S. Barai - Academia.edu (original) (raw)
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West Pomeranian University of Technology, Szczecin
BAM Federal Institute for Materials Research and Testing
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Papers by S. Barai
The need for non-destructive evaluation (NDE) technologies for maintenance of complex welded stru... more The need for non-destructive evaluation (NDE) technologies for maintenance of complex welded structures such as pressure vessels, load bearing structural members and power plants has long been recognized. This paper presents an application of data mining approach for weld data extracted from reported radiographic images. Data mining is the extraction of implicit, previously unknown and potentially useful information from data. In recent times, machinelearning models such, as neural networks are becoming standard tools for data mining of scientific data. This paper addresses various issues related to data mining and demonstrates their application. The study highlights the two major aspects of insight of data and prediction of the model for the problem domain.
Advances in Soft Computing
Artificial Intelligence in Engineering, 1999
The use of machine learning (ML), and in particular, arti cial neural networks (ANN), in engineer... more The use of machine learning (ML), and in particular, arti cial neural networks (ANN), in engineering applications has increased dramatically over the last years. However, by and large, the development of such applications or their report lack proper evaluation. De cient evaluation practice was observed in the general neural networks community and again in engineering applications through a survey we conducted of articles published in AI in Engineering and elsewhere. This de cient status hinders understanding and prevents progress. This paper goal is to remedy this situation. First, several evaluation methods are discussed with their relative qualities. Second, these qualities are illustrated by using the methods to evaluate ANN performance in two engineering problems. Third, a systematic evaluation procedure for ML is discussed. This procedure will lead to better evaluation of studies, and consequently to improved research and practice in the area of ML in engineering applications.
The need for non-destructive evaluation (NDE) technologies for maintenance of complex welded stru... more The need for non-destructive evaluation (NDE) technologies for maintenance of complex welded structures such as pressure vessels, load bearing structural members and power plants has long been recognized. This paper presents an application of data mining approach for weld data extracted from reported radiographic images. Data mining is the extraction of implicit, previously unknown and potentially useful information from data. In recent times, machinelearning models such, as neural networks are becoming standard tools for data mining of scientific data. This paper addresses various issues related to data mining and demonstrates their application. The study highlights the two major aspects of insight of data and prediction of the model for the problem domain.
The need for non-destructive evaluation (NDE) technologies for maintenance of complex welded stru... more The need for non-destructive evaluation (NDE) technologies for maintenance of complex welded structures such as pressure vessels, load bearing structural members and power plants has long been recognized. This paper presents an application of data mining approach for weld data extracted from reported radiographic images. Data mining is the extraction of implicit, previously unknown and potentially useful information from data. In recent times, machinelearning models such, as neural networks are becoming standard tools for data mining of scientific data. This paper addresses various issues related to data mining and demonstrates their application. The study highlights the two major aspects of insight of data and prediction of the model for the problem domain.
Advances in Soft Computing
Artificial Intelligence in Engineering, 1999
The use of machine learning (ML), and in particular, arti cial neural networks (ANN), in engineer... more The use of machine learning (ML), and in particular, arti cial neural networks (ANN), in engineering applications has increased dramatically over the last years. However, by and large, the development of such applications or their report lack proper evaluation. De cient evaluation practice was observed in the general neural networks community and again in engineering applications through a survey we conducted of articles published in AI in Engineering and elsewhere. This de cient status hinders understanding and prevents progress. This paper goal is to remedy this situation. First, several evaluation methods are discussed with their relative qualities. Second, these qualities are illustrated by using the methods to evaluate ANN performance in two engineering problems. Third, a systematic evaluation procedure for ML is discussed. This procedure will lead to better evaluation of studies, and consequently to improved research and practice in the area of ML in engineering applications.
The need for non-destructive evaluation (NDE) technologies for maintenance of complex welded stru... more The need for non-destructive evaluation (NDE) technologies for maintenance of complex welded structures such as pressure vessels, load bearing structural members and power plants has long been recognized. This paper presents an application of data mining approach for weld data extracted from reported radiographic images. Data mining is the extraction of implicit, previously unknown and potentially useful information from data. In recent times, machinelearning models such, as neural networks are becoming standard tools for data mining of scientific data. This paper addresses various issues related to data mining and demonstrates their application. The study highlights the two major aspects of insight of data and prediction of the model for the problem domain.