Ensemble Learning-Based Metamodel for Enhanced Surface Roughness Prediction in Polymeric Machining by Elango Natarajan, Manickam Ramasamy, Sangeetha Elango, Karthikeyan Mohanraj, Chun Kit Ang, Ali Khalfallah

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Application of artificial neural network in determining the fabric weave pattern by Subrata Das, Keerthana Shanmugaraja

“…The approaches based on early machine learning algorithms directly depend on handcrafted features, which are time-consuming and occurs more errors. …”
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Spatiotemporal estimation of ambient forest phytoncides: Unveiling patterns through geospatial-based machine learning approach by Aji Kusumaning Asri, Hao-Ting Chang, Chia-Pin Yu, Wan-Yu Liu, Yinq-Rong Chern, Rui-Hao Xie, Shih-Chun Candice Lung, Kai Hsien Chi, Yu-Cheng Chen, Sen-Sung Cheng, Gary Adamkiewicz, John D. Spengler, Chih-Da Wu

“…The results showed that RF and XGB were the most effective algorithms, explaining approximately 83.3% and 98.4% of the spatiotemporal variability in camphene and α-pinene, respectively. …”
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A Comparative Analysis of Machine Learning Algorithms for Classification of Diabetes Utilizing Confusion Matrix Analysis by Maad M. Mijwil, Mohammad Aljanabi

“…Machine learning algorithms can scrutinize vast quantities of data from electronic health records, medical images, and other sources to identify patterns and make predictions, which can support healthcare professionals and experts in making better-informed decisions, enhancing patient care, and determining a patient's health status. …”
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Machine Learning Algorithm for Assessing Photovoltaic Panels Partial Shading Losses based on Inverter Data by Armando Luís Sousa Araujo, Tiago Francisco Pires

“…These algorithms recognise similarities and patterns using expected and measured power data. …”
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Short-Term Electric Load Forecasting for an Industrial Plant Using Machine Learning-Based Algorithms by Oğuzhan Timur, Halil Yaşar Üstünel

“…Recent studies have emphasized the pervasive utilization of machine learning-based algorithms in the field of electric load forecasting for industrial plants. …”
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A Survey on Machine Learning Enhanced Integrated Sensing and Communication Systems: Architectures, Algorithms, and Applications by Mikael Ade Krisna Respati, Byung Moo Lee

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The impact of cultural factors on digital marketing strategies with Machine learning and honey bee Algorithm (HBA) by Muhammad Khan, Masood Ahmad, Rakhmonov Dilshodjon Alidjonovich, Kalonov Mukhiddin Bakhritdinovich, Kurbanbekova Mohichehra Turobjonovna, Imomov Jamshidxon Odilovich

“…This paper analyses the impact of cultural factors on digital marketing strategies in Pakistan. Improvement of machine learning (ML) techniques combined with the Honey Bee Algorithm (HBA) has been incorporated for better solutions. …”
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Machine learning algorithms applied to the diagnosis of COVID-19 based on epidemiological, clinical, and laboratory data by Silvia Elaine Cardozo Macedo, Marina de Borba Oliveira Freire, Oscar Schmitt Kremer, Ricardo Bica Noal, Fabiano Sandrini Moraes, Mauro André Barbosa Cunha

“…Epidemiological, clinical, and laboratory data were processed by machine learning algorithms in order to identify patterns. …”
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Optimized machine learning algorithms with SHAP analysis for predicting compressive strength in high-performance concrete by Samuel Olaoluwa Abioye, Yusuf Olawale Babatunde, Oluwafikejimi Abigail Abikoye, Aisha Nene Shaibu, Bailey Jonathan Bankole

“…Abstract This research examines the application of eight different machine learning (ML) algorithms for predicting the compressive strength of high-performance concrete (HPC). …”
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Evaluating machine learning algorithms for energy consumption prediction in electric vehicles: A comparative study by Izhar Hussain, Kok Boon Ching, Chessda Uttraphan, Kim Gaik Tay, Adil Noor

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Exploring high opioid prescriptions among nephrologists in the United States using machine learning algorithms by Shivashankar Basapura Chandrashekarappa, Sulaf Assi, Manoj Jayabalan, Abdullah Al-Hamid, Dhiya Al-Jumeily

“…As these factors are complex in nature, understanding them requires machine learning approach. This study explored overprescribing opioids among nephrologists in the US using unsupervised machine learning algorithms. …”
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Investigating the performance of random oversampling and genetic algorithm integration in meteorological drought forecasting with machine learning by Tahsin Baykal, Özlem Terzi, Gülsün Yıldırım, Emine Dilek Taylan

“…However, traditional drought monitoring approaches are limited in dealing with data imbalances and capturing complex temporal patterns. Therefore, this study aims to evaluate the effectiveness of machine learning methods for meteorological drought estimation and to integrate Random Oversampling (ROS) and Genetic Algorithm (GA) methods to improve estimation accuracy. …”
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CIAO: A machine-learning algorithm for mapping Arctic Ocean Chlorophyll-a from space by Maria Laura Zoffoli, Vittorio Brando, Gianluca Volpe, Luis González Vilas, Bede Ffinian Rowe Davies, Robert Frouin, Jaime Pitarch, Simon Oiry, Jing Tan, Simone Colella, Christian Marchese

“…Furthermore, CIAO produced consistent spatial patterns without artifacts and provided more reliable Chl-a estimates in coastal waters, where other algorithms tend to overestimate. …”
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Investigation of Micro-Scale Damage and Weakening Mechanisms in Rocks Induced by Microwave Radiation and Their Associated Strength Reduction Patterns: Employing Meta-Heuristic Opti... by Zhongyuan Gu, Xin Xiong, Chengye Yang, Miaocong Cao

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Spoofing speech detection algorithm based on joint feature and random forest by Jiaqi YU, Zhihua JIAN, Jia XU, Lin YOU, Yunlu WANG, Chao WU

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Spoofing speech detection algorithm based on joint feature and random forest by Jiaqi YU, Zhihua JIAN, Jia XU, Lin YOU, Yunlu WANG, Chao WU

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Application of smart technologies for predicting soil erosion patterns by Rana Muhammad Adnan Ikram, Mo Wang, Hossein Moayedi, Atefeh Ahmadi Dehrashid, Shiva Gharibi, Jing-Cheng Han

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Evaluation of the Proposed Hand Vein Authentication System using Machine Learning by rajaa ahmed, Ziyad Tariq Mustafa Al-Ta’i

“…The features are extracted through PCA Net for acquiring the most distinctive attributes of hand veins. The different machine learning algorithms used in this evaluation for classification of the extracted features include SVM, Logistic Regression, and Naive Bayes. …”
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T‐SNERF: A novel high accuracy machine learning approach for Intrusion Detection Systems by Mohamed Hammad, Nabil Hewahi, Wael Elmedany

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