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

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Biocomposite’s Multiple Uses for a New Approach in the Diagnosis of Parkinson’s Disease Using a Machine Learning Algorithm by Abdallah Al-Husban, Mustafa Mahdi Abdulridha, A. A. Hamad Mohamad, Abdelrahman Mohamed Ibrahim

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Unknown IoT Device Identification Models and Algorithms Based on CSCL-Siamese Networks and Weighted-Voting Clustering Ensemble by Junhao Qian, Wenyu Zheng, Xulin Lu, Zhihua Li

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Energy Scheduling of Hydrogen Hybrid UAV Based on Model Predictive Control and Deep Deterministic Policy Gradient Algorithm by Haitao Li, Chenyu Wang, Shufu Yuan, Hui Zhu, Bo Li, Yuexin Liu, Li Sun

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Ecological Suitability Assessment Methods of Waste Pile-Up along Railway Routes Based on Machine Learning Algorithms by Cuicui Ji, Zaoyang Huang, Xiangjun Pei, Bin Sun, Lichuan Chen, Dan Liang, Yanfei Kang

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Adoption of K-means clustering algorithm in smart city security analysis and mythical experience analysis of urban image. by Haotong Han

“…<h4>Objective</h4>An information security evaluation model based on the K-Means Clustering (KMC) +  Decision Tree (DT) algorithm is constructed, aiming to assess its value in evaluating smart city (SC) security. …”
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An Assembled Feature Attentive Algorithm for Automatic Detection of Waste Water Treatment Plants Based on Multiple Neural Networks by Cong Li, Zhengchao Chen, Zhuonan Huang, Yue Shuai, Shaohua Wang, Xiangkun Qi, Jiayi Zheng

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ExAq-MSPP: An Energy-Efficient Mobile Sink Path Planning Using Extended Aquila Optimization Algorithm by S. Sangeetha, T. Aruldoss Albert Victoire, Manoharan Premkumar, Ravichandran Sowmya

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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

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Revolutionizing proton exchange membrane fuel cell modeling through hybrid aquila optimizer and arithmetic algorithm optimization by Manish Kumar Singla, S. A. Muhammed Ali, Ramesh Kumar, Pradeep Jangir, Mohammad Khishe, G. Gulothungan, Haitham A. Mahmoud

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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

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Sex estimation with parameters of the facial canal by computed tomography using machine learning algorithms and artificial neural networks by Yusuf Secgin, Seren Kaya, Oğuzhan Harmandaoğlu, Oğuzhan Öztürk, Deniz Senol, Ömer Önbaş, Nihat Yılmaz

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Cervical Cancer Prediction Based on Imbalanced Data Using Machine Learning Algorithms with a Variety of Sampling Methods by Mădălina Maria Muraru, Zsuzsa Simó, László Barna Iantovics

“…Cervical cancer affects a large portion of the female population, making the prediction of this disease using Machine Learning (ML) of utmost importance. ML algorithms can be integrated into complex, intelligent, agent-based systems that can offer decision support to resident medical doctors or even experienced medical doctors. …”
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The Impact of Image Spatial Resolution and Machine Learning Algorithm on Urban Vegetation Classification: Focus on Data Loss and Misclassification by Alexander Takele Muleta, Julius Bamah, Shirley Bushner, Oz Kira

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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

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Prediction of barite scale formation and inhibition in hydrocarbon reservoirs using AI modeling: Focus on different optimization algorithms by Ouafa Belkacem, Ahmed Rezrazi, Kamel Aizi, Lokmane Abdelouahed, Maamar Laidi, Abdelhafid Touil, Leila Cherifi, Salah Hanini

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Effect of the exposure to brominated flame retardants on hyperuricemia using interpretable machine learning algorithms based on the SHAP methodology. by Yu Cai, Xi-Ru Huang, Sheng-Jia Wang, Ying-Chao Liang, De-Liang Liu, Shu-Fang Chu, Hui-Lin Li

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Machine learning algorithms to predict heart failure with preserved ejection fraction among patients with premature myocardial infarction by Jing-xian Wang, Chang-ping Li, Zhuang Cui, Yan Liang, Yu-hang Wang, Yu Zhou, Yin Liu, Jing Gao, Jing Gao, Jing Gao, Jing Gao

“…The final model included ten variables, which were Brain natriuretic peptide (BNP) &gt; 100pg/ml, SYNTAX Score &gt; 14.5, Age, Monocyte to Lymphocyte Ratio (MLR) &gt; 0.3, Hematocrit (HCT) &lt; 45%, Heart rate (HR) &gt; 75 bpm, Body Mass Index (BMI) ≥ 24 kg/m2, C-reactive Protein to Lymphocyte Ratio (CLR) &gt; 2.83, Hypertension and Fibrinogen (Fg) &gt; 4 g/L.ConclusionsThe explainable prediction model established based on the XGBoost algorithm can accurately predict the risk of in-hospital HFpEF in PMI patients and is available at https://hfpefpmi.shinyapps.io/apppredict/. …”
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Nutritional intake of micronutrient and macronutrient and type 2 diabetes: machine learning schemes by Mohammad Rashidmayvan, Amin Mansoori, Elahe Derakhshan-Nezhad, Davoud Tanbakuchi, Fatemeh Sangin, Maryam Mohammadi-Bajgiran, Malihehsadat Abedsaeidi, Sara Ghazizadeh, MohammadReza Mohammad Taghizadeh Sarabi, Ali Rezaee, Gordon Ferns, Habibollah Esmaily, Majid Ghayour-Mobarhan

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Integrating Hyperspectral, Thermal, and Ground Data with Machine Learning Algorithms Enhances the Prediction of Grapevine Yield and Berry Composition by Shaikh Yassir Yousouf Jewan, Deepak Gautam, Debbie Sparkes, Ajit Singh, Lawal Billa, Alessia Cogato, Erik Murchie, Vinay Pagay

“…The use of multimodal data and machine learning (ML) algorithms could overcome these challenges. Our study aimed to assess the potential of multimodal data (hyperspectral vegetation indices (VIs), thermal indices, and canopy state variables) and ML algorithms to predict grapevine yield components and berry composition parameters. …”
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