Specialization

Neuro-Computing Techniques & Software Engineering

Email

palika.chopra@thapar.edu

SCI:

1. Chopra, P., Sharma, R. K. and Kumar, M., (2016). "Predicting compressive strength of concrete using artificial neural network and genetic programming". Advances in Materials Science and Engineering, Article ID 7648467, 10 pages.
2. Chopra, T., Parida, M., Kwatra, N., and Chopra, P., (2018). "Development of pavement distress deterioration prediction models for urban road network using genetic programming". Advances in Civil Engineering, Article ID 1253108, 15 pages.
3. Chopra, P., Sharma, R. K., Kumar, M. and Chopra, T., (2018). "Comparison of machine learning techniques for the prediction of compressive strength of concrete". Advances in Civil Engineering, Article ID 5481705,9 pages.

Non-SCI:

1. Chopra, P., Sharma, R. K. and Kumar, M., (2015). “Artificial neural networks for the prediction of compressive strength of concrete”. International Journal of Applied Sciences & Engineering, 13(3), 187-204.
2. Chopra, P., Sharma, R. K. and Kumar, M., (2014). “Predicting compressive strength of concrete for varying workability using regression models”.International Journal of Engineering & Applied Sciences, 6(4), 10-22.
3. Chopra, P., Sharma, R. K. and Kumar, M., (2014). “Regression models for the prediction of compressive strength of concrete with & without fly ash”. International Journal of Latest Trends in Engineering and Technology, 3(4), 400-406.
4. Chopra, P., Sharma, R. K. and Kumar, M., (2013). “Ridge regression for the prediction of compressive strength of concrete”. International Journal of Innovations in Engineering and Technology, 2(3), 106-111.

Conference Publication

1. Grewal, R., Malhi, A., and Chopra, P., (2019). “Translating Artificial Intelligence into Healthcare: Diabetic Retinopathy Detection”. International conference on communication and Electronics Systems at Coimbatore, India.