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Materials Algorithms Project
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  1. Provenance of code.
  2. Purpose of code.
  3. Specification.
  4. Description of subroutine's operation.
  5. References.
  6. Parameter descriptions.
  7. Error indicators.
  8. Accuracy estimate.
  9. Any additional information.
  10. Example of code
  11. Auxiliary subroutines required.
  12. Keywords.
  13. Download source code.
  14. Links.

Provenance of Source Code

T. Sourmail,
Phase Transformations Group,
Department of Materials Science and Metallurgy,
University of Cambridge,
Cambridge, U.K.

The neural network program was produced by:

David MacKay,
Cavendish Laboratory,
University of Cambridge,
Madingley Road,
Cambridge, CB3 0HE, U.K.

Added to MAP: December 2001

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Estimation of the losses in FeCo alloys as a function of the temperature, frequency of applied field, and ageing time/temperature.

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Language: FORTRAN / C
Product form: Source code / Executable files
Operating System: Any

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MAP_NEURAL_FECO_LOSSES  contains a suite of programs which enable the user to estimate the the losses in FeCo alloys as a function of the temperature, frequency of applied field, and ageing time/temperature. It makes use of a neural network program called generate44, which was developed by David MacKay and is part of the bigback5 program. The network was trained using experimental results. 3 different models are provided, which differ from each other by the number of hidden units and by the value of the seed used when training the network. It was found that a more accurate result could be obtained by averaging the results from all the models [2]. This suite of programs calculates the results of each model and then combines them, by averaging, to produce a committee result and error estimate, as described by MacKay.

Programs are available which run on any operating system, A set of program and data files are provided for the model, which calculate the losses in equiatomic FeCo alloys. The files for UNIX are included in a directory called FeCo_losses. This directory contains the following files and subdirectories:

A text file containing step-by-step instructions for running the program, including a list of input variables.
A text file containing the minimum and maximum limits of each input and output variable. This file is used to normalise and unnormalise the input and output data.
An input text file containing the input variables used for predictions.
This is a unix shell file containing the command steps required to run the module. It can be executed by typing sh model.gen  at the command prompt. This shell file compiles and runs all the programs necessary for normalising the input data, executing the network for each model, unnormalising the output data and combining the results of each model to produce the final committee result.
generate44 / generate55
This is the executable file for the neural network program. generate44 runs on unix operating system and generate55 on the PC. It reads the normalised input data file, norm_test.in, and uses the weight files in subdirectory c. The results are written to the temporary output file _out.
Contains the final un-normalised committee results for the predicted losses.
The weights files for the different models.
Files containing information for calculating the size of the error bars for the different models.
Files containing information about the perceived significance value [1] for each model.
Files containing values for the noise, test error and log predictive error [1] for each model.
A normalised output file which was created when developing the model. It is accessed by generate44 via spec.t1.
out1, out2 etc.
The normalised output files for each model.
The normalised output file containing the committee results. It is generated by gencom.for.

Detailed instructions on the use of the program are given in the README files. Further information about this suite of programs can be obtained from reference 1.

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  • D.J.C. MacKay, 1997, Mathematical Modelling of Weld Phenomena 3, eds. H. Cerjak & H.K.D.H. Bhadeshia, Inst. of Materials, London, pp 359.

  • Parameters

    Input parameters

    The input variables for the model are listed in the labels.txt  file in the corresponding directory. The maximum and minimum values for each variable are given in the file MINMAX.

    Output parameters

    These program gives the losses (W/kg) . The corresponding output files is called result. The format of the output file is:
    Prediction     Error bar      Lower-limit      Upper-limit    
        (W/kg)                       (W/kg)              (W/kg)
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    Error Indicators


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    A full calculation of the error bars is presented in reference 2.

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    Further Comments


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    1. Program text

           Complete program.

    2. Program data

    See sample data file: test.dat.

    3. Program results

    See sample output file: Result or result.dat.

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    Auxiliary Routines


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    neural network, FeCo alloys, losses, soft magnetic alloys

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    All unix variants:
    Download (280 kB)
    Download (280 kB)
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    MAP originated from a joint project of the National Physical Laboratory and the University of Cambridge.


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