Artificial neural network optimized by differential evolution for predicting diameters of jet grouted columns

Journal of Rock Mechanics and Geotechnical Engineering, Год журнала: 2021, Номер 13(6), С. 1500 - 1512

Опубликована: Сен. 14, 2021

A novel and effective artificial neural network (ANN) optimized using differential evolution (DE) is first introduced to provide a robust reliable forecasting of jet grouted column diameters. The proposed computational method adopts the DE algorithm tackle difficulties in training performance networks optimize four quintessential hyper-parameters (i.e. epoch size, number neurons hidden layer, layers, regularization parameter) that govern efficacy. This approach further enhanced by stochastic gradient optimization allow 'expensive' computation efforts. ANN-DE trained prepared grouting dataset, then verified compared with prevalent machine learning tools, i.e. support vector (SVM). results show that, outperforms existing methods for predicting diameter columns since it well balances efficiency model performance. Specifically, achieved root mean square error (RMSE) values 0.90603 0.92813 testing phases, respectively. corresponding were 0.8905 0.9006 ANN, then, 0.87569 0.89968 SVM, paradigm bound be useful solving various geotechnical engineering problems regardless multi-dimension nonlinearity.

Язык: Английский

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Safety prediction of shield tunnel construction using deep belief network and whale optimization algorithm

Automation in Construction, Год журнала: 2022, Номер 142, С. 104488 - 104488

Опубликована: Июль 19, 2022

Язык: Английский

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Multivariate cryptocurrency prediction: comparative analysis of three recurrent neural networks approaches

Journal Of Big Data, Год журнала: 2022, Номер 9(1)

Опубликована: Апрель 28, 2022

Abstract As a new type of currency introduced in the millennium, cryptocurrency has established its ecosystems and attracts many people to use invest it. However, cryptocurrencies are highly dynamic volatile, making it challenging predict their future values. In this research, we multivariate prediction approach three different recurrent neural networks (RNNs), namely long short-term memory (LSTM), bidirectional LSTM (Bi-LSTM), gated unit (GRU). We also propose simple layers deep architecture for regression task study. From experimental results on five major cryptocurrencies, i.e., Bitcoin (BTC), Ethereum (ETH), Cardano (ADA), Tether (USDT), Binance Coin (BNB), find that both Bi-LSTM GRU have similar performance terms accuracy. execution time, results, where is slightly better lower variation average.

Язык: Английский

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CBR Prediction of Pavement Materials in Unsoaked Condition Using LSSVM, LSTM-RNN, and ANN Approaches

International Journal of Pavement Research and Technology, Год журнала: 2023, Номер 17(3), С. 750 - 786

Опубликована: Фев. 13, 2023

Язык: Английский

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The potential of industrial waste: Electric arc furnace slag (EAF) as recycled road construction materials

Construction and Building Materials, Год журнала: 2023, Номер 368, С. 130393 - 130393

Опубликована: Янв. 17, 2023

Язык: Английский

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Intelligent prediction model of a polymer fracture grouting effect based on a genetic algorithm-optimized back propagation neural network

Tunnelling and Underground Space Technology, Год журнала: 2024, Номер 148, С. 105781 - 105781

Опубликована: Апрель 26, 2024

Язык: Английский

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Machine and deep learning-based prediction of flexural moment capacity of ultra-high performance concrete beams with/out steel fiber

Asian Journal of Civil Engineering, Год журнала: 2024, Номер 25(6), С. 4541 - 4562

Опубликована: Май 10, 2024

Язык: Английский

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Indirect estimation of resilient modulus (Mr) of subgrade soil: Gene expression programming vs multi expression programming

Structures, Год журнала: 2024, Номер 66, С. 106837 - 106837

Опубликована: Июль 1, 2024

Язык: Английский

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Improvement of flexural strength of concrete pavements using natural rubber latex

Construction and Building Materials, Год журнала: 2021, Номер 282, С. 122704 - 122704

Опубликована: Фев. 26, 2021

Язык: Английский

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Estimating unconfined compressive strength of unsaturated cemented soils using alternative evolutionary approaches

Transportation Geotechnics, Год журнала: 2021, Номер 29, С. 100591 - 100591

Опубликована: Июнь 1, 2021

Язык: Английский

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