Intelligent Modeling; Single (Multi-layer perceptron) and Hybrid (Neuro-Fuzzy Network) Method in Forest Degradation (Case Study: Sari County) by somayeh mehrabadi

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Correlation of rivaroxaban solubility in mixed solvents for optimization of solubility using machine learning analysis and validation by Muteb Alanazi, Jowaher Alanazi, Tareq Nafea Alharby, Bader Huwaimel

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Quadcopter Trajectory Tracking Based on Model Predictive Path Integral Control and Neural Network by Yong Li, Qidan Zhu, Ahsan Elahi

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Food Sales Prediction Using MLP, RANSAC, and Bagging by Hussam Mezher Merdas, Ayad Hameed Mousa

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Role of denoisers in simulation-based inference from graph-structured data: a case study for position inference in an astroparticle detector by Venkat Roy, Aaron Higuera, Shixiao Liang, Christina Peters, Waheed U. Bajwa, Christopher D. Tunnell

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Methods for Constructing Artificial Neural Networks for Data Classification by L. V. Serebryanaya

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Investigation of Different Components of Steel Metal Utilizing Artificial Intelligence by Zainab L. H, Fatima Abd Naji

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Modelling Lithuanian family farms’ participation in agri-environmental subsidy schemes: a Neural Network Approach by Kristina Gesevičienė, Erika Besusparienė

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MDFGNN-SMMA: prediction of potential small molecule-miRNA associations based on multi-source data fusion and graph neural networks by Jianwei Li, Xukun Zhang, Bing Li, Ziyu Li, Zhenzhen Chen

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Utilizing the Novel Developed MLP Techniques to Survey Pile Subsidence via Optimization Algorithms by Augustinus Sieck, Graciela Daniels

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Evaluating Neural Network Performance in Predicting Disease Status and Tissue Source of JC Polyomavirus from Patient Isolates Based on the Hypervariable Region of the Viral Genome by Aiden M. C. Pike, Saeed Amal, Melissa S. Maginnis, Michael P. Wilczek

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A Hybrid Artificial Neural Network and Particle Swarm Optimization algorithm for Detecting COVID-19 Patients by Alla Ahmad Hassan, Tarik A Rashid

Subjects: “…Particle Swarm Optimization, Neural Networks, Logistic Regression, Nave Bayes Classifier, Multilayer Perceptron, Support Vector Machine, BF Tree, Bayesian Networks.…”
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Application of ensemble learning techniques to model the atmospheric concentration of SO2 by A. Masih

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