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A back‐propagation neural network was applied to predicting the K IC values using tensile material data and investigating the effects of crack plane orientation and temperature. The 595 K IC data of structural steels were used for training and testing the neural network model.

In the trained neural network model, yield stress has relatively the most effect on K IC value among tensile material properties and K IC value was more sensitive to K IC test temperature than to crack plane orientation valid in the range of material data covered in this study. The performance of the trained artificial neural network (ANN) was evaluated by comparing output of the ANN with results of a conventional least squares fit to an assumed shape. The conventional linear or nonlinear least squares fitting methods gave very poor fitting results but the results predicted by the trained neural network were considerably satisfactory. This study shows that the neural network can be a good tool to predict K IC values according to the variation of the temperature and the crack plane orientation using tensile test results.

NeuroShell 2 NeuroShell 2 is our legacy neural network product targeted towards computer science instructors and students. It contains classic algorithms and architectures popular with graduate school professors and computer science students. • • • • • • • • • • NeuroShell 2 combines powerful neural network architectures, a Microsoft® Windows icon driven user interface, sophisticated utilities, and popular options to give users the ultimate neural network experimental environment.

It is recommended for academic users only, or those users who are concerned with classic neural network paradigms like backpropagation. Users interested in solving real problems should consider the NeuroShell Predictor, NeuroShell Classifier, or the NeuroShell Trader. Beginner's Neural Networks NeuroShell 2 includes both Beginner's and Advanced Systems in addition to Runtime Facilities. NeuroShell 2 includes interfaces for beginners and experts alike. The Beginner's System in NeuroShell 2 is designed for novices and first-time users. It includes a simplified set of procedures for building and executing a complete, powerful neural network application.

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The Beginner's System uses our powerful enhanced backpropagation paradigm, and defaults neural network parameters such as learning rate, momentum, and number of hidden neurons. To use the system you enter data, specify the inputs and outputs, and train the neural network.

You are then able to apply the trained neural network to new data and export the results to other programs. Advanced Neural Networks The NeuroShell 2 Advanced Options screen displays the independent modules that may be used to create a neural network application. The Advanced System in NeuroShell 2 gives experienced neural network users the ability to create and execute 16 different neural network architectures, with more user control compared to the Beginner's System. Spreadsheet Format Users can choose to enter their data in their familiar spreadsheet program or work in the NeuroShell 2 Datagrid. The program uses spreadsheet files as its internal format so you can view or edit them yourself. In fact, NeuroShell 2 will call your favorite Windows spreadsheet program. File Import and Export NeuroShell 2 imports ASCII, binary, and spreadsheet files.