A Comparative Study of Breast Cancer Detection and Recurrence Prediction Using CatBoost Classifier by Rana Dhia’a Abdu-aljabar, Khansaa Dheya Aljafaar, Zinah Jaffar Mohammed Ameen, Hala A. Naman

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Welding defect detection with image processing on a custom small dataset: A comparative study by József Szőlősi, Béla J. Szekeres, Péter Magyar, Bán Adrián, Gábor Farkas, Mátyás Andó

“…Abstract This work focuses on detecting defects in welding seams using the most advanced You Only Look Once (YOLO) algorithms and transfer learning. To this end, the authors prepared a small dataset of images using manual welding and compared the performance of the YOLO v5, v6, v7, and v8 methods after two‐step training. …”
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Comparative analysis of the effectiveness of three immunization strategies in controlling disease outbreaks in realistic social networks. by Zhijing Xu, Zhenghu Zu, Tao Zheng, Wendou Zhang, Qing Xu, Jinjie Liu

“…The high incidence of emerging infectious diseases has highlighted the importance of effective immunization strategies, especially the stochastic algorithms based on local available network information. …”
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A Comparative Study of XBORE and XBOREOPT Hybrid Models for Ore Production Forecasting in the Mining Industry by Morris Mkokweza, Santhi Kumaran, George Mufungulwa

“…Few hybrid models have been developed to handle data from mine systems, and this study investigates the comparative performance of machine learning algorithms XBORE and XBOREOPT for predicting ore production in mining operations. …”
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Comparing the Effectiveness of Artificial Intelligence Models in Predicting Ovarian Cancer Survival: A Systematic Review by Farkhondeh Asadi, Milad Rahimi, Nahid Ramezanghorbani, Sohrab Almasi

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Research on Evidence Theory Model of Hesitant Fuzzy Information Over Two Universes by MAO Yixuan, WANG Qinghai

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Depression Analysis and Detection Using Machine Learning: Incorporating Gender Differences in a Comparative Study by Marina Galanina, Anna Rekiel, Anna BaCzyk, Bozena Kostek

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Research on Optimization of Target Positioning Error Based on Unmanned Aerial Vehicle Platform by Yinglei Li, Qingping Hu, Shiyan Sun, Yuxiang Zhou, Wenjian Ying

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Research on the On-Line Identification of Ship Maneuvering Motion Model Parameters and Adaptive Control by Jinlai Liu, Lubin Chang, Luping Xu, Fang He, Yixiong He

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Research on the optimization method of inventory management of important spare parts of intercity railway. by Dongyan Wang, Ying Sun, Liang Yu, Kun Shen, Junbo Li, Xia Wu

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Comparative Analysis of Machine Learning Techniques for Fault Diagnosis of Rolling Element Bearing with Wear Defects by Devendra Sahu, Ritesh Kumar Dewangan, Surendra Pal Singh Matharu

“…Timely and accurate diagnosis of bearing faults is essential for preventing unexpected failures and minimizing downtime. This research addresses these challenges by employing advanced signal processing techniques and machine learning algorithms. …”
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Leveraging Feature Sets and Machine Learning for Enhanced Energy Load Prediction: A Comparative Analysis by Fernando Pedro Silva Almeida, Mauro Castelli, Nadine Côrte-Real

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Innovative approach for gauge-based QPE in arid climates: comparing neural networks and traditional methods by Bayan Banimfreg, Ernesto Damiani, Vesta Afzali Gorooh, Duncan Axisa, Luca Delle Monache, Youssef Wehbe

“…Conclusion By effectively merging advanced neural network algorithms with conventional rainfall estimation methods, this study provides a robust framework for understanding and estimating precipitation in arid regions like the UAE. …”
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Compliance Model and Structure Optimization Method Based on Genetic Algorithm for Flexure Hinge Based on X-Lattice Structure by Yin Zhang, Jianwei Wu, Jiubin Tan

“…In order to design a flexure hinge based on the X-lattice structure with good comprehensive performance, this paper proposes an intelligent structure optimization method based on a genetic algorithm. The feasibility of the optimization algorithm is verified by an example.…”
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Proposing a Novel Method for Optimal Location Finding Based on Machine Learning Algorithms and Gray Wolf Optimization by Fatemeh Heydari Pirbasti, Mahmoud Modiri, Kiamars Fathi-Hafshejani, Alireza Rashidi-Komijan

“…Proposed clustering method is evaluated and compared with some metaheuristics algorithm. The simulation results of the proposed method show cost reduction in finding the desired locations compared to similar researches. …”
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A secure and size efficient algorithm to enhance data hiding capacity and security of cover text by using unicode by Allah Ditta, Muhammad Azeem, Shahid Naseem, Khurram Gulzar Rana, Muhammad Adnan Khan, Zafar Iqbal

“…In the described algorithm, the identification of secret information from text files is hard due to less redundant bits in the text as compared to the image, audio, and video steganographic mediums. …”
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A New Meta-heuristic Algorithm based on Multi-criteria Decision Making to Solve Community Detection Problem by Vahid Baradaran, Amir Hossein Hosseinian, Reza Derakhshani

“…The performance of the proposed algorithm has been evaluated through comparing it against classical genetic algorithm and a greedy one. …”
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Benchmarking Machine Learning Algorithms for Bearing Fault Classification Using Vibration Data: A Deployment-Oriented Study by Prasanta Kumar Samal, R. Srinidhi, Pramod Kumar Malik, H. J. Manjunatha, Imran M. Jamadar

“…This work provides a practical reference for researchers and practitioners by systematically comparing ML algorithms and elucidating the trade-offs between predictive accuracy, computational efficiency, and deployment readiness in real-world fault diagnosis applications.…”
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In-Memory Versus Disk-Based Computing with Random Forest for Stock Analysis: A Comparative Study by Chitra Joshi, Chitrakant Banchorr, Omkaresh Kulkarni, Kirti Wanjale

“…As data become increasingly large, diverse and fast-moving, conventional processing systems often fall short of the performance required for modern analytics.Objective: This research seeks to thoroughly assess the performance of two prominent big data processing frameworks-Apache Spark (in-memory computing) and MapReduce (disk-based computing)-with a focus on applying random forest algorithms to predict stock prices. …”
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Research and application of VoLTE video call quality based on machine learning by Qizhu ZHONG

“…To overcome the shortcomings of current methods for evaluating VoLTE video call quality,a method for evaluating VoLTE video call quality without reference based on machine learning and network index parameters was proposed.Firstly,the network parameters of the decoding core network were collected and preprocessed; then,the key features for VoLTE video call quality assessment were selected,and a reference-free evaluation model for VoLTE video quality assessment was constructed by comparing and selecting appropriate machine learning algorithms,so as to achieve real-time VoLTE video call quality assessment independent of the test environment and the original video.By researching the preprocessing of feature index data extracted from XDR data,the standardization of feature index was solved,and the evaluation model of feature input was convenient; the key features of VoLTE video call were selected and evaluated by feature engineering,which reduced the feature dimension and the complexity of the algorithm; at the same time,advanced machine learning technology was adopted to ensure and enhance the algorithm assessment accuracy.…”
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