Prediction of the Load-Bearing Behavior of SPSW with Rectangular Opening by RBF Network

Moradi, Mohammad Javad; Roshani, Mohammadmehdi; Shabani, Amirhosein; Kioumarsi, Mahdi

doi:10.3390/app10031185

Cited by 39 publications

(21 citation statements)

References 31 publications

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“…In this dataset, there are 12,589 records in the testing data and 113,297 records in the training data. Additionally, the same water quality dataset is predicted with the long short-term memory (LSTM) (Bi, Liu & Li, 2020) and the RBFNN models (Moradi et al, 2020), and the prediction results are compared with those of the enhanced semi-naive Bayesian prediction model. To quantitatively represent the prediction effects of the different algorithms, the root mean square error (RMSE) (Hyndman & Koehler, 2006), mean absolute percentage error (MAPE) (de Myttenaere et al, 2016) and mean absolute error (MAE) (Willmott & Matsuura (2005)) are used as error functions; they are described in Eqs.…”

Section: Results and Validation Single Pasture Prediction Evaluationmentioning

confidence: 99%

A novel dissolved oxygen prediction model based on enhanced semi-naive Bayes for ocean ranches in northeast China

Sun

Fan

2021

PeerJ Computer Science

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A challenge of achieving intelligent marine ranching is the prediction of dissolved oxygen (DO). DO directly reflects marine ranching environmental conditions. Through accurate DO predictions, timely human intervention can be made in marine pasture water environments to avoid problems such as reduced yields or marine crop death due to low oxygen concentrations in the water. We use an enhanced semi-naive Bayes model for prediction based on an analysis of DO data from marine pastures in northeastern China from the past three years. Based on the semi-naive Bayes model, this paper takes the possible values of a DO difference series as categories, counts the possible values of the first-order difference series and the difference series of the interval before each possible value, and selects the most probable difference series value at the next moment. The prediction accuracy is optimized by adjusting the attribute length and frequency threshold of the difference sequence. The enhanced semi-naive Bayes model is compared with LSTM, RBF, SVR and other models, and the error function and Willmott’s index of agreement are used to evaluate the prediction accuracy. The experimental results show that the proposed model has high prediction accuracy for DO attributes in marine pastures.

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Section: Results and Validation Single Pasture Prediction Evaluationmentioning

confidence: 99%

A novel dissolved oxygen prediction model based on enhanced semi-naive Bayes for ocean ranches in northeast China

Sun

Fan

2021

PeerJ Computer Science

View full text Add to dashboard Cite

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“…In recent years, artificial intelligence has been widely used in radiation-based measuring instruments [32][33][34][35][36][37][38][39]. In 1971, M.G.…”

Section: Group Methods Of Data Handling (Gmdh)mentioning

confidence: 99%

Feasibility Study of Using X-ray Tube and GMDH for Measuring Volume Fractions of Annular and Stratified Regimes in Three-Phase Flows

et al. 2021

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In this paper, the feasibility of using an X-ray tube instead of radioisotope sources for measuring volume fractions of gas, oil, and water in two typical flow regimes of three-phase flows, namely, annular and stratified, is evaluated. This study’s proposed detection system is composed of an X-ray tube, a 1 inch × 1 inch NaI detector, and one Pyrex-glass pipe to model different volume fractions for two flow regimes, annular and stratified. Group method of data handling (GMDH), a powerful regression tool, was also implemented to analyze the obtained data. The obtained results in this work indicate that a simple system based on an X-ray tube and just one NaI detector could be a potential alternative to radioisotope-based systems for separate measurements of gas, oil, and water volume fractions in annular and stratified flow regimes of a three-phase flow.

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“…These systems are information manager models inspired by the human brain. In nature, the performance of neural networks is determined by the way in which the components are interconnected [22]. Therefore, it is possible to construct an artificial structure in accordance with natural networks and determine the relationship between its components by adjusting the values of each connection, as the weight of the connection.…”

Section: Artificial Neural Networkmentioning

confidence: 99%

Predicting the Effect of Fly Ash on Concrete’s Mechanical Properties by ANN

et al. 2021

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Fly ash, as a supplemental pozzolanic material, reduces concrete’s adverse environmental footprint by decreasing the emission of carbon dioxide (CO2) during the cement manufacturing process. Fly ash, which is a waste material, can enhance both the mechanical characteristics and durability of concrete, and has the capability to play an important role in sustainable design. Considering the widespread interest in applying Fly ash, and despite research studies, the level of replacement is still unclear. In this paper, a novel method using artificial neural networks (ANN) is presented to predict concrete’s mechanical characteristics by adding Fly ash. In this regard, a host of available experimental data, such as the properties of Fly ash, along with concrete additives, was fed into an ANN model. Concrete samples’ tensile and compressive strengths, in addition to their modulus of elasticity, were defined as outputs. It was observed that the predicted outcomes agreed well with the experimental results. To further enhance the research outcomes, simple but practical equations are presented to assess the effect of using Fly ash on concrete’s mechanical characteristics.

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Prediction of the Load-Bearing Behavior of SPSW with Rectangular Opening by RBF Network

Cited by 39 publications

References 31 publications

A novel dissolved oxygen prediction model based on enhanced semi-naive Bayes for ocean ranches in northeast China

A novel dissolved oxygen prediction model based on enhanced semi-naive Bayes for ocean ranches in northeast China

Feasibility Study of Using X-ray Tube and GMDH for Measuring Volume Fractions of Annular and Stratified Regimes in Three-Phase Flows

Predicting the Effect of Fly Ash on Concrete’s Mechanical Properties by ANN

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