Matrix‐based method for solving decision domains of neighbourhood multigranulation decision‐theoretic rough sets

Chen, Jiajun; Yu, Shaoming; Wei, Wenjie; Ma, Yan

doi:10.1049/cit2.12055

Cited by 15 publications

(14 citation statements)

References 26 publications

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“…These approaches have been extensively employed in numerical modeling, predicting interest fields and designing engineering structures. Therefore, intelligent modelling or intelligent design is gradually becoming a trend [47][48][49][50]. In future research, especially in the tool development phase, relevant algorithms can be introduced.…”

Section: Discussionmentioning

confidence: 99%

Research on the Modular Design and Application of Prefabricated Components Based on KBE

Li,

Feng,

Liu

et al. 2023

Buildings

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The design and production of prefabricated buildings pose challenges in achieving standardization, limiting their extensive adoption. In order to address issues of prefabricated components, such as the low reusability of design knowledge, limited standardization, and design disconnection, this paper adopted the prefabricated cantilevered structure components as the research object. It employs knowledge-based engineering (KBE) theory and secondary split modularization approach in conjunction with Revit secondary development technology to establish a modular design system. The system formalizes complex design knowledge into concise user interfaces and a logically clear programming language, ensuring the design system’s ease of use and accessibility. To validate the authenticity and applicability of the modular design system developed in this paper, a comparison is made between the traditional modeling tool and modular modeling tool. Through empirical analysis, the result indicates that the new tool proposed in this paper can enhance the efficiency of design professionals by 72.92%. Among these, the tool meets the modeling and design requirements of 96.1% of the prefabricated components in the project, making it highly suitable for the modeling and design process of the vast majority of prefabricated components. Therefore, this design approach, which integrates KBE and three-dimensional geometric technology, makes the modular design of prefabricated cantilevered structural components feasible, providing a reference for future research in the design of other prefabricated components.

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Section: Discussionmentioning

confidence: 99%

Research on the Modular Design and Application of Prefabricated Components Based on KBE

Li,

Feng,

Liu

et al. 2023

Buildings

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“…Therefore, in this paper, we used the enhanced particle swarm optimization algorithm to fine-tune these parameters. According to the principle of the particle swarm optimization algorithm [30,31], the initial position, velocity, particle range, and expected fitness value for single-factor optimization can be iteratively calculated to obtain the optimal value. In this part, the optimization of the two factors, weight and threshold, may be difficult due to the different value ranges of the two factors [32].…”

Section: Optimized Bp Neural Network Prediction Modelmentioning

confidence: 99%

Studying Corrosion Failure Prediction Models and Methods for Submarine Oil and Gas Transport Pipelines

Cui,

Wu,

et al. 2023

Applied Sciences

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To predict the corrosion failure of carbon steel oil and gas pipelines more accurately, a new corrosion failure prediction model for submarine oil and gas transport pipelines was constructed. A corrosion failure prediction management system was also developed based on the constructed model. To construct the model, corrosion experiments were carried out to analyze the influences of temperature, partial pressure of CO2, pH value, and flow rate acting on the corrosion rate. Based on the analysis results and the corrosion experiment data, a new corrosion failure prediction model containing the time and flow rate for oil and gas pipelines was constructed. The model is based on the existing corrosion prediction model and has a determination coefficient, R2, of 0.9573, which indicates good prediction accuracy. A machine learning prediction model was also used to predict, and the prediction results are compared with that of the proposed model, which further verifies the accuracy and feasibility of the proposed model. A corrosion failure prediction management system for carbon steel oil and gas pipelines was developed based on the constructed model, which makes corrosion failure prediction more convenient and faster and provides a reference for the accurate prediction and efficient control of oil and gas pipeline corrosion failure.

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“…Information data processing is also a very important stage. Good information processing technology can provide us with great help in different areas, such as in using deep nonlinear state space models [ 50 ], end-to-end dual stream convolutional neural networks [ 51 ], quotient space theory [ 52 ], and fusing MG-DTRS and NRS methods [ 53 ]. Currently, few scholars have combined quasi-zero stiffness vibration sensing and energy harvesting to study the measurement of absolute motion and the collection of vibrational energy.…”

Section: Introductionmentioning

confidence: 99%

Quasi-Zero Stiffness Vibration Sensing and Energy Harvesting Integration Based on Buckled Piezoelectric Euler Beam

Tuo,

Xu,

et al. 2023

Sensors

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This paper presents a novel quasi-zero stiffness vibration sensing and energy harvesting integration system for absolute displacement measurements based on a buckled piezoelectric Euler beam (BPEB) with quasi-zero stiffness (QZS) characteristics. On one hand, BPEB provides negative stiffness to the system, thus creating a vibration-free point within the system and transforming the absolute displacement measurement problem into a relative motion sensing problem. On the other hand, during the measurement process, the BPEB collects the vibration energy from the system, which can provide electrical energy for low-power relative motion sensing devices and remarkably suppress the frequency range of the jump phenomenon, thereby further expanding the frequency domain measurement range of the sensing system. The research results have shown that this system can measure the absolute motion signal of the tested object in low-frequency vibration with small excitation. By adjusting parameters such as the force–electric coupling coefficient and damping ratio, the measurement accuracy of the sensing system can be improved. Furthermore, the system can convert the mechanical energy of vibrations into electrical energy to power the surrounding low-power sensors or provide partial power. This could potentially achieve self-powering integrated quasi-zero stiffness vibration sensing, offering another approach and possibility for the automation development in wireless sensing systems and the Internet of Things field.

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Matrix‐based method for solving decision domains of neighbourhood multigranulation decision‐theoretic rough sets

Cited by 15 publications

References 26 publications

Research on the Modular Design and Application of Prefabricated Components Based on KBE

Research on the Modular Design and Application of Prefabricated Components Based on KBE

Studying Corrosion Failure Prediction Models and Methods for Submarine Oil and Gas Transport Pipelines

Quasi-Zero Stiffness Vibration Sensing and Energy Harvesting Integration Based on Buckled Piezoelectric Euler Beam

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