An approach to evaluation of the extremely low-frequency magnetic field radiation in the laptop computer neighborhood by artificial neural networks

作者：Brodic Darko^*; Tanikic Dejan; Amelio Alessia

来源：Neural Computing & Applications, 2017, 28(11): 3441-3453.

DOI：10.1007/s00521-016-2246-3

• Artificial neural networks
• Classification
• Exposure
• Magnetic field
• Non-ionizing radiation
• Portable computers
• Self-organizing map

The paper considers the level of the extremely low-frequency magnetic field produced by laptop computers, which can be hazardous to the laptop users' health. It proposes a new model for prediction of the laptop magnetic field radiation starting from a priori known laptop characteristics using artificial neural network. In the experiment, the magnetic field of ten different laptop computers is measured. The measuring of the magnetic field is performed at the points, which are relevant to laptop computer users. Prediction is obtained from testing laptops. The predicted magnetic field results are evaluated by correlation coefficient and clustered for detection of magnetic field ranges by self-organizing map. Obtained cluster set is compared with the cluster set computed on the measured magnetic field at the same laptop characteristics. Correlation coefficient showed good correspondence of the predicted values with the measured values. Furthermore, the comparison between the two cluster sets revealed a good alignment of magnetic field ranges in measured and predicted results.

• 出版日期2017-11