Multi-objective coordinated control and optimization for photovoltaic microgrid scheduling by Da Yu, Kai Hou, Xu Lin, Guoyang Cai, Xin Shan, Weihua Wang

“…To address the challenges of slow convergence and local optima in traditional PV microgrid scheduling methods, this study introduced an improved multiple objective particle swarm optimization (IMOPSO) algorithm that integrates an adaptive inertia weight adjustment strategy based on optimal similarity and a multi-directional iterative Pareto solution archive update mechanism. …”
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Using Artificial Intelligence Tools to Analyze Particulate Matter Data (PM_2.5) by Miriam Gómez Marín, Henry O. Sarmiento-Maldonado, Alba Nelly Ardila Arias, William Alonso Giraldo Aristizábal, Rubén Darío Vásquez-Salazar

“…A multivariable clustering methodology was evaluated using the LAMDA algorithm as an alternative tool for analyzing air quality data. …”
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Elastoplastic constitutive model considering the filling and cementation effects for gas hydrate-bearing sediments: development and finite element implementation by Qingmeng Yuan, Qingmeng Yuan, Qingmeng Yuan, Qianyong Liang, Qianyong Liang, Jinqiang Liang, Jinqiang Liang, Zhigang Wang, Zhigang Wang, Lin Yang, Lin Yang, Xuemin Wu, Xuemin Wu, Binbin Guo, Binbin Guo, Yifei Dong, Yifei Dong

“…Additionally, cementation strength is incorporated to adjust the yield function, while state parameters are used to modify the potential strength. …”
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Improving forest above-ground biomass estimation using genetic-based feature selection from Sentinel-1 and Sentinel-2 data (case study of the Noor forest area in Iran) by Armin Moghimi, Ava Tavakoli Darestani, Nikrouz Mostofi, Mahdiyeh Fathi, Meisam Amani

“…In this study, we employed a Genetic Algorithm (GA) to estimate forest Above-Ground Biomass (AGB) by selecting the most applicable features from both Sentinel-2 optical and Sentinel-1 Synthetic Aperture Radar (SAR) images in the Noor forest. …”
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Model Predictive Control of Electric Water Heaters in Individual Dwellings Equipped with Grid-Connected Photovoltaic Systems by Oumaima Laguili, Julien Eynard, Marion Podesta, Stéphane Grieu

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Optimized feature selection and advanced machine learning for stroke risk prediction in revascularized coronary artery disease patients by Yong Si, Armin Abdollahi, Negin Ashrafi, Greg Placencia, Elham Pishgar, Kamiar Alaei, Maryam Pishgar

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Integrating infiltration processes in hybrid downscaling methods to estimate sub-surface soil moisture by Mo Zhang, Yong Ge, Jianghao Wang

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Concrete Dam Deformation Prediction Model Based on Attention Mechanism and Deep Learning by ZHANG Hongrui, CAO Xin, JIANG Chao, ZU Anjun, XU Mingxiang

“…Traditional statistical methods based on hydrostatic-season-time (HST) theory, while having clear physical meanings and being easy to implement, are limited by their inherent linear assumptions, resulting in constrained prediction accuracy. …”
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Estimating and mapping tailings properties of the largest iron cluster in China for resource potential and reuse: A new perspective from interpretable CNN model and proposed spectr... by Haimei Lei, Nisha Bao, Moli Yu, Yue Cao

“…The direct standardization (DS) algorithm was applied to correct GF-5 hyperspectral image. …”
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Improved Lyrebird optimization for multi microgrid sectionalizing and cost efficient scheduling of distributed generation by Karthik Nagarajan, Arul Rajagopalan, Mohit Bajaj, Valliappan Raju, Vojtech Blazek, Lukas Prokop

“…This paper introduces the Improved Lyrebird Optimization Algorithm (ILOA) for optimal sectionalizing and scheduling of multi-microgrid systems, aiming to minimize generation costs and active power losses while ensuring system reliability. …”
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Reduced-dose deep learning iterative reconstruction for abdominal computed tomography with low tube voltage and tube current by Shumeng Zhu, Baoping Zhang, Qian Tian, Ao Li, Zhe Liu, Wei Hou, Wenzhe Zhao, Xin Huang, Yao Xiao, Yiming Wang, Rui Wang, Yuhang Li, Jian Yang, Chao Jin

