Editor


Sujata Dash Nagaland University, Zunheboto, India
Email: prof.sujatadash@gmail.com


Sujata Dash

Dash, S. (2023). A systematic review of adaptive machine learning techniques for early detection of Parkinson's disease. Artificial Intelligence for Neurological Disorders, 361-385.

Hanmandlu, M., Choudhury, D. K., & Dash, S. (2016). Detection of fabric defects using fuzzy decision tree. International Journal of Signal and Imaging Systems Engineering, 9(3), 184-198.

Biswas S., Dash S.(2018). A hybrid bootstrapping approach for developing named entity corpora from wikipedia . International Journal of Engineering and Technology(UAE), 7 (4), pp. 11 - 16

Dash, S., & Patra, B. (2014). Feature selection algorithms for classification and clustering in bioinformatics. In Global Trends in Intelligent Computing Research and Development (pp. 111-130). IGI Global.

Ahmad, M., Farooq, U., Atta-Ur-Rahman, Alqatari, A., Dash, S., & Luhach, A. K. (2019). Investigating TYPE constraint for frequent pattern mining. Journal of Discrete Mathematical Sciences and Cryptography, 22(4), 605-626.

Panda, M., Dash, S., Nayyar, A., Bilal, M., & Mehmood, R. M. (2020). Test suit generation for object oriented programs: A hybrid firefly and differential evolution approach. IEEE Access, 8, 179167-179188.

Panda, M., & Dash, S. (2021, December). An Improved JAYA Algorithm Based Test Suite Generation for Object Oriented Programs: A Model Based Testing Method. In International Conference on Advanced Informatics for Computing Research (pp. 112-122). Cham: Springer International Publishing.

Dash, S., Luhach, A. K., Chilamkurti, N., Baek, S., & Nam, Y. (2019). A Neuro-fuzzy approach for user behaviour classification and prediction. Journal of Cloud Computing, 8(1), 1-15.

Dash, S. (2016). Hybrid Ensemble Learning Methods for Classification of Microarray Data: RotBagg Ensemble Based Classification. In Handbook of Research on Computational Intelligence Applications in Bioinformatics (pp. 17-36). IGI Global.