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ANN model
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This study seeks to introduce a more comprehensive assessment method than previous endeavors, particularly concerning the bond strength of FRP bars with various surface types within concrete, spanning normal, high-strength, and ultra-high-strength concrete.
16p
vithomson
02-07-2024
0
0
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In this study, a surrogate model based on artificial neural networks (ANN) will be established to predict the mechanical behaviors of the plastic Primitive TPMS reinforced beams. Finite element analysis (FEA) simulation results of different numbers of reinforcement layers and volume fractions were adopted as the model data, the robust model have been owing to a hyperparameter tuning investigation.
10p
dathienlang1012
03-05-2024
5
0
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The appropriate number of neurons in the hidden layer was determined by feature testing of the fit of the weights, and the threshold of the synapse was perfected by testing the features during training.
11p
viellison
06-05-2024
3
1
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The purpose of this article is to analyze the performance of companies in the slaughterhouse industry in health and safety issues. The research method is quantitative modeling. The main research technique uses a mixed method based on multi-attribute utility method (MAUT) and artificial neural networks (ANN). The research object is 34 slaughterhouse companies located in Southern Brazil. Then, we ranked the companies and modeled their decision trees using the MAUT method.
9p
longtimenosee10
26-04-2024
2
1
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In this study, we mapped and evaluated LULC changes in Huong Hoa district, Quang Tri province, over a period of 10 years based on Landsat 8 satellite image data processed on ArcGIS software. On that basis, we carried out the simulation of the LULC change for 2033 using the QGIS MOLUSCE plugin.
13p
viritesh
02-04-2024
7
1
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This article presents the results of improving an artificial neural network (ANN) to predict the tool wear in high-speed dry turning of SKD11 steel. The original ANN was a backpropagation (BPN) model with the Gradient Descent algorithm (GD). In the improved model, so-called ANN-CS, some parameters were optimized by the Cuckoo search algorithm (CS).
15p
vibego
02-02-2024
2
1
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This study was conducted to build an early forecast model for the dengue epidemic using an artificial neural network (ANN) in Vung Tau City in Ba Ria - Vung Tau Province. Weather factors (temperature, precipitation, humidity, wind speed) were all correlated with the number of dengue cases (p
9p
vikissinger
21-12-2023
1
1
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Bilateral breast cancer (BBC), as well as ovarian cancer, are significantly associated with germline deleterious variants in BRCA1/2, while BRCA1/2 germline deleterious variants carriers can exquisitely benefit from poly (ADP-ribose) polymerase (PARP) inhibitors. However, formal genetic testing could not be carried out for all patients due to extensive use of healthcare resources, which in turn results in high medical costs.
11p
vileonardodavinci
23-12-2023
11
4
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In this article, an Artificial Neural Network (ANN)-based model for daily global solar radiation prediction is proposed. This model is trained with a backpropagation algorithm and make prediction using meteorological variables as inputs.
6p
vijeff
01-12-2023
4
3
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Continued part 1, part 2 of ebook "Sustainable construction and building materials: Select proceedings of ICSCBM 2018" provides readers with contents including: rice husk ash (RHA) - the future of concrete; effect of nano-silica and GGBS on the strength properties of fly ash-based geopolymers; compressive strength prediction of high-strength concrete using regression and ANN models; prediction of compressive strength of high-volume fly ash concrete using artificial neural network;...
446p
dangsovu
20-10-2023
8
5
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This paper develops an Artificial Neural Network (ANN) model based on 96 experimental data to forecast the dynamic modulus of asphalt concrete mixtures. The accuracy of the models was assessed using numerous performance indexes such as the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and coefficient of determination (R2).
10p
visharma
20-10-2023
3
3
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In this study, an artificial neural network-based Bayesian regularization (ANN) model is proposed to predict the compressive strength of concrete. The database in this study includes 208 experimental results synthesized from laboratory experiments with 9 input variables related to temperature change and design material composition.
13p
visharma
20-10-2023
5
4
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This paper presents the results of applying the Artificial Neural Network (ANN) model in determining pile bearing capacity. The traditional methods used to calculate the bearing capacity of piles still have many disadvantages that need to be overcome such as high cost, complicated calculation, time-consuming.
8p
visharma
20-10-2023
5
4
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This study aims to compare and contrast the performance of Artificial neural network (ANN) and Decision Tree (DT) methods in predicting the compressive strength and slump values of concrete samples. Experimental data used for model building and comparison were obtained from a previous research project.
9p
vifriedrich
30-08-2023
5
3
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Using a data-driven approach to study and predict the shear strength of slender steel fiber reinforced concrete beams has great applicability for the design and construction process. Based on the data-driven approach, an Artificial Neural Network (ANN) model with some hyperparameters optimized by Particle Swarm Optimization (PSO) algorithm is successfully built.
12p
viberkshire
09-08-2023
8
4
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Ebook "Marketing research (8th edition)" continues to provide readers with a “nuts and bolts” introduction to the field of marketing research. Intended for readers with no prior background in marketing research, the book teaches the basic fundamental statistical models needed to analyze market data. This new edition continues with the successful condensed and streamlined organization as the previous edition. An integrated case study throughout the text helps readers relate the material to the real world and their future careers.
499p
tichhythan
17-08-2023
16
10
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This paper presents the algorithms for training an artificial neural network (ANN) for regression analysis; the algorithm is based on the generalized delta rule. The training method of a simple neuron model and an ANN model are presented and generalized. The models are then programed in Visual C# .NET and applied to predict the compressive strength of concrete mixes. Three datasets, collected from the literature, are used to demonstrate the applications of the models.
7p
nhanchienthien
25-07-2023
5
4
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The impact of different rice husk ash contents (5, 10, 20%) on mortar strength is examined at different elevated temperatures (150, 300, 450, 750oC). Based on a 45 experimental result data set, three machine learning algorithms including the Artificial Neural Network (ANN), the Least Squares Support Vector Regression (LS-SVR) and the Multivariate Adaptive Regression Splines (MARS) have been used to model the functional relationship between the mixture components and the compressive strength.
10p
nhanchienthien
25-07-2023
6
4
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The paper "Artificial neural network for regression analysis developed in excel VBA: A case study in pile bearing capacity prediction" aims at developing an artificial neural network (ANN) for regression analysis. The ANN model is developed in Excel Visual Basic for Applications (VBA) to facilitate its practical implementations. The capability of the developed ANN program has been tested with the task of pile bearing capacity prediction.
7p
nhanchienthien
25-07-2023
10
5
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The assessment of financial health of a company plays an important role in helping stakeholders making their decisions. There have been many tools to assess the financial situation, the use of artificial neural network has been recently applied widely and shown certain advantages. Artificial neural network (ANN) are information processing model, which were studied by the nervous system of the organism, including large numbers of neurons linked to process the information.
8p
nhanchienthien
25-07-2023
9
4
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