“…This study investigated the feasibility of a deep learning iterative reconstruction algorithm (Deep IR) in reducing the radiation dose while improving the image quality for abdominal computed tomography (CT) with low tube voltage and current. …”
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The P Balasubramaniam Award-2024 Singapore Orthopaedic Association Annual Scientific Meeting Award: Novel artificial intelligence algorithm for soft tissue balancing and bone cuts... by Matthew Song Peng Ng, Ryan Wai Keong Loke, Melvin Kian Loong Tan, Yau Hong Ng, Zi Qiang Glen Liau

“…Conclusion Our novel AI algorithm significantly improves accuracy in achieving surgeon-defined target extension and flexion gaps while reducing soft tissue balancing and total surgical duration. …”
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Évaluation comparative des algorithmes d'apprentissage automatique pour la classification des types de sols à partir de caractéristiques physico-chimiques : application de Random F... by Mamadou Ndiaye, René Boissy, Mbagnick Faye, N’kpomé Styvince Romaric Kouao

“…This study explores the application of machine learning algorithms for soil type classification, a crucial task for agriculture and sustainable land management, particularly in areas facing environmental challenges such as soil degradation. …”
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Joint Three-Task Optical Performance Monitoring with High Performance and Superior Generalizability Using a Meta-Learning-Based Convolutional Neural Network-Attention Algorithm and... by Di Zhang, Junyao Shi, Yameng Cao, Yan Ling Xue

“…The results demonstrate that the MAML-CNN-ATT algorithm achieves errors of less than 1 dB in both NLNP estimation and OSNR monitoring tasks while achieving 100% accuracy in the MFI task. …”
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Data-driven Detection and Identification of Line Parameters with PMU and Unsynchronized SCADA Measurements in Distribution Grids by Jinping Sun, Qifang Chen, Mingchao Xia

“…Then, the power-loss samples with the PMU time stamps and chronological correlations are generated by the two PDFs of the power loss via the Metropolis-Hastings (MH) algorithm. Finally, using the power-loss samples and PMU current measurements, the line parameters are identified using the total least squares (TLS) algorithm. …”
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ON THE CREATION OF THE AUTOMATION SYSTEM RELATED TO SOCIAL-ECONOMIC MOVEMENTS OF PEOPLE by L. V. Rudikova, V. V. Danilchik

“…General approaches of algorithms and data structures usage are proposed. The system architecture is described with the possibility of scaling both vertical and horizontal.The proposed system organizes the process of searching for data and filling the database from third-party sources. …”
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UAV Path Optimization for WSN in Smart Agriculture by Katia Karam, Ali Mansour, Mohamad Khaldi, Benoit Clement, Mohammad Ammad-Uddin

“…Many existing studies oversimplify this problem by considering some of these constraints while neglecting others, leading to suboptimal solutions. …”
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Research on Lightweight Dynamic Security Protocol for Intelligent In-Vehicle CAN Bus by Yuanhao Wang, Yinan Xu, Zhiquan Liu, Suya Liu, Yujing Wu

“…In hardware tests, using an ECU operating at a frequency of 30 MHz, the computation time for the security algorithm on a single message was 0.85 ms, while at 400 MHz, the computation time was reduced to 0.064 ms. …”
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LEAF-YOLO: Lightweight Edge-Real-Time Small Object Detection on Aerial Imagery by Van Quang Nghiem, Huy Hoang Nguyen, Minh Son Hoang

“…To address this, we propose LEAF-YOLO, a lightweight and efficient object detection algorithm with two versions: LEAF-YOLO (standard) and LEAF-YOLO-N (nano). …”
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SOE: A Multi-Objective Traffic Scheduling Engine for DDoS Mitigation with Isolation-Aware Optimization by Mingwei Zhou, Xian Mu, Yanyan Liang

“…These objectives are combined into a composite scalarized loss function with soft constraints, prioritizing a BTAR while maintaining flexibility. To solve this problem, we introduce MOFATA, a multi-objective extension of the Fata Morgana Algorithm (FATA) within a Pareto-based evolutionary framework. …”
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