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Research Publication in Journals

1.    Pandey, Manish Kumar, Anu Saini, Karthikeyan Subbiah, Nalini Chintalapudi, and Gopi Battineni. 2022. "Improved Carpooling Experience through Improved GPS Trajectory Classification Using Machine Learning Algorithms" Information 13, no. 8: 369.

2.    Nair, Preeti, Manish Kumar Pandey, and Arun Kumar Singh. 2021. “Tapping the Sentiment of the Customers through Association Rule Mining for the Products Endorsed by Celebrities.” Journal of Scientific Research 65(5): 212–16. (I.F. NA)

3.    Anand, Akash, Manish K. Pandey, Prashant K. Srivastava, Ayushi Gupta, and Mohammed L. Khan 2021. "Integrating Multi-Sensors Data for Species Distribution Mapping Using Deep Learning and Envelope Models" Remote Sensing 13, no. 16: 3284. (I.F. 4.848)

4.    Manish Kumar Pandey, Mamta Mittal, Karthikeyan Subbiah, Optimal balancing & efficient feature ranking approach to minimize credit risk, International Journal of Information Management Data Insights, Volume 1, Issue 2, 2021, 100037, ISSN 2667-0968, (I.F. NA) 

5.    Ayushi Gupta, Prachi Singh, Prashant K. Srivastava, Manish K. Pandey, Akash Anand, K. S. Chandra Sekar & Karuna Shanker (2021) Development of hyperspectral indices for anti-cancerous Taxol content estimation in the Himalayan region, Geocarto International, DOI: 10.1080/10106049.2021.1983031 (I.F. 4.889)

6.    Singh, Pangambam Sendash, Singh, Vijendra Pratap, Pandey, Manish Kumar, Karthikeyan, Subbiah, 2021, Enhanced classification of hyperspectral images using improvised oversampling and undersampling techniques, International Journal of Information Technology, ISSN 2511-2112, (I.F. NA)

7.    Singh, Ram Kumar, Drews, Martin, De la Sen, Manuel, Srivastava, Prashant Kumar, Trisasongko, Bambang H., Kumar, Manoj, Pandey, Manish Kumar, Anand, Akash, Singh, S. S., Pandey, A. K., Dobriyal, Manmohan, Rani, Meenu, Kumar, Pavan, 2021, Highlighting the compound risk of COVID-19 and environmental pollutants using geospatial technology, Scientific Reports, 8363, 11, 1, ISSN 2045-2322, (I.F. 4.379)

8.    Ramandeep Kaur M. Malhi, Akash Anand, Prashant K. Srivastava, Sumit K. Chaudhary, Manish K Pandey, Mukund Dev Behera, Amit Kumar, Prachi Singh, G. Sandhya Kiran, Synergistic evaluation of Sentinel 1 and 2 for biomass estimation in a tropical forest of India, Advances in Space Research,2021, ISSN 0273-1177, (I.F. 2.152)

9.    Ramandeep Kaur M. Malhi, Manish Kumar Pandey, Akash Anand, Prashant K. Srivastava, George P. Petropoulos, Prachi Singh, G. Sandhya Kiran & B. K. Bhattarcharya (2021) Band selection algorithms for foliar trait retrieval using AVIRIS-NG: a comparison of feature-based attribute evaluators, Geocarto International, 4.889)

10.    Singh, V. P., Pandey, M. K. *, Singh, P. S., & Karthikeyan, S. (2020). An LSTM Based Time Series Forecasting Framework for Web Services Recommendation. Computación y Sistemas, 24(2). (I.F. NA)

11.    Sendash Singh, P., Pratap Singh, V., Kumar Pandey, M., & Karthikeyan, S. (2020). Local Binary Ensemble based Self-training for Semi-supervised Classification of Hyperspectral Remote Sensing Images. Computación y Sistemas, 24(2). (I.F. NA)

12.    Singh, V. P., Pandey, M. K. *, Singh, P. S., & Karthikeyan, S. (2020). Neural Net Time Series Forecasting Framework for Time-Aware Web Services Recommendation. Procedia Computer Science, 171, 1313–1322. (I.F. NA)

13.    Singh, V. P., Pandey, M. K. *, Singh, P. S., & Karthikeyan, S. (2019). An empirical mode decomposition (E.M.D.) enabled long sort term memory (LSTM) based time series forecasting framework for web services recommendation. In Frontiers in Artificial Intelligence and Applications (Vol. 320, pp. 715–723). IOS Press. (I.F. NA)

14.    Singh, V. P., Pandey, M. K. *, Singh, P. S., & Karthikeyan, S. (2020). An Econometric Time Series Forecasting Framework for Web Services Recommendation. In Procedia Computer Science (Vol. 167, pp. 1615–1625). Elsevier B.V. (I.F. NA)

15.    Anand, A., Srivastava, P. K., Maurya, N. K., Dugesar, V., Pandey, M. K., Singh, P., Gupta, A., & Kothwade, G. (2019). Analyzing the Aerosol Absorption Index ( AAI ) trend in Indian region during Post-Monsoon Season. Bulletin of Environmental and Scientific Research, 8(2), 6–9.

