Performance analysis of artificial intelligence techniques to control the saturation level in the magnetic core of a welding transformer

Subbanna, S.; M, Suryakalavarthi

doi:10.1109/iceeot.2016.7755331

Search citation statements

Order By: Relevance

Paper Sections

Select...

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2019

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

(1 citation statement)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Likewise Rama Subbanna et al [11], has also implemented the above mentioned three ANN training algorithms to observe the saturation level in the magnetic core of a welding transformer. Various performance metrics such as computational time, algorithm complexity, root square error and the gradient are used to determine the finest algorithm.…”

Section: Introductionmentioning

confidence: 99%

Regression Analysis of ANN Training Algorithms for an Anaerobic Wastewater Treatment System

Harikishore¹,

Shanthi²

2019

IJRAT

View full text Add to dashboard Cite

The process of an anaerobic reactor in predicting the COD Level was modeled by the application of Neural Networks. The effluent COD is the most common factor used in all types of Wastewater Treatment Systems. This research is about the prediction of the concentration of |COD by using the ANN, a simple feed forward, Back Propagation (BP) neural network. The three layered feed forward ANN has been trained using four back propagation algorithms. The efficiency and accuracy were measured based on MSE and Regression Coefficient(R) to evaluate their performance. The model trained with Levenberg -Marquardt algorithm provided best results with MSE = 0.533 and R=0.991. The model performed up to the expectation and the result of the prediction is appropriate.

show abstract

Section: Introductionmentioning

confidence: 99%