Residential Building Renovation Considering Energy, Carbon Emissions, and Cost: An Approach Integrating Machine Learning and Evolutionary Generation by Rudai Shan, Wanyu Lai, Huan Tang, Xiangyu Leng, Wei Gu

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Assessment of the Level of Financial Inclusion of Women in Kazakhstan: An Empirical Analysis of Structural Factors by A. A. Kireyeva, M. T. Kurmasheva

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Enhancing Tire Condition Monitoring through Weightless Neural Networks Using MEMS-Based Vibration Signals by Siddhant Arora, Sridharan Naveen Venkatesh, Vaithiyanathan Sugumaran, Anoop Prabhakaranpillai Sreelatha, Vetri Selvi Mahamuni

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A Machine Learning-Based Parameterized Tropical Cyclone Precipitation Model by Yi Lu, Jie Yin, Peiyan Chen, Hui Yu, Sirong Huang

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An integrated machine learning and fractional calculus approach to predicting diabetes risk in women by David Amilo, Khadijeh Sadri, Evren Hincal, Muhammad Farman, Kottakkaran Sooppy Nisar, Mohamed Hafez

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Spatio-Temporal Habitat Dynamics of Migratory Small Yellow Croaker (<i>Larimichthys polyactis</i>) in Hangzhou Bay, China by Xiangyu Long, Dong Wang, Pengbo Song, Mengwen Han, Rijin Jiang, Yongdong Zhou

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A machine learning model for early detection of sexually transmitted infections by Juma Shija, Judith Leo, Elizabeth Mkoba

“…The dataset was split into a 70%:15%:15% ratio for training, testing, and validation, respectively, and five machine learning algorithms were evaluated: AdaBoost, Support Vector Machine, Random Forest, Decision Tree, and Stochastic Gradient Descent. …”
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Performance Evaluation of Robotic Harvester with Integrated Real-Time Perception and Path Planning for Dwarf Hedge-Planted Apple Orchard by Tantan Jin, Xiongzhe Han, Pingan Wang, Yang Lyu, Eunha Chang, Haetnim Jeong, Lirong Xiang

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Incorporation of explainable artificial intelligence in ensemble machine learning-driven pancreatic cancer diagnosis by Faisal Abdulaziz Almisned, Natacha Usanase, Dilber Uzun Ozsahin, Ilker Ozsahin

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Impacts of farming and herding activities on land use and land cover changes in the north eastern corridor of Ghana: A comprehensive analysis by Nanii Yenibehit, Abubakari Abdulai, Joseph Amikuzuno, James Kofi Blay

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Hybrid Model for 6G Network Traffic Prediction and Wireless Resource Optimization by Mohammed Anis Oukebdane, A. F. M. Shahen Shah, Md Baharul Islam, John Ekoru, Milka Madahana

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Detection and Analysis of Malicious Software Using Machine Learning Models by Selman Hızal, Ahmet Öztürk

“…Our analysis encompasses binary and multi-class classification tasks under various experimental conditions, including percentage splits and 10-fold cross-validation. The evaluated algorithms include Random Tree (RT), Random Forest (RF), J-48 (C4.5), Naive Bayes (NB), and XGBoost. …”
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Sysmon event logs for machine learning-based malware detection by Riki Mi’roj Achmad, Dyah Putri Nariswari, Baskoro Adi Pratomo, Hudan Studiawan

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Mapping Antarctic Blue Ice Areas With Sentinel-2A/B Images and LightGBM Model by Xiaolong Teng, Jiahui Xu, Xiangbin Cui, Guitao Shi, Zhengyi Hu, Qingyu Gu, Bailang Yu, Jianping Wu, Yan Huang

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Immune status assessment based on plasma proteomics with meta graph convolutional networks by Min Zhang, Nan Xu, Qi Cheng, Jing Ye, Shiwei Wu, Haoliang Liu, Chengkui Zhao, Lei Yu, Weixing Feng

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Converging efficiency: Computational and fractal insights into parallel non-linear schemes by Mudassir Shams, Nasreen Kausar, Ali Akgül, Tonguç Çağın

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Predicting forest above-ground biomass using SAR imagery and GEDI data through machine learning in GEE cloud by Chiranjit Singha, Kishore Chandra Swain, Satiprasad Sahoo, Ayad M. Fadhil Al-Quraishi, Joseph Omeiza Alao, Hussein Almohamad, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo

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Lightweight Deepfake Detection Based on Multi-Feature Fusion by Siddiqui Muhammad Yasir, Hyun Kim

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Multi-scenario Dynamic Simulation and Optimization of Urban Ventilation Environment: A Case Study of Taiyuan Metropolitan Area by Junda HUANG, Yuncai WANG

“…Then, a prediction model is constructed based on the random forest algorithm. The land use types and ventilation environment of multiple scenarios in 2010 and 2020 are input into the validated prediction model to simulate changes in the future ventilation environment. …”
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Enhancing liver disease diagnosis with hybrid SMOTE-ENN balanced machine learning models—an empirical analysis of Indian patient liver disease datasets by Ritu Rani, Garima Jaiswal, Nancy, Lipika, Shashi Bhushan, Fasee Ullah, Prabhishek Singh, Manoj Diwakar, Manoj Diwakar

“…Immediate action is necessary for timely diagnosis of the ailment before irreversible damage is done.MethodsThe work aims to evaluate some of the traditional and prominent machine learning algorithms, namely, Logistic Regression, K-Nearest Neighbor, Support Vector Machine, Gaussian Naïve Bayes, Decision Tree, Random Forest, AdaBoost, Extreme Gradient Boosting, and Light GBM for diagnosing and predicting chronic liver disease. …”
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