16.    Anand, A., Srivastava, P. K., Pandey, M. K., Maurya, N. K., Dugesar, V., Singh, P., & Gupta, A. (2019). Spatio-Temporal Analysis of Forest cover change in Bero District. Bulletin of Environmental and Scientific Research, 8(4), 1–6.

17.    Pandey, M. K. *, & Subbiah, K. (2019). Performance analysis of time series forecasting using machine learning algorithms for prediction of Ebola casualties. Communications in Computer and Information Science, 899, 320–334. (I.F. NA)

18.    Sunil Kumar and Manish Kumar Pandey*. Comparison of Dynamic Load Balancing Policies in Data Centres. International Journal of Computer Applications 104(17):9-13, October 2014. (I.F. NA)

Research Publication in Conferences

1.    P. S. Singh, V. P. Singh, M. K. Pandey and S. Karthikeyan, "One-class Classifier Ensemble based Enhanced Semisupervised Classification of Hyperspectral Remote Sensing Images," 2020 International Conference on Emerging Smart Computing and Informatics (ESCI), Pune, India, 2020, pp. 22-27,
2.    Pandey, M.K. *, Karthikeyan, S.: Performance analysis of time series forecasting of ebola casualties using machine learning algorithm. In: Proceedings ITISE 201, Granada, 18–20 September (2017). ISBN 978-84-17293-01-7 
3.    Pandey M.K. *, Subbiah K. (2016) Social Networking and Big Data Analytics Assisted Reliable Recommendation System Model for Internet of Vehicles. In: Hsu CH., Wang S., Zhou A., Shawkat A. (eds) Internet of Vehicles – Technologies and Services. I.O.V. 2016. Lecture Notes in Computer Science, vol 10036. Springer, Cham
4.    M. K. Pandey* and K. Subbiah, "A Novel Storage Architecture for Facilitating Efficient Analytics of Health Informatics Big Data in Cloud," 2016 IEEE International Conference on Computer and Information Technology (C.I.T.), Nadi, 2016, pp. 578-585.
5.    S. Kumar, M. K. Pandey*, A. Nath and K. Subbiah, "Performance Analysis of Ensemble Supervised Machine Learning Algorithms for Missing Value Imputation," 2016 2nd International Conference on Computational Intelligence and Networks (CINE), Bhubaneswar, 2016, pp. 160-165.
6.    S. Kumar, M. K. Pandey*, A. Nath and K. Subbiah, "Missing QoS-values predictions using neural networks for cloud computing environments," 2015 International Conference on Computing and Network Communications (CoCoNet), Trivandrum, 2015, pp. 414-419.
7.    S. Kumar, M. K. Pandey, A. Nath, K. Subbiah and M. K. Singh, "Comparative study on machine learning techniques in predicting the QoS-values for web-services recommendations," International Conference on Computing, Communication & Automation, Noida, 2015, pp. 161-167.
8.    M. K. Pandey*, S. Kumar, K. Subbiah, " Information Security Management System (ISMS) Standards in Cloud Computing-A Critical Review," International Conference on Control, Computing, Communication and Materials, Allahabad, 2013.

Research Publication in Books

1.    Pandey M.K., Srivastava P.K. (2021) A Probe into Performance Analysis of Real-Time Forecasting of Endemic Infectious Diseases Using Machine Learning and Deep Learning Algorithms. In: Roy S., Goyal L.M., Mittal M. (eds) Advanced Prognostic Predictive Modelling in Healthcare Data Analytics. Lecture Notes on Data Engineering and Communications Technologies, vol 64. Springer, Singapore.
2.    Manish Kumar Pandey, Prashant K. Srivastava, George P. Petropoulos, Chapter 21 - Future pathway for research and emerging applications in GPS/GNSS, Editor(s): George p. Petropoulos, Prashant K. Srivastava, G.P.S. and GNSS Technology in Geosciences, Elsevier, 2021, Pages 429-438, ISBN 9780128186176,
3.    Pandey, P. C., Pandey, M. K., Gupta, A., Singh, P., & Srivastava, P. K. (2021). Spectroradiometry: types, data collection, and processing. Advances in Remote Sensing for Natural Resource Monitoring, 9-27.
4.    Srivastava, P. K., Malhi, R. K. M., Pandey, P. C., Anand, A., Singh, P., Pandey, M. K., & Gupta, A. (2020). Revisiting hyperspectral remote sensing: origin, processing, applications and way forward. In Hyperspectral Remote Sensing (pp. 3–21). Elsevier.
5.    Lamine, S., Pandey, M. K., Petropoulos, G. P., Brewer, P. A., Srivastava, P. K., Manevski, K., … Macklin, M. G. (2020). Spectroradiometry as a tool for monitoring soil contamination by heavy metals in a floodplain site. In Hyperspectral Remote Sensing (pp. 249–268). Elsevier.

Last Updated - 6-Aug-2022