Quarterly Publication

Document Type : Original Article

Authors

1 Department of Computer Science and Engineering, Amity University, Sector 125, Noida, Uttar Pradesh, India.

2 Department of Management and International Business (MIB), University of Auckland, New Zealand.

3 School of Management & Marketing, Taylor’s University, Malaysia.

10.22105/bdcv.2021.142228

Abstract

To lessen the impact of a low student success rate, it's critical to be able to identify students who are in danger of failing early on, so that more targeted remedial intervention may be implemented. Private colleges use a variety of techniques, including increased tuition, expanded laboratory access, and the formation of learning communities. The prompt identification of students in danger of failing a given programme is important to both the students and the institutions with which they are registered, as seen by the debate presented below. Students are classified using artificial neural networks and random forests in this article. A private higher education provider provided a dataset of 2000 students. Artificial neural networks were found to provide the best performing model, with an accuracy of 83.24% percent.

Keywords

  1. Ande, V. K., & Mohapatra, H. (2015). SSO mechanism in distributed environment. International journal of innovations & advancement in computer science, 4(6), 133-136. https://www.academia.edu/download/38572672/SSO.pdf
  2. Kumar, R., Jha, S., & Singh, R. (2020). A different approach for solving the shortest path problem under mixed fuzzy environment. International journal of fuzzy system applications (IJFSA)9(2), 132-161.
  3. Broumi, S., Dey, A., Talea, M., Bakali, A., Smarandache, F., Nagarajan, D., ... & Kumar, R. (2019). Shortest path problem using Bellman algorithm under neutrosophic environment. Complex & intelligent systems5(4), 409-416. https://doi.org/10.1007/s40747-019-0101-8
  4. Mohapatra, H. (2000). C programming: practice cpp. Kindle Ebook.
  5. Masuti, M., & Mohapatra, H. (2015). Human centric software engineering. International journal of innovations & advancement in computer science, 4(7).
  6. Mohapatra, H., & Rath, A. K. (2020). Fundamentals of software engineering: designed to provide an insight into the software engineering concepts. BPB Publications.
  7. Mohapatra, H., Debnath, S., & Rath, A. K. (2019). Energy management in wireless sensor network through EB-LEACH. International journal of research and analytical reviews (IJRAR), 56-61.
  8. Mohapatra, H., Debnath, S., Rath, A. K., Landge, P. B., Gayen, S., & Kumar, R. (2020). An efficient energy saving scheme through sorting technique for wireless sensor network. International journal of emerging trends in engineering research8(8), 4278-4286.
  9. Mohapatra, H., Rath, A. K., Landge, P. B., Bhise, D. H. I. R. A. J., Panda, S., & Gayen, S. A. (2020). A comparative analysis of clustering protocols of wireless sensor network. International journal of mechanical and production engineering research and development (IJMPERD) ISSN (P)10(3), 8371-8386.
  10. Mohapatra, H., & Rath, A. K. (2019). Fault tolerance through energy balanced cluster formation (EBCF) in WSN. Smart innovations in communication and computational sciences(pp. 313-321). Springer, Singapore. https://doi.org/10.1007/978-981-13-2414-7_29
  11. Mohapatra, H., & Rath, A. K. (2019). Fault tolerance in WSN through PE-LEACH protocol. IET wireless sensor systems9(6), 358-365.
  12. Mohapatra, H., & Rath, A. K. (2021). Fault tolerance in WSN through uniform load distribution function. International journal of sensors wireless communications and control11(4), 385-394. https://doi.org/10.2174/2210327910999200525164954
