Follow-Up and Risk Assessment in Patients with Myocardial Infarction Using Artificial Neural Networks by Tatjana Gligorijević, Zoran Ševarac, Branislav Milovanović, Vlado Đajić, Marija Zdravković, Saša Hinić, Marina Arsić, Milica Aleksić

“…Artificial neural networks (ANNs) are machine learning technique, inspired by the principles found in biological neurons. …”
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Damage Identification for Large Span Structure Based on Multiscale Inputs to Artificial Neural Networks by Wei Lu, Jun Teng, Yan Cui

“…A methodology to combine the local and global measurements in noisy environments based on artificial neural network is proposed in this paper. For a real large span structure, the capacity of the methodology is validated, including the decision on damage placement, the discussions on the number of the sensors, and the optimal parameters for artificial neural networks. …”
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Forecasting Türkiye's Paper and Paper Products Sector Import Using Artificial Neural Networks by Kamil Abdullah Eşidir, Yunus Emre Gür

“…This study aims to forecast the imports of the Turkish paper sector for the period from April 2023 to March 2024 using two artificial neural network (ANN) models: Multilayer Perceptron (MLP) and Radial Basis Function (RBF). …”
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Mortality Predicted Accuracy for Hepatocellular Carcinoma Patients with Hepatic Resection Using Artificial Neural Network by Herng-Chia Chiu, Te-Wei Ho, King-Teh Lee, Hong-Yaw Chen, Wen-Hsien Ho

“…The aim of this present study is firstly to compare significant predictors of mortality for hepatocellular carcinoma (HCC) patients undergoing resection between artificial neural network (ANN) and logistic regression (LR) models and secondly to evaluate the predictive accuracy of ANN and LR in different survival year estimation models. …”
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Application of artificial neural networks for predictive model of municipal solid waste collection in tourist cities by T. Kridakorn Na Ayutthaya, N. Jakrawatana, D. Rinchumphu, V. Owatsakul

Subjects: “…artificial neural networks (ann)…”
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Optimization of Neurons Number in Artificial Neural Network Model for Predicting the Power Production of PV Module by Hussain Hamdi Khalaf, Ali Nasser Hussain, Zuhair S. Al-Sagar, Abdulrahman Th. Mohammad, Hilal A. Fadhil

“… In this work, an Artificial Neural Network (ANN) with a backward-propagation technique was used to predict the power generation of the Photovoltaic (PV) module in weather conditions of Baghdad city-Iraq. …”
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Vibration Reliability Analysis of Drum Brake Using the Artificial Neural Network and Important Sampling Method by Zhou Yang, Unsong Pak, Cholu Kwon

“…This research aims to evaluate the calculation accuracy and efficiency of the artificial neural network-based important sampling method (ANN-IS) on reliability of structures such as drum brakes. …”
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Evaluation the efficiency of using Artificial Neural Networks in predicting meteorological droughts in north-west of Iran by Arash malekian, mahro dehbozorgi, Amir hoshang ehsani

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Generalization of artificial neural network for predicting methane production in laboratory-scale anaerobic bioreactor landfills by M.J. Zoqi

“…Implementation of artificial neural networks for modeling and prediction of this process still remains challenging. …”
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Prosthetic Hand Based on Human Hand Anatomy Controlled by Surface Electromyography and Artificial Neural Network by Larisa Dunai, Isabel Seguí Verdú, Dinu Turcanu, Viorel Bostan

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Artificial Neural Networks as Digital Twins for Whispering Gallery Mode Optical Sensors in Robotics Applications by Amir R. Ali, Mohamed W. A. Ramadan

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Operation of Hydroelectric Power Plants, Dam Reservoirs, and Energy Trade Using Artificial Neural Networks by Sibel Akkaya Oy, Serkan İnal, Ali Ekber Özdemir

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Artificial Neural Network Modeling for Spatial and Temporal Variations of Pore-Water Pressure Responses to Rainfall by M. R. Mustafa, R. B. Rezaur, H. Rahardjo, M. H. Isa, A. Arif

“…This paper evaluates the applicability of artificial neural network (ANN) technique for modeling soil pore-water pressure variations at multiple soil depths from the knowledge of rainfall patterns. …”
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Sensitivity Analysis of the Artificial Neural Network Outputs in Friction Stir Lap Joining of Aluminum to Brass by Mohammad Hasan Shojaeefard, Mostafa Akbari, Mojtaba Tahani, Foad Farhani

“…Scanning electron microscopy (SEM) and X-ray diffraction analysis were used to probe chemical compositions. An artificial neural network model was developed to simulate the correlation between the Friction Stir Lap Welding (FSLW) parameters and mechanical properties. …”
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Torque Prediction In Deep Hole Drilling: Artificial Neural Networks Versus Nonlinear Regression Model by Ngoc Hung- Chu, Hoai Nam- Nguyen, Van Du- Nguyen, Dang Binh- Nguyen

“…In this paper, we have developed a two-layer artificial neural network (ANN) model for training using the Levenberg-Marquardt algorithm to predict torque during deep drilling. …”
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Prediction of Load-Carrying Capacity in Steel Shear Wall with Opening Using Artificial Neural Network by E. Khalilzadeh Vahidi, M. M. Roshani

“…Load-carrying capacity of the SPSW is studied under static load using nonlinear geometrical and material analysis in ABAQUS and the obtained simulation results are verified. An artificial neural network (ANN) is proposed to model the effects of these parameters. …”
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Artificial neural network forecast application for fine particulate matter concentration using meteorological data by M. Memarianfard, A.M. Hatami, M. Memarianfard

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Applicability of Artificial Neural Networks to Predict Mechanical and Permeability Properties of Volcanic Scoria-Based Concrete by Aref M. al-Swaidani, Waed T. Khwies

“…The investigated concrete properties were the compressive strength, the water permeability, and the concrete porosity. Artificial neural networks (ANNs) were used for prediction of the investigated properties. …”
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Construction and Application of Recognition Model for Black-Odorous Water Bodies Based on Artificial Neural Network by Zhonghua Xu, Changguo Dai, Jing Wang, Lejun Liu, Lei Jiang

“…In the water environment, construction, and civil engineering industries, digital twins have gradually become a popular solution in recent years, and in digital twins, accurate data prediction and category recognition are important parts of it. Artificial neural network (ANN), a widely used data-driven model, can accurately identify nonlinear relationships in the water environment. …”
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Optimization and Prediction of Mechanical and Thermal Properties of Graphene/LLDPE Nanocomposites by Using Artificial Neural Networks by P. Noorunnisa Khanam, MA AlMaadeed, Sumaaya AlMaadeed, Suchithra Kunhoth, M. Ouederni, D. Sun, A. Hamilton, Eileen Harkin Jones, Beatriz Mayoral

“…These applied conditions are used to optimize the following properties: thermal conductivity, crystallization temperature, degradation temperature, and tensile strength while prediction of these properties was done through artificial neural network (ANN). The three first properties increased with increase in both screw speed and C-GNP content. …”
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