Multi-criteria decision model for multicircular flight control of unmanned aerial vehicles through a hybrid approach by Noorulden Basil, Hamzah M. Marhoon, Bayan Mahdi Sabbar, Abdullah Fadhil Mohammed, Osamah Albahri, Ahmed Albahri, Abdullah Alamoodi, Iman Mohamad Sharaf, Amare Merfo Amsal, Mahrous Ahmed, Enas Ali, Sherif S. M. Ghoneim

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Sensorless Control of Ultra-High-Speed PMSM via Improved PR and Adaptive Position Observer by Xiyue Bai, Weiguang Huang, Chuang Gao, Yingna Wu

“…To improve the precision of the position and speed estimation in ultra-high-speed (UHS) permanent magnet synchronous motors (PMSM) without position sensors, multiple refinements to the traditional extended electromotive force (EEMF) estimation algorithm are proposed in this paper. …”
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Evaluation Method for Remaining Life of XLPE Insulated Power Cable by MA Hanchao, GAO Baoqi, LI Xiangyang, WU Suzhou, ZHANG Xiaojun

“…The results show that this method can obtain the optimal solution fitness value quickly, improve the efficiency of the surplus life evaluation of the analysis object, determine the weight value of the assessment factor under the measurement of the iterative period, and improve the residual life of the cable. …”
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Advanced long-term actual evapotranspiration estimation in humid climates for 1958–2021 based on machine learning models enhanced by the RReliefF algorithm by Ahmed Elbeltagi, Salim Heddam, Okan Mert Katipoğlu, Abdullah A. Alsumaiei, Mustafa Al-Mukhtar

“…To address this issue and guarantee more accurate ET predictions, this study attempts the following: i) to assess the performance of five machine learning (ML) models optimized by the RReliefF algorithm in estimating actual ET values for each month in four Chinese provinces under various agroclimatic conditions; and ii) to select the optimal model based on statistical metrics while minimizing discrepancies between the estimated and actual ET values. …”
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Dynamic and static integrated classification model of gas well based on XGBoost algorithm—an example from block S of Sulige tight sandstone gas field by Shuangshuang Zhang, Shuangshuang Zhang, Xiangdong Yu, Xiuli Gao, Donglin Li, Shijun Huang

“…Aiming at this problem, this paper establishes a set of dynamic and static integrated classification model of tight sandstone gas wells in Sulige based on XGBoost algorithm. …”
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Comparative analysis and selection of the geometry of the microphone array based on MEMS microphones for sound localisation by Andrii Riabko, Tetiana Vakaliuk, Oksana Zaika, Roman Kukharchuk, Yuriy Smorzhevsky

“…The goal is to determine the most effective array architecture and beamforming algorithms to achieve compactness, accuracy, and balanced omnidirectional coverage. …”
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A Deep Learning Model for Identifying the Risk of Mesenteric Malperfusion in Acute Aortic Dissection Using Initial Diagnostic Data: Algorithm Development and Validation by Zhechuan Jin, Jiale Dong, Chengxiang Li, Yi Jiang, Jian Yang, Lei Xu, Ping Li, Zhun Xie, Yulin Li, Dongjin Wang, Zhili Ji

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Autonomous Robotic Path Planning Based on the Gaussian Mixture Model in Complex Manufacturing Environment by Rui Sun, Yuanmin Wang, Wenzheng Zhao, Yinhua Liu

“…To solve this problem, this paper proposes a path segment directed evolution algorithm (PSDEA) based on the Gaussian mixture model and a heuristic optimization algorithm. …”
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Research on Gating Fusion Algorithm for Power Grid Survey Data Based on Enhanced Mamba Spatial Neighborhood Relationship by Aiyuan Zhang, Jinguo Lv, Yu Geng, Xiaolei Wang, Xianhu Li

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Predictive models for overall health of hydroelectric equipment based on multi-measurement point output by Liu Dong, Kong Lijun, Song Jinghui, Zhou Yiming

“…By comparing and analyzing the predictive performance, error results, and real-time prediction performance before and after model optimization, it was concluded that the prediction model constructed by SBM, hypersphere algorithm, and LSTM network had an overall average improvement of 23.7% in the prediction precision of 12 parameters, including temperature, vibration frequency, pressure, and lubrication degree, for the optimized upper guide bearing, thrust guide bearing, and water guide bearing systems. …”
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An Optimized Transformer–GAN–AE for Intrusion Detection in Edge and IIoT Systems: Experimental Insights from WUSTL-IIoT-2021, EdgeIIoTset, and TON_IoT Datasets by Ahmad Salehiyan, Pardis Sadatian Moghaddam, Masoud Kaveh