  13. Mohapatra, H., & Rath, A. K. (2019). Fault-tolerant mechanism for wireless sensor network. IET wireless sensor systems10(1), 23-30.
  14. Mohapatra, H., & Rath, A. K. (2020). Survey on fault tolerance-based clustering evolution in WSN. IET networks9(4), 145-155.
  15. Mohapatra, H., Rath, A. K., Lenka, R. K., Nayak, R. K., & Tripathy, R. (2021). Topological localization approach for efficient energy management of WSN. Evolutionary intelligence, 1-11. https://doi.org/10.1007/s12065-021-00611-z
  16. Mohapatra, H., Rath, S., Panda, S., & Kumar, R. (2020). Handling of man-in-the-middle attack in wsn through intrusion detection system. International journal of emerging trends in engineering research8(5), 1503-1510.
  17. Mohapatra, H. (2021). Designing of fault tolerant models for wireless sensor network (Ph. D Dissertation, Veer Surendra Sai University of Technology). Retrieved from http://hdl.handle.net/10603/333160
  18. Nirgude, V., Mahapatra, H., & Shivarkar, S. (2017). Face recognition system using principal component analysis & linear discriminant analysis method simultaneously with 3d morphable model and neural network BPNN method. Global journal of advanced engineering technologies and sciences4(1), 1-6.
  19. Mohapatra, H. (2009). HCR by using neural network (Master's thesis, M. Tech_s Desertion, Govt. College of Engineering and Technology, Bhubaneswar).
  20. Mohapatra, H., & Rath, A. K. (2021). A fault tolerant routing scheme for advanced metering infrastructure: an approach towards smart grid. Cluster computing, 24,2193–2211. https://doi.org/10.1007/s10586-021-03255-x
  21. Panda, M., Pradhan, P., Mohapatra, H., & Barpanda, N. K. (2019). Fault tolerant routing in heterogeneous environment. International journal of scientific & technology research8(8), 1009-1013.
  22. Parida, R., Rath, K., Mohapatra, H. (2021). Binary self-adaptive salp swarm optimization based dynamic load balancing in cloud computing: load balancing in cloud computing. International journal of information technology and web engineering (IJITWE). In press
  23. Kumar, R., Dey, A., Broumi, S., & Smarandache, F. (2020). A study of neutrosophic shortest path problem. Neutrosophic graph theory and algorithms(pp. 148-179). IGI Global.
  24. Kumar, R., Edalatpanah, S. A., Jha, S., & Singh, R. (2019). A novel approach to solve gaussian valued neutrosophic shortest path problems. International journal of engineering and advanced technology, 8(3), 347–353.
  25. Kumar, R., Edaltpanah, S. A., Jha, S., Broumi, S., & Dey, A. (2018). Neutrosophic shortest path problem. Neutrosophic sets and systems, 23, 5–15.
  26. Kumar, R., Edalatpanah, S. A., & Mohapatra, H. (2020). Note on “optimal path selection approach for fuzzy reliable shortest path problem”. Journal of intelligent & fuzzy systems, 39(5), 7653-7656. DOI:3233/JIFS-200923
  27. Kumar, R., Edalatpanah, S. A., Jha, S., Broumi, S., Singh, R., & Dey, A. (2019). A multi objective programming approach to solve integer valued neutrosophic shortest path problems. Neutrosophic sets and systems, 24, 134-149.
  28. Kumar, R., Edalatpanah, S. A., Jha, S., & Singh, R. (2019). A pythagorean fuzzy approach to the transportation problem. Complex & intelligent systems5(2), 255-263. https://doi.org/10.1007/s40747-019-0108-1
  29. Pratihar, J., Kumar, R., Dey, A., & Broumi, S. (2020). Transportation problem in neutrosophic environment. Neutrosophic graph theory and algorithms(pp. 180-212). IGI Global.
  30. Pratihar, J., Kumar, R., Edalatpanah, S. A., & Dey, A. (2021). Modified Vogel’s approximation method for transportation problem under uncertain environment. Complex & intelligent systems7(1), 29-40. https://doi.org/10.1007/s40747-020-00153-4
