Concrete Compression Test Data Estimation Based on a Wavelet Neural Network Model

Wang, Haiying; Wang, Xinping; Wang, Chao; Xu, Jian

doi:10.1155/2019/4952036

Cited by 5 publications

(4 citation statements)

References 15 publications

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“…The state-of-the-art of computing research is an evolutionary and deep learning model approach due to evolutionary and deep learning models being more advanced to solve the computational problem than other approaches. The evolutionary algorithms that have been implemented are wavelet neural networks (WNN), genetic algorithm (GA), simulated annealing (SA), and fuzzy c-means clustering (FCM) [29]. The deep learning algorithm such as convolution neural network (CNN) was used by Deng et al [30] and Albawi et al [31].…”

Section: Artificial Intelligence Computational Model Of Vctmmentioning

confidence: 99%

Design and Evaluation of Virtual Compression Testing Machine Based on Multilayer Perceptron for Vocational-Education Virtual Laboratory

et al. 2023

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The weaknesses of Conventional Compression Testing Machines (CCTM) for student practicum are the high costs of procurement, maintenance, electricity, concrete materials, and human/equipment error factors. This research proposed of Virtual Compression Testing Machine (VCTM) based on Multilayer Perceptron that uses 2 hidden layers, 60 neurons with bagging, and other parameters of a Deep Neural Network with RMSE value of 4.738. The application of VCTM has been successfully carried out and there was no significant difference with CCTM. VCTM can be used for various types of concrete with high testing intensity. Lecturers and researchers can use VCTM to conduct research.

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Section: Artificial Intelligence Computational Model Of Vctmmentioning

confidence: 99%

Design and Evaluation of Virtual Compression Testing Machine Based on Multilayer Perceptron for Vocational-Education Virtual Laboratory

et al. 2023

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“…In addition, Behnood and Golafshani [24] used a multi-objective optimization method to determine the minimum error and developed a neural network model to evaluate the compressive strength of silica fume concrete. 2019, Wang et al [25] proposed a wavelet neural network for short-term evaluation of concrete compressive strength.…”

Section: Cement Compressive Strength Prediction Technologymentioning

confidence: 99%

A Global Study of Green Cement Intelligent Manufacturing Based on Artificial Intelligence

Binggang,

Jingbo,

Wanshun

et al. 2023

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This paper delves into the exploration of artificial intelligence (AI) applications in the cement industry, with a particular emphasis on the manufacturing of green cement. It investigates current situation and difficulties in the cement industry, such as the lack of self-developed software. Then, this paper suggests AI-based solutions to overcome these hurdles. The study discusses three key intelligent manufacturing technologies that have the potential to revolutionize the cement industry. These include the identification of abnormal working conditions, prediction of cement compressive strength, and the application of digital twin technology. Through various case studies, the transformative potential of these technologies is analyzed, providing a comprehensive understanding of their impact on the cement industry. This paper further examines the influence of green low-carbon intelligent manufacturing on China's cement production capacity. It highlights how the adoption of these technologies can lead to more sustainable and efficient practices in the cement industry. The study concludes with recommendations for the application of AI in cement and other process industries, emphasizing the need for embracing AI to enhance sustainability and efficiency. The overarching aim of this study is to illuminate the prospects of AI in augmenting the sustainability and efficiency of the cement industry, thereby contributing to the broader discourse on AI applications in industrial processes.

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“…Zhang et al 34 (1) Using the fuzzy c-mean (FCM) algorithm 35 to improve the ranging accuracy. (2) The weighted centroid positioning algorithm.…”

Section: Zhang and Huang 33mentioning

confidence: 99%

A quadratic weighted centroid algorithm for tunnel personnel positioning

Wang

Liang

et al. 2020

International Journal of Distributed Sensor Networks

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To improve the accuracy and generalization of tunnel personnel positioning systems, this article proposes a quadratic weighted centroid algorithm. By adopting a Gaussian filter model to improve the range accuracy of the received signal strength indicator algorithm and combining the centroid algorithm and weighting factor with a trilateration positioning model, a quadratic weighted centroid algorithm is proposed to improve the positioning accuracy of unknown positioning nodes. The key ideas behind the quadratic weighted centroid algorithm include an optimization of the received signal strength indicator range value scheme, a centroid algorithm based on trilateral measurement positioning, and a weighting factor to improve the positioning accuracy of the trilateral centroid positioning algorithm. Compared with the centroid algorithm, the Min-Max multilateration algorithm, and the weighted centroid based on distance algorithm, the simulation results showed that (1) the positioning performance of the quadratic weighted centroid algorithm was superior to the other three algorithms; (2) when the reference nodes were symmetrically arranged, the positioning accuracy was higher than a fold line layout; and (3) when the lateral reference node spacing was extended from 20 to 30 m, the average positioning error met positioning accuracy requirements, which could reduce overall system costs.

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Concrete Compression Test Data Estimation Based on a Wavelet Neural Network Model

Cited by 5 publications

References 15 publications

Design and Evaluation of Virtual Compression Testing Machine Based on Multilayer Perceptron for Vocational-Education Virtual Laboratory

Design and Evaluation of Virtual Compression Testing Machine Based on Multilayer Perceptron for Vocational-Education Virtual Laboratory

A Global Study of Green Cement Intelligent Manufacturing Based on Artificial Intelligence

A quadratic weighted centroid algorithm for tunnel personnel positioning

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