“…To enhance the training and convergence of the GAN component, we integrate an improved chimp optimization algorithm (IChOA) for hyperparameter tuning and feature refinement. …”
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Energy management for microgrids integrating renewable sources and hybrid electric vehicles by Wanying Liu, Chunqing Rui, Zilin Liu, Jinxin Chen

“…It also incorporates demand response mechanisms for greater resilience. The Kepler Optimization Algorithm (KOA), inspired by Kepler's laws of planetary motion, is employed to tackle the nonlinear optimization problem. …”
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High-resolution image inpainting using a probabilistic framework for diverse images with large arbitrary masks by G. Sumathi, M. Uma Devi

“…Addressing inpainting challenges in high-resolution images remains a complex task. The most recent image inpainting techniques rely on machine learning models; however, a major limitation of supervised methods is their dependence on end-to-end training. …”
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Multi-Objective Optimal Scheduling of Water Transmission and Distribution Channel Gate Groups Based on Machine Learning by Yiying Du, Chaoyue Zhang, Rong Wei, Li Cao, Tiantian Zhao, Wene Wang, Xiaotao Hu

“…A one-dimensional hydrodynamic model based on St. Venant’s system of equations is built to generate the feature dataset, which is then combined with the random forest algorithm to create a nonlinear prediction model. …”
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An integrated model of threshold-based scaling and fractional admission controlling to improve resource utilization efficiency in 5G core networks. by Ly Cuong Hoa, Thanh Chuong Dang, Viet Minh Nhat Vo

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A simulation-driven computational framework for adaptive energy-efficient optimization in machine learning-based intrusion detection systems by Ripal Ranpara, Osamah Alsalman, Om Prakash Kumar, Shobhit K. Patel

“…Extensive simulations conducted on the KDD 1999 dataset demonstrate that GreenMU achieves a detection accuracy close to 99%, significantly surpassing standard baseline models while reducing energy consumption by 31%. Furthermore, the framework improves computational efficiency, reducing processing time by 15% and making it highly effective for resource-constrained environments such as IoT and edge computing. …”
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Challenges in Unifying Physically Based and Machine Learning Simulations Through Differentiable Modeling: A Land Surface Case Study by Shahryar K. Ahmad, Sujay V. Kumar, Clara Draper, Rolf H. Reichle

“…Scaling and bias correction factors, often used in ML approaches for enhancing generalizability, were found to limit the transferability of the optimized physical parameters to the land model. The global objective function further compromises the algorithm's ability to simultaneously capture contrasting moisture regimes. …”
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Optimizing Social Security Contributions for Spanish Self-Employed Workers: Combining Data Preprocessing and Ensemble Models for Accurate Revenue Estimation by Luis Palomero, Vicente García, José Salvador Sánchez

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Artificial intelligence-optimized shield parameters for soft ground tunneling in urban environment: A case study of Bangkok MRT Blue Line by Sahatsawat Wainiphithapong, Chana Phutthananon, Sompote Youwai, Pitthaya Jamsawang, Phattarawan Malaisree, Ochok Duangsano, Pornkasem Jongpradist

“…This integrated framework, which combines the non-dominated sorting genetic algorithm (NSGA-II) with LSTM neural networks, is applied to MOO to identify the optimal SOPs, while accounting for their influence on S variation as a time-series over 11 timesteps, as considered in this study. …”
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A data-driven approach utilizing machine learning (ML) and geographical information system (GIS)-based time series analysis with data augmentation for water quality assessment in M... by Abhijeet Das

“…Our research in Mahanadi River Basin, Odisha, presents an enhanced methodology based on data, specifically designed to be beneficial for Water Quality (WQ) based on Synthetic Pollution Index (SPI) and machine learning models such as Long Short-Term Memory (LSTM) and Sparrow Search Algorithm (SSA), for its analysis and interpretation of extensive, intricate data sets on water quality, as well as the allocation of pollution sources or contributing elements, in order to improve knowledge of the water quality and the planning of monitoring networks for efficient water resource management. …”
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