Intelligent path planning algorithms for UAVs: Classification, complexity analysis, hybrid ablation insights, and future directions by Dradoum Alaa, Khelassi Abdelmadjid, Lachekhab Fadhila

“…This paper offers an overview of UAV path planning research founded on intelligent algorithms, which are divided into three categories: computational intelligence (CI), machine learning (ML), and hybrid methods. …”
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Medical Image Classification Algorithm Based on Weight Initialization-Sliding Window Fusion Convolutional Neural Network by Feng-Ping An

“…Based on the above ideas, this paper proposes a medical classification algorithm based on a weight initialization/sliding window fusion for multilevel convolutional neural networks. …”
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A Topical Review of Quantum and Classical Machine Learning Approaches to Disaster Escape Routing Problems by A. Vinil, Parameswaran Iyer, Jetain Chetan, Aniket Bembale, Nagendra Singh

“…However, most classical algorithms are most effective on static graphs. They either cannot be adapted to dynamic graphs or become computationally expensive. …”
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Alphabet Handwriting Recognition: From Wood‐Framed Hydrogel Arrays Design to Machine Learning Decoding by Guihua Yan, Xichen Hu, Ziyue Miao, Yongde Liu, Xianhai Zeng, Lu Lin, Olli Ikkala, Bo Peng

“…Efficient handwritten recognition is then achieved through appropriate manual feature extraction and algorithms with low complexity within a computing network, as demonstrated in this work, the strategic choice of expertise‐based feature engineering and simplified algorithms effectively boost the overall model performance on handwriting recognition. …”
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In-Process Monitoring of Inhomogeneous Material Characteristics Based on Machine Learning for Future Application in Additive Manufacturing by André Jaquemod, Marijana Palalić, Kamil Güzel, Hans-Christian Möhring

“…The integration of in-process monitoring in machining processes facilitates the identification of inhomogeneity characteristics in manufacturing, which is crucial for process adaptation. …”
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A comprehensive machine learning for high throughput Tuberculosis sequence analysis, functional annotation, and visualization by Md. Saddam Hossain, Md. Parvez Khandocar, Farzana Akter Riti, Md. Yeakub Ali, Prithbey Raj Dey, S M Jahurul Haque, Amira Metouekel, Atrsaw Asrat Mengistie, Mohammed Bourhia, Farid Khallouki, Khalid S. Almaary

“…We trained ML-supervised algorithms like XG Boost, Logistic Regression, Random Forest Classifier, Ad- aBoost, and Support Vector Machine to help classify TB patients from large RNA-sequence count data. …”
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Spectroscopy-Based Methods and Supervised Machine Learning Applications for Milk Chemical Analysis in Dairy Ruminants by Aikaterini-Artemis Agiomavriti, Maria P. Nikolopoulou, Thomas Bartzanas, Nikos Chorianopoulos, Konstantinos Demestichas, Athanasios I. Gelasakis

“…Currently, the advancements and utilization of spectroscopy-based techniques combined with machine learning algorithms have made the development of analytical tools and real-time monitoring and prediction systems in the dairy ruminant sector feasible. …”
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Machine learning based method for forecasting short-term passenger flow in urban rail stations by HU Mingwei, SHI Xiaolong, WU Wenlin, HE Guoqing

“…In order to improve the operation efficiency of the urban rail transit system and achieve the goal of smart operations, this paper applies machine learning algorithms and completes the feature engineering of urban rail transit passenger flow data in terms of time, space and external factors. …”
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Machine Learning-Based Intrusion Detection Systems for the Internet of Drones: A Systematic Literature Review by Mostafa Ogab, Sofiane Zaidi, Abdelhabib Bourouis, Carlos T. Calafate

“…The selected studies are categorized according to publication year, venue, journal, drone domain, IDS type, utilized algorithms, datasets, attack classifications, and software environments. …”
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Development of Advanced Machine Learning Models for Predicting CO₂ Solubility in Brine by Xuejia Du, Ganesh C. Thakur

