A machine learning based global simulation data mining approach for efficient design changes

Shao, Yanli; Liu, Yusheng; Ye, Xiaoping; Zhang, Shuting

doi:10.1016/j.advengsoft.2018.07.002

Cited by 12 publications

(3 citation statements)

References 24 publications

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“…This aforementioned pattern suggests that digital methods for validation have so far been considered primarily on a rather application-specific basis. When new methods are presented in these works, as in [115,117,119,125,[134][135][136], they mostly refer to the context of manufacturing, e.g., [96,104,106,107,109,126]. Considering the share of manufacturing within the entire overarching development process, this subtopic seems to be overrepresented in the given context.…”

Section: Validationmentioning

confidence: 99%

Digital Engineering Methods in Practical Use during Mechatronic Design Processes

Gerschütz

Sauer

Kormann

et al. 2023

Designs

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This work aims to evaluate the current state of research on the use of artificial intelligence, deep learning, digitalization, and Data Mining in product development, mainly in the mechanical and mechatronic domain. These methods, collectively referred to as “digital engineering”, have the potential to disrupt the way products are developed and improve the efficiency of the product development process. However, their integration into current product development processes is not yet widespread. This work presents a novel consolidated view of the current state of research on digital engineering in product development by a literature review. This includes discussing the methods of digital engineering, introducing a product development process, and presenting results classified by their individual area of application. The work concludes with an evaluation of the literature analysis results and a discussion of future research potentials.

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Section: Validationmentioning

confidence: 99%

Digital Engineering Methods in Practical Use during Mechatronic Design Processes

Gerschütz

Sauer

Kormann

et al. 2023

Designs

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“…Precision defines how reliable measurements are, although they are farther from the accepted value. The equation of precision is shown in Equation (2).…”

Section: Assessment Of Measuresmentioning

confidence: 99%

“…To discover; the relation and patterns in enormous datasets, sophisticated data analysis tools are being adopted and utilized for the extraction of data mining techniques [1]. Numerous theoretical and empirical research that demonstrate the benefits of the combination paradigm over separate classifier models have been published [2][3][4][5]. In recent years, ML has gained significant traction in a number of areas, including remote sensing, image categorization, and pattern identification.…”

Section: Introductionmentioning

confidence: 99%

Voting Combinations-Based Ensemble: A Hybrid Approach

Abro

Talpur

JUMANİ

et al. 2022

Celal Bayar Üniversitesi Fen Bilimleri Dergisi

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Machine learning (ML) is a prominent and extensively researched field in the artificial intelligence area which assists to strengthen the accomplishment of classification. In this study, the main idea is to provide the classification and analysis of ML and Ensemble Learning (EL) algorithms. To support this idea, six supervised ML algorithms, C4.5 (J48), K-Nearest Neighbor (KNN), Logistic Regression (LR), Support Vector Machine (SVM), Naive Bayes (NB) and One Rule (OneR) in addition the five UCI Datasets of ML Repository, are being applied that demonstrates the robustness and effectiveness of numerous approaches. In this paper, a voting-based ensemble classifier has been proposed along with two base learners (namely, Random Forest and Rotation Forest) to progress the performance. Whereas, for analytical procedures, significant parameters have been considered: Accuracy, Area under Curve (AUC), recall, precision, and F-measure values. Hence, the prime objective of this research is to obtain binary classification and efficiency by conducting the progress of ML and EL approaches. We present experimental outcomes that validate the effectiveness of our method to well-known competitive approaches. Image recognition and ML challenges, such as binary classification, can be solved using this method.

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An approach to user knowledge acquisition in product design

Tan

Zhang

2021

Advanced Engineering Informatics

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A machine learning based global simulation data mining approach for efficient design changes

Cited by 12 publications

References 24 publications

Digital Engineering Methods in Practical Use during Mechatronic Design Processes

Digital Engineering Methods in Practical Use during Mechatronic Design Processes

Voting Combinations-Based Ensemble: A Hybrid Approach

An approach to user knowledge acquisition in product design

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