Artificial Neural Network (ANN) Based Fast and Accurate Inductor Modeling and Design by Thomas Guillod, Panteleimon Papamanolis, Johann W. Kolar

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Prediction of Compressive Strength Behavior of Ground Bottom Ash Concrete by an Artificial Neural Network by Kraiwut Tuntisukrarom, Raungrut Cheerarot

“…The objective of this work was to examine the compressive strength behavior of ground bottom ash (GBA) concrete by using an artificial neural network. Four input parameters, specifically, the water-to-binder ratio (WB), percentage replacement of GBA (PR), median particle size of GBA (PS), and age of concrete (AC), were considered for this prediction. …”
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Estimation of Maximum Daily Fresh Snow Accumulation Using an Artificial Neural Network Model by Gun Lee, Dongkyun Kim, Hyun-Han Kwon, Eunsoo Choi

“…For estimation of maximum daily fresh snow accumulation (MDFSA), a novel model based on an artificial neural network (ANN) was proposed. Daily precipitation, mean temperature, and minimum temperature were used as the input data for the ANN model. …”
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Artificial Neural Network-based Model for Predicting Cardiologists’ Over-apron Dose in CATHLABs by Reza Fardid, Fatemeh Farah, Hossein Parsaei, Hadi Rezaei, Mohammad Vahid Jorat

Subjects: “…artificial neural network…”
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Application of Functional Link Artificial Neural Network for Prediction of Machinery Noise in Opencast Mines by Santosh Kumar Nanda, Debi Prasad Tripathy

“…Functional link artificial neural network (FLANN), polynomial perceptron network (PPN), and Legendre neural network (LeNN) were used to predict the machinery noise in opencast mines. …”
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Predicting the correlation between neurological abnormalities and thyroid dysfunction using artificial neural networks by Dina Falah Noori Al-Sabak, Leila Sadeghi, Gholamreza Dehghan

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Analysis of the Severity of Accidents on Rural Roads Using Statistical and Artificial Neural Network Methods by Mohammad Habibzadeh, Pooyan Ayar, Mohammad Hassan Mirabimoghaddam, Mahmoud Ameri, Seyede Mojde Sadat Haghighi

“…In addition, two artificial neural network (ANN) models were developed using two kinds of learning methods to train neurons to select the best result. …”
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Inventory optimization model using Artificial Neural Network method and Continuous Review (s,Q) by Hanny Setyaningrum, Iphov Kumala Sriwana, Ilma Mufidah

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Evaluating Concrete Strength Under Various Curing Conditions Using Artificial Neural Networks by Al-Gburi Majid, Almssad Asaad, Al-Zuhairi Osamah Ibrahim

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Artificial neural networks and remote sensing in the analysis of the highly variable Pampean shallow lakes by Graciela Canziani, Rosana Ferrati, Claudia Marinelli, Federico Dukatz

Subjects: “…artificial neural network…”
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Evaluation Models for Soil Nutrient Based on Support Vector Machine and Artificial Neural Networks by Hao Li, Weijia Leng, Yibing Zhou, Fudi Chen, Zhilong Xiu, Dazuo Yang

“…In this paper, we present a series of comprehensive evaluation models for soil nutrient by using support vector machine (SVM), multiple linear regression (MLR), and artificial neural networks (ANNs), respectively. We took the content of organic matter, total nitrogen, alkali-hydrolysable nitrogen, rapidly available phosphorus, and rapidly available potassium as independent variables, while the evaluation level of soil nutrient content was taken as dependent variable. …”
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Characterization of the Collagen Extraction Manufacturing Process Using Markov Chains and Artificial Neural Networks by Rosa Trasvina-Osorio, Sergio Alonso-Romero, Juan de Anda-Suarez, Valentin Calzada-Ledesma, Javier Yanez-Mendiola, Luis Fernando Villanueva-Jimenez, Erick Rojas-Mancera

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RETRACTED: Artificial Neural Network-based fatigue behavior prediction of metals and composite materials by Koptiaev Dmitrii, Ivanov Yuri, Chashin Nikolai, Lupachev Daniil

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Artificial neural network based delamination prediction in composite plates using vibration signals by T. G. Sreekanth, M. Senthilkumar, S. Manikanta Reddy

“…In this research work, the supervised feed-forward multilayer back-propagation Artificial Neural Network (ANN) is used to determine the position and area of delaminations in GFRP plates using changes in natural frequencies as inputs. …”
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Using an Artificial Neural Network to Validate and Predict the Physical Properties of Self-Compacting Concrete by K. Thirumalai Raja, N. Jayanthi, Jule Leta Tesfaye, N. Nagaprasad, R. Krishnaraj, V. S. Kaushik

“…Many academics have been interested in using an artificial neural network (ANN) to forecast concrete strength in recent years. …”
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Enhancing climate action evaluation using artificial neural networks: An analysis of SDG 13 by Cosimo Magazzino, Zakaria Zoundi

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Modeling the effect of extrusion parameters on density of biomass pellet using artificial neural network by Abedin Zafari, Mohammad Hossein Kianmehr, Rahman Abdolahzadeh

Subjects: “…Biomass pellet. Density. Artificial neural network, , , , , , , , , ,…”
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An Artificial Neural Network Based Prediction of Mechanical and Durability Characteristics of Sustainable Geopolymer Composite by P. Manikandan, K. Selija, V. Vasugi, V. Prem Kumar, L. Natrayan, M. Helen Santhi, G. Senthil Kumaran

“…Furthermore, an artificial neural network prototype was proposed in this work to forecast the mechanical and durability properties of fiber reinforced FA-RHA blended geopolymer mortar. …”
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Experimental and Thermal Investigation on Powder Mixed EDM Using FEM and Artificial Neural Networks by Venkata N. Raju Jampana, P. S. V. Ramana Rao, A. Sampathkumar

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Modeling of Throughput in Production Lines Using Response Surface Methodology and Artificial Neural Networks by Federico Nuñez-Piña, Joselito Medina-Marin, Juan Carlos Seck-Tuoh-Mora, Norberto Hernandez-Romero, Eva Selene Hernandez-Gress

“…Moreover, the artificial neural network produces better predictions for data not utilized in the models construction. …”
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