“…This study explores the application of advanced machine learning (ML) models to predict CO₂ solubility in NaCl brine, a critical parameter for effective carbon capture, utilization, and storage (CCUS). …”
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Insights into landslide susceptibility: a comparative evaluation of multi-criteria analysis and machine learning techniques by Zuleide Ferreira, Bruna Almeida, Ana Cristina Costa, Manoel do Couto Fernandes, Pedro Cabral

“…Although some studies have employed machine learning (ML) algorithms and multi-criteria analysis (MCA) for landslide susceptibility mapping (LSM), comparative evaluations of these methods remain scarce, particularly regarding predictor importance, performance metrics, and hyperparameter optimization. …”
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Employing Streaming Machine Learning for Modeling Workload Patterns in Multi-Tiered Data Storage Systems by Edson Ramiro Lucas Filho, George Savva, Lun Yang, Kebo Fu, Jianqiang Shen, Herodotos Herodotou

“…Modern multi-tiered data storage systems optimize file access by managing data across a hybrid composition of caches and storage tiers while using policies whose decisions can severely impact the storage system’s performance. Recently, different Machine-Learning (ML) algorithms have been used to model access patterns from complex workloads. …”
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Large-Scale Completion of Ionospheric TEC Maps Using Machine Learning Models With Constraints Conditions by Qingfeng Li, Hanxian Fang, Chao Xiao, Die Duan, Hongtao Huang, Ganming Ren

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Prediksi Kesiapan Sekolah Menggunakan Machine Learning Berbasis Kombinasi Adam dan Nesterov Momentum by Indah Mustika Rahayu, Ahmad Yusuf, Mujib Ridwan

“…Meanwhile, teachers and parents who have a role in providing support and stimulation to children cannot use these instrument. Machine learning is a technique that uses algorithms to find useful patterns in data. …”
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IoT-driven real-time weather measurement and forecasting mobile application with machine learning integration by Jul Jalal Al-Mamur Sayor, Nishat Tasnim Shishir, Bitta Boibhov Barmon, Sumon Ahemed, Md. Moshiur Rahman

“…This paper introduces a real-time weather forecasting mobile application that integrates machine learning and IoT technology to address these challenges effectively. …”
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Weight optimization of steel lattice transmission towers based on Differential Evolution and machine learning classification technique by Tran-Hieu Nguyen, Anh-Tuan Vu

“…A classification model based on the Adaptive Boosting algorithm is developed in order to eliminate unpromising candidates during the optimization process. …”
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Loss reduction optimization strategies for medium and low-voltage distribution networks based on Intelligent optimization algorithms by Nian Liu, Yuehan Zhao

“…Methodology In order to reduce line losses, a loss optimization model for low and medium voltage distribution networks based on an improved Gray Wolf optimization support vector machine is proposed. The optimization model introduces a dimensional learning strategy based on the original model to enhance the adaptability and robustness of the model. …”
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Stable Parallel Algorithms for Interdisciplinary Computer-Based Online Education with Real Problem Scenarios for STEM Education by Liangfu Jiang, Haoran Yuan

“…In this paper, we analyse and study the interdisciplinary style of stable parallel algorithms for online computer education and real problem scenarios for STEM education. …”
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A hybrid Genetic Algorithm and Fuzzy Logic approach to ergonomic design of workstations in metal casting operations by Intan Berlianty, Irwan Soejanto, Indun Titisariwati, Favian Ersanta Andhika Putra, Wahyu Tri Utami, Mohamad Kamil Insani

“…Hazardous working conditions, including high temperatures, exposure to gases, and repetitive motions, increase the risk of injuries and fatigue. 1 This study proposes a novel hybrid approach that integrates Genetic Algorithm (GA) and Fuzzy Logic (FL) to optimize workstation ergonomics. …”
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Advancing truss structure optimization—A multi-objective weighted average algorithm with enhanced convergence and diversity by Divya Adalja, Kanak Kalita, Lenka Čepová, Pinank Patel, Nikunj Mashru, Pradeep Jangir, Arpita

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