Applications of Recent Metaheuristic Algorithms for Loss Reduction in Distribution Power Systems considering Maximum Penetration of Photovoltaic Units by Le Duy Luan Nguyen, Phuc Khai Nguyen, Viet Cuong Vo, Ngoc Dieu Vo, Thang Trung Nguyen, Tan Minh Phan

“…Photovoltaic units (PVUs) are placed optimally by implementing the Coot optimization algorithm (COOA), the archimedes optimization algorithm (AOA), the transient search optimization algorithm (TSOA), the crystal structure algorithm (CrSA), the war strategy optimization algorithm (WSA), and the average and subtraction-based optimizer (ASBO). …”
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Review of machine learning algorithms used in groundwater availability studies in Africa: analysis of geological and climate input variables by Haoulata Touré, Cyril D. Boateng, Solomon S. R. Gidigasu, David D. Wemegah, Vera Mensah, Jeffrey N. A. Aryee, Marian A. Osei, Jesse Gilbert, Samuel K. Afful

“…The findings suggest that more research needs to be conducted on the use of machine learning algorithms on this topic in Africa. In the reviewed papers Fuzzy-based algorithms are commonly used. …”
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Electric vehicles charging station allocation based on load profile forecasting and Dijkstra’s algorithm for optimal path planning by Sahbi Boubaker, Sameer Al-Dahidi, Souad Kamel, Nejib Ghazouani, Habib Kraiem, Faisal S. Alsubaei, Farid Bourennani, Walid Meskine, Mohamed Benghanem, Adel Mellit

“…To determine the most accessible stations, Dijkstra’s algorithm for shortest-path computation based on the EV’s current location and the locations of the CSs around is applied. …”
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Advanced KNN-based cost-efficient algorithm for precision localization and energy optimization in dynamic underwater sensor networks by Nadia Shamshad, Lei Wang, Kiran Saleem, Danish Sarwr, Salil Bharany, Ahmad Almogren, Jaeyoung Choi, Ateeq Ur Rehman, Ayman Altameem

“…By addressing existing localization challenges, the algorithm minimizes localization errors, energy consumption and Time costs while significantly enhancing localization accuracy to 99.98%. …”
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An Unambiguous Super-Resolution Algorithm for TDM-MIMO-SAR 3D Imaging Applications on Fast-Moving Platforms by Sheng Guan, Mingming Wang, Xingdong Liang, Yunlong Liu, Yanlei Li

“…Therefore, it is of vital importance to develop an algorithm which can achieve unambiguous TDM-MIMO-SAR 3D imaging even when the PRI is low. …”
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Integrating Genetic Algorithm and Geographically Weighted Approaches into Machine Learning Improves Soil pH Prediction in China by Wantao Zhang, Jingyi Ji, Binbin Li, Xiao Deng, Mingxiang Xu

“…This study integrates Geographic Weighted Regression (GWR) with three ML models (Random Forest, Cubist, and XGBoost) and designs and develops three geographically weighted machine learning models optimized by Genetic Algorithms to improve the prediction of soil pH values. …”
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Optimized conductor selection and phase balancing in unbalanced distribution networks: Economic optimization via the vortex search algorithm by Brandon Cortés-Caicedo, Jhony Andrés Guzmán-Henao, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña, Rubén Iván Bolaños

“…This methodology is compared against the hurricane optimization algorithm, the sine cosine algorithm, and the salp swarm optimization algorithm. …”
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GU-Net3+: A Global-Local Feature Fusion Algorithm for Building Extraction in Remote Sensing Images by Yali Liu, Cui Ni, Peng Wang, Dongqing Yang, Hexin Yuan, Chao Ma

“…First, frequency domain transformation and a Convolutional Block Attention Module (CBAM) were applied to preprocess the remote sensing images, enhancing building details while suppressing irrelevant noise interference. …”
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Optimized control of parallel heat pump units based on the satin bower bird algorithm in a distributed architecture by Sijia Zhang, Jiangtao Xi, Anjun Zhao, Jun Liu, Yuping Zhang

“…Experimental results confirm the robustness of the D-SBO algorithm, achieving up to a 23.1% improvement in COP. …”
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Spiking Neural Networks Optimized by Improved Cuckoo Search Algorithm: A Model for Financial Time Series Forecasting by Panke Qin, Yongjie Ding, Ya Li, Bo Ye, Zhenlun Gao, Yaxing Liu, Zhongqi Cai, Haoran Qi

“…To address the performance limitations of Spiking Neural Networks (SNNs) caused by hyperparameter sensitivity, this study proposes an SNN model optimized by an Improved Cuckoo Search (ICS) algorithm (termed ICS-SNN). The ICS algorithm enhances global search capability through piecewise-mapping-based population initialization and introduces a dynamic discovery probability mechanism that adaptively increases with iteration rounds, thereby balancing exploration and exploitation. …”
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A Fast and Effective MIMO Algorithm Using CLR-RNN for Hybrid MDM and WDM Optical Communication System by Danni Zhang, Zhongwei Tan, Xinyuan Ma, Shun Lu, Wenhua Ren, Fengping Yan

“…The results show that the introduction of an adaptive machine learning model in MIMO detection for WDM-MDM optical transmission systems can significantly improve the quality of the transmitted signals and achieve better performance than other MIMO detection algorithms while maintaining a faster computational speed and a lower number of parameters.…”
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Drug-Induced Autoimmune Hepatitis: Robust Causality Assessment Using Two Different Validated and Scoring Diagnostic Algorithms by Rolf Teschke, Axel Eickhoff, Gaby Danan

