ANN method
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In this study, the simultaneous determination of Co, Cd, Ni, Cu, and Pb was carried out as a color complex with 4-(2-pyridylazo) resorcinol in an aqueous solution under the assesting of machine learning. A partial least-squares multivariate linear regression and artificial neuron network for the analysis of mixtures of metals were developed. MATLAB is a powerful software machine learning program that was used to support matrix calculations and displays.
8p visergeyne 18-06-2024 0 0 Download
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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 Download
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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 Download
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Residual stresses play a significant role in the properties and performance of epoxy-based coatings, with their origins rooted in various factors encountered during production and application. This study focuses on quantifying residual stresses in three distinct epoxy-based coatings, commonly used as linings for crude oil storage tanks, namely, pure epoxy, Novolac epoxy, and glass-flake-reinforced epoxy.
8p vimichaelfaraday 28-12-2023 8 4 Download
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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 Download
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In the present study, two chemometric techniques, Artificial Neural Network (ANN) and Partial Least Square-Discrimination Analysis (PLSDA) have been assessed for their efficiencies for classification. Here, UV spectroscopic data are used as input.
6p viisac 23-09-2023 3 1 Download
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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 Download
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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 Download
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Short-term load forecasting of buildings based on artificial neural network and clustering technique
In this paper, we propose an artificial neural network (ANN) based method to predict the energy use in campus buildings in short-term time series from one hour up to one week. The proposed method analyzes and extracts the features from the historical data of load and temperature to generate the prediction of future energy consumption in the building based on sparsified K-means. To evaluate the performance of the proposed approach, historical load data in hourly resolution collected from the campus buildings in Chonnam National University were used.
13p nhanchienthien 25-07-2023 8 4 Download
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The QSPR modeling is popularly used in many fields as in silico approach for predicting properties of chemical compounds based on the relationships between the structural characteristics and the properties.
11p viargus 03-03-2023 2 2 Download
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Applying machine learning method in neutron and gamma identification according to their pulse shapes
Neutron and gamma’s time of flight from a Cf252 source have been measured to identify them accordingly. Their pulse shape characteristics measured by EJ-299-33 scintillator were used to train an artificial neural network (ANN) in a machine learning method.
6p visnape 30-01-2023 8 4 Download
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This paper uses the data obtained in the actual blasting of the Deo Ca tunnel (39 datasets) to build the computational and prediction models for the area of the tunnel face after blasting by two methods, the multiple linear regression analysis method and the method of using artificial neural network (ANN).
10p vibentley 08-09-2022 14 5 Download
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This paper presents a method to determine the capacity and location of compensating capacitors to reduce power loss and improve voltage quality in the Microgrid. At each bus location, the compensating capacitor capacity is varied to determine the bus location and capacitor capacity.
9p vibentley 08-09-2022 13 4 Download
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This paper proposes a new approach using one of the applications of deep learning models to predict river water levels in irrigation systems. A predictive model has been developed based on the Long Short-Term Memory (LSTM) neural networks to forecast the water levels upstream of Tranh Culvert in the Bac Hung Hai irrigation system in Vietnam.
8p visherylsandber 04-07-2022 13 2 Download
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The paper applied seismic attribute analysis method combined with artificial neural network (ANN) and well data to predict the distribution of sandstones reservoirs of Lower Miocene sediments in the Northeastern Bach Ho oil field.
9p vinikolatesla 31-03-2022 11 2 Download
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Heterogeneous Fenton-like removal of Acid Red 17 (AR17) from aqueous solution was investigated. Feimpregnated nanoporous clinoptilolite (Fe-NP-Clin) was prepared by an impregnation method and used as a catalyst. A complete characterization including X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), inductively coupled plasma (ICP), and Brunauer–Emmett–Teller (BET) analyses was done to describe the physical and chemical properties of NP-Clin and Fe-NP-Clin samples.
17p langthannam 29-12-2021 12 0 Download
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This study aims to explore the approaches of population estimation of Rohingya migrants using remote sensing and machine learning. Two di®erent approaches of population estimation viz., (i) data-driven approach and (ii) satellite image-driven approach have been explored. A total of 11 machine learning models including Arti¯cial Neural Network (ANN) are applied for both approaches.
17p redemption 20-12-2021 9 0 Download
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Based on the value of mean squared error, absolute average deviation and coefficient of determination, the ANN model was found superior to DMD models in predicting the value of responses. The optimum composition of flour obtained using the DMD method was 69.44 g of PMF, 21 g of RLF and 9.56 g of MLF, whereas using the ANNGA technique, it was 68.25 g of PMF, 23.12 g of RLF and 8.63 g of MLF.
10p mudbound 10-12-2021 7 1 Download
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In this study, the stability constants (logB11) of twenty-eight new complexes between several ion metals and thiosemicarbazone ligands were predicted on the basis of the quantitative structure property relationship (QSPR) modeling. The stability constants were calculated from the results of the QSPR models. The QSPR models were built by using the multivariate least regression (QSPRMLR) and artificial neural network (QSPRANN)
15p viwilliamleiding 10-12-2021 13 1 Download
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Artificial neural networks (ANNs) have been applied successfully to virtually every problem in the predictions of the settlement. However, there is not much research on predicting the settlement over time. In this paper, an ANN model is developed and compared with two traditional methods (Asaoka method and the method of Asaoka combined with Polynomial) in predicting the settlement of two cases of road construction.
9p vicolinzheng 10-12-2021 10 1 Download