He, Linqian Fan, Guiping Wang

“…The experiment results show that the AFNN algorithm reduces the total equalization time by approximately 37.4% and improves equalization efficiency by about 4.89% in contrast with the conventional mean-difference algorithm. …”
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ANALISIS KLASTERISASI DAN PERAMALAN HASIL KOMODITAS TANAMAN CABAI MENGGUNAKAN METODE K-MEDOIDS DAN FUZZY TIMES SERIES DI KABUPATEN LIMA PULUH KOTA by Desvina Yulisda, Muthmainnah Muthmainnah, Hisyam Maulana Hadi

“…Clustering is needed in this area because many sub-districts in Lima Puluh Kota Regency produce chilli commodities so that it can facilitate the government in determining which areas have the potential to increase and optimise the yield of chilli commodities. This research uses Cluster Analysis with the K-Medoids Algorithm method and forecasting using the Fuzzy Time Series method. …”
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Macrostructural Analysis of the Dynamics of the Two-Sector Economy by O. S. Sukharev, E. N. Voronchikhina

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Robust Task Offloading and Trajectory Optimization for UAV-Mounted Mobile Edge Computing by Runhe Wang, Yang Huang, Yiwei Lu, Pu Xie, Qihui Wu

“…Nevertheless, current research lacks studies of robust offloading scheme scheduling and trajectory planning using terrestrial random channels. …”
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INFORMATION TECHNOLOGY FOR RECOGNITION OF ROAD SIGNS USING A NEURAL NETWORK by Elena Yashina, Roman Artiukh, Nikolai Рan, Andrei Zelensky

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Deep neural network based distribution system state estimation using hyperparameter optimization by Gergő Békési, Lilla Barancsuk, Bálint Hartmann

“…In the past decade, distribution system state estimation has become a crucial topic in power system research due to the increasing importance of distribution networks amidst the decline of centralized energy production. …”
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Cross-Attention-Based High Spatial-Temporal Resolution Fusion of Sentinel-2 and Sentinel-3 Data for Ocean Water Quality Assessment by Yanfeng Wen, Peng Chen, Zhenhua Zhang, Yunzhou Li

“…Current marine research that leverages remote sensing data urgently requires gridded data of high spatial and temporal resolution. …”
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PCMINN: A GPU-Accelerated Conditional Mutual Information-Based Feature Selection Method by Nikolaos Papaioannou, Georgios Myllis, Alkiviadis Tsimpiris, Stamatis Aggelopoulos, Vasiliki Vrana

“…Although effective, the original CMINN algorithm can be computationally intensive, particularly with large and high-dimensional datasets. …”
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