Research article |
Codes |
[14] Kumar, A., Gaurav, K, Singh, A., & Yassen, Z.M. (2024). Assessment of machine learning models to predict daily streamflow in a semiarid river catchment, Neural Computing and Applications. |
To be uploaded soon |
[13] Bhadani, V.*, Singh, A.*, Kumar V., & Gaurav, K. (2024). Nature-inspired optimal tuning of input membership functions of fuzzy inference system for groundwater level prediction, Environmental Modelling & Software, 105995 (*Equal contribution first author). |
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[12] Singh, A., Mousavi, SHS. & Nagar, J. (2024). F-TLBO-ID: Fuzzy Fed Teaching Learning Based Optimisation Algorithm to Predict the Number of k-barriers for Intrusion Detection, Applied Soft Computing, 111163. |
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[11] Singh, A., Patel, S., Bhadani, V., Kumar V., & Gaurav, K. (2024). AutoML-GWL: Automated machine learning model for the prediction of groundwater level, Engineering Applications of Artificial Intelligence, 107405. |
To be uploaded soon |
[10] Singh, A., & Gaurav, K. (2023). Deep learning and data fusion to estimate surface soil moisture from multi-sensor satellite images, Scientific Report, 2251. |
To be uploaded soon |
[9] Singh, A., Nagar, J., Amutha, J., & Sharma, S. (2023). P2CA-GAM-ID: Coupling of Probabilistic Principal Components Analysis with Generalised Additive Model to predict the k-barriers for Intrusion Detection, Engineering Applications of Artificial Intelligence, 107137. |
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[8] Nagar, J., Chaturvedi, S. K., Soh, S., & Singh, A. (2023). A machine learning approach to predict the k-coverage probability of wireless multihop networks considering boundary and shadowing effects, Expert Systems with Applications, 226, 120160. |
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[7] Singh, A., Amutha, J., Nagar, J., & Sharma, S. (2023). A deep learning approach to predict the number of k-barriers for intrusion detection over a circular region using wireless sensor networks, Expert Systems with Applications, 118588. |
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[6] Singh, A., Niranjannaik, M., Kumar, S., & Gaurav, K. (2022). Comparison of Different Dielectric Models to Estimate Penetration Depth of L-and S-Band SAR Signals into the Ground Surface, Geographies, 2(4), 734-742.
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[5] Singh, A., Nagar, J., Sharma, S., & Kotiyal, V. (2021). A Gaussian process regression approach to predict the k-barrier coverage probability for intrusion detection in wireless sensor networks, Expert Systems with Applications, 172, 114603.
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[4] Kotiyal, V.*, Singh, A.*, Sharma, S.*, Nagar, J.*, & Lee, C. C*. (2021). ECS-NL: An enhanced cuckoo search algorithm for node localisation in wireless sensor networks, Sensors, 21(11), 3576 (*Equal contribution first author).
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[3] Singh, A., Gaurav, K., Meena, G.K., & Kumar, S (2020). Estimation of Soil Moisture Applying Modified Dubois Model to Sentinel-1; A Regional Study from Central India, Remote Sensing, 12, 2266.
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[2] Singh, A., Kotiyal, V., Sharma, S., Nagar, J., & Lee, C. C. (2020). A machine learning approach to predict the average localization error with applications to wireless sensor networks, IEEE Access, 8, 208253-208263.
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[1] Singh, A., Sharma, M., Kumar, R., Singh, S. P., & Madhesiya, J. R. (2019). Modelling and analysis of polarization noise in vertical cavity surface emitting LASERs, Multiscale and Multidisciplinary Modeling, Experiments and Design, 2, 151-157.
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