  31. Gayen, S., Jha, S., Singh, M., & Kumar, R. (2019). On a generalized notion of anti-fuzzy subgroup and some characterizations. International journal of engineering and advanced technology8(3), 385-390.
  32. Gayen, S., Smarandache, F., Jha, S., & Kumar, R. (2020). Interval-valued neutrosophic subgroup based on interval-valued triple t-norm. Neutrosophic sets in decision analysis and operations research(pp. 215-243). IGI Global.
  33. Gayen, S., Smarandache, F., Jha, S., & Kumar, R. (2020). Introduction to interval-valued neutrosophic subring. Neutrosophic sets and systems, 36.
  34. Gayen, S., Smarandache, F., Jha, S., Singh, M. K., Broumi, S., & Kumar, R. (2020). Introduction to plithogenic hypersoft subgroup. Neutrosophic sets and systems, 33, 208–233.
  35. Gayen, S., Smarandache, F., Jha, S., Singh, M. K., Broumi, S., & Kumar, R. (2020). Introduction to plithogenic subgroup. Neutrosophic graph theory and algorithms(pp. 213-259). IGI Global.
  36. Gayen, S., Smarandache, F., Jha, S., Singh, M. K., Broumi, S., & Kumar, R. (2020). Soft subring theory under interval-valued neutrosophic environment. Neutrosophic sets and systems, 36.
  37. Kumar, R., Edalatpanah, S. A., Jha, S., Gayen, S., & Singh, R. (2019). Shortest path problems using fuzzy weighted arc length. International journal of innovative technology and exploring engineering8(6), 724-731.
  38. Kumar, R., Jha, S., & Singh, R. (2017). Shortest path problem in network with type-2 triangular fuzzy arc length. Journal of applied research on industrial engineering4(1), 1-7. DOI: 22105/jarie.2017.48858
  39. Mohapatra, H., Panda, S., Rath, A., Edalatpanah, S., & Kumar, R. (2020). A tutorial on powershell pipeline and its loopholes. International journal of emerging trends in engineering research8(4), 975-982.
  40. Kumar, R., Edalatpanah, S. A., Gayen, S., & Broum, S. (2021). Answer note “a novel method for solving the fully neutrosophic linear programming problems: suggested modifications”. Neutrosophic sets and systems39(1), 12.
  41. Panda, H., Mohapatra, H., & Rath, A. K. (2020). WSN-based water channelization: an approach of smart water. Smart cities—opportunities and challenges58, 157-166. https://doi.org/10.1007/978-981-15-2545-2_15
  42. Mohapatra, H., Rath, A. K. (2020). IoT-based smart water' (Control, Robotics & Sensors, 2020), 'IoT Technologies in Smart Cities: From sensors to big data, security and trust', Chap. 3, pp. 63-82, DOI: 10.1049/PBCE128E_ch3.
  43. Mohapatra, H., & Rath, A. K. (2020, October). Nub less sensor based smart water tap for preventing water loss at public stand posts. 2020 IEEE microwave theory and techniques in wireless communications (MTTW)(Vol. 1, pp. 145-150). IEEE.
  44. Rout, S. S., Mohapatra, H., Nayak, R. K., Tripathy, R., Bhise, D., Patil, S. P., & Rath, A. K. (2020). Smart water solution for monitoring of water usage based on weather condition. International journal8(9).
  45. Mohapatra, H., & Rath, A. K. (2021). IoE based framework for smart agriculture. Journal of ambient intelligence and humanized computing, 1-18. https://doi.org/10.1007/s12652-021-02908-4
  46. Mohapatra, H., & Rath, A. K. (2021). An IoT based efficient multi-objective real-time smart parking system. International journal of sensor networks37(4), 219-232.
  47. Mohapatra, H., & Rath, A. K. (2019). Detection and avoidance of water loss through municipality taps in India by using smart taps and ICT. IET wireless sensor systems9(6), 447-457.
  48. Mohapatra, H. (2020). Offline drone instrumentalized ambulance for emergency situations. IAES international journal of robotics and automation9(4), 251-255.