“…Moreover, 2/20 reports (10%) did not use any causality algorithm, providing elusive features of DIAIH. While DIAIH is clearly restricted to drugs as responsible agents, this term is erroneously used to refer to disease induced by non-drugs such as herbs, green tea, dimethoate (an organophosphate insecticide), dietary supplements, biologics, herbal remedies, different viruses, and bacteria, as well as vaccines. …”
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Tropical cyclone track prediction harnessing deep learning algorithms: A comparative study on the Northern Indian Ocean by Sabbir Rahman, M. Fahim Faisal, Prianka Mondal, Md. Mahfuzur Rahman

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Study on Short Term Temperature Forecast Model in Jiangxi Province based on LightGBM Machine Learning Algorithm by Kanghui SUN, An XIAO, Houjie XIA

“…In order to achieve further improvement in the forecast accuracy of station temperatures and enhance the forecast capability for extreme temperatures， this study establishes a 24-hour national station daily maximum （minimum） temperature forecast model for Jiangxi Province based on the LightGBM machine-learning algorithm and the MOS forecast framework by using the surface observation data of 91 national stations in Jiangxi Province and the upper-air and surface forecast data of the ECMWF model from 2017 to 2019.The results of the 2020 evaluation show that the LightGBM model daily maximum （minimum） temperature forecast is consistent with the observed trend， and the annual average forecast is better than that of three numerical models， ECMWF， CMA-SH9 and CMA-GFS， two machine learning products， RF and SVM， and subjective revision products.In terms of the spatial and temporal distribution of forecast errors， the model's daily maximum （minimum） temperature forecast errors in winter and spring are slightly larger than those in summer and autumn； the daily maximum temperature forecast errors show the spatial distribution characteristics of "larger in the south and smaller in the north， and larger in the periphery than in the centre"， while the opposite is true for the daily minimum temperatures.In terms of important weather processes， the LightGBM model has the best prediction effect among the seven products in the high temperature process； in the strong cold air process， the LightGBM model is still better than the three numerical model products and the other two machine-learning models， but the prediction effect of the daily minimum temperature is not as good as that of the subjective revision products.After a simple empirical correction for the low-temperature forecast error in the strong cold air process， the model low-temperature forecast effect is close to that of the subjective revision product.The model significance analysis shows that the recent surface observation features also contribute to the model construction， and the results can be used as a reference for model improvement and temperature forecast product development.At present， the LightGBM model temperature forecast products have been applied to meteorological operations in Jiangxi Province.…”
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Improved security for IoT-based remote healthcare systems using deep learning with jellyfish search optimization algorithm by Faris Kateb, Mahmoud Ragab, Felwa Abukhodair, Omar Ahmed Abdulkader, Louai A. Maghrabi, Sami Saeed Binyamin, Mohammed Khaled Al-Hanawi

“…The bacterial foraging optimization algorithm (BFOA) method is used for feature extraction. …”
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S₂Head: Small-Scale Human Head Detection Algorithm by Improved YOLOv8n Architecture by Yuteng Sui, Xinghua Shan, Linlin Dai, Hui Jing, Bo Li, Jianjun Ma

“…To address this, we propose a novel lightweight head detection algorithm named S2Head, based on an improved YOLOv8n framework. …”
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Beyond Algorithm Updates: A Systematic Validation of GPM DPR-V07 over China’s Multiscale Topography by Jia Song, Haiwei Zhang, Yi Lyu, Hao Wu, Fei Zhang, Xu Ma, Bin Yong

“…The Global Precipitation Measurement (GPM) mission’s Dual-Frequency Precipitation Radar (DPR) serves as a critical benchmark for calibrating satellite-based precipitation products, with its retrieval quality directly governing the accuracy of global precipitation estimates. While the updated version 07 (DPR-V07) algorithm introduces substantial refinements over its predecessor (DPR-V06), systematic evaluations of its operational advancements in precipitation monitoring remain limited. …”
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Mapping climate change induced forest fire susceptibility using tree-based machine learning algorithms in Bangladesh by Mafrid Haydar, Al Hossain Rafi, Md.Kamran Hasan Khan, Sakib Hosan, Halima Sadia

“…This study employs tree-based machine learning (ML) algorithms to assess Forest Fire Susceptibility in the Chittagong Hill Tracts (CHT) of Bangladesh under current and anticipated climate change scenarios. …”
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Automated Audit and Self-Correction Algorithm for Seg-Hallucination Using MeshCNN-Based On-Demand Generative AI by Sihwan Kim, Changmin Park, Gwanghyeon Jeon, Seohee Kim, Jong Hyo Kim

“…This study not only enhances the efficiency and reliability of handling the Seg-Hallucination but also eliminates the reliance on ground truth. The ASHSC algorithm offers intuitive 3D guidance for uncertainty regions, while maintaining manageable computational complexity. …”
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YOLOFIV: Object Detection Algorithm for Around-the-Clock Aerial Remote Sensing Images by Fusing Infrared and Visible Features by Huiying Wang, Chunping Wang, Qiang Fu, Binqiang Si, Dongdong Zhang, Renke Kou, Ying Yu, Changfeng Feng

“…With the rapid advancements in deep learning technology, various deep learning-based object detection algorithms have found extensive applications in UAV-related tasks. …”
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