**Author details**

**5. Conclusion**

**Figure 8.**

**Figure 9.**

wireless classification process.

*Training coding of SVM in MATLAB software.*

**Acknowledgements**

manuscript significantly.

**152**

**Appendices and nomenclature**

CWT continuous wavelet transform

AI artificial intelligent

Further use of this coding will produce the classification result from the use of ST and SVM in the LabVIEW tools. This classification is significant, particularly in sending the electricity-based problem which originated from PQ disturbances. The LabVIEW function which assemble the ST, SVM and interfacing system in one platform could be a beneficial for electrical engineer conduct the problem shooting step. The capability of LabVIEW to integrate with different type algorithm prove to be the strength to materialize its function as classification tools. The introduction of this classification technique will minimize the time taken to pinpoint problem related to PQ disturbance. The more advance feature of this tools could be extended towards cloud computing function, Internet of Thing (IOT) application as well as

*Coding of randomized data of classification using SVM in MATLAB software.*

*LabVIEW - A Flexible Environment for Modeling and Daily Laboratory Use*

We are grateful to the editors and anonymous reviewers for their constructive comments and valuable suggestions that helped to improve the quality of this

Ahmad Farid Abidin\* and Mohd Abdul Talib Mat Yusoh Faculty of Electrical Engineering, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia

\*Address all correspondence to: ahmad924@uitm.edu.my

© 2021 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
