Early detection of diabetic retinopathy using PCA-firefly based deep learning model TR Gadekallu, N Khare, S Bhattacharya, S Singh, PKR Maddikunta, IH Ra, ... Electronics 9 (2), 274, 2020 | 332 | 2020 |
Deep neural networks to predict diabetic retinopathy TR Gadekallu, N Khare, S Bhattacharya, S Singh, PKR Maddikunta, ... Journal of Ambient Intelligence and Humanized Computing, 1-14, 2023 | 269 | 2023 |
An efficient XGBoost–DNN-based classification model for network intrusion detection system P Devan, N Khare Neural Computing and Applications 32 (16), 12499-12514, 2020 | 255 | 2020 |
Smo-dnn: Spider monkey optimization and deep neural network hybrid classifier model for intrusion detection N Khare, P Devan, CL Chowdhary, S Bhattacharya, G Singh, S Singh, ... Electronics 9 (4), 692, 2020 | 154 | 2020 |
An efficient system for heart disease prediction using hybrid OFBAT with rule-based fuzzy logic model GT Reddy, N Khare Journal of Circuits, Systems and Computers 26 (04), 1750061, 2017 | 116 | 2017 |
A survey of intrusion detection from the perspective of intrusion datasets and machine learning techniques G Singh, N Khare International Journal of Computers and Applications 44 (7), 659-669, 2022 | 100 | 2022 |
Cuckoo search optimized reduction and fuzzy logic classifier for heart disease and diabetes prediction TR Gadekallu, N Khare International Journal of Fuzzy System Applications (IJFSA) 6 (2), 25-42, 2017 | 83 | 2017 |
Heart disease classification system using optimised fuzzy rule based algorithm GT Reddy, N Khare International Journal of Biomedical Engineering and Technology 27 (3), 183-202, 2018 | 63 | 2018 |
Hybrid firefly-bat optimized fuzzy artificial neural network based classifier for diabetes diagnosis. GT Reddy, N Khare International Journal of Intelligent Engineering & Systems 10 (4), 2017 | 60 | 2017 |
FFBAT-optimized rule based fuzzy logic classifier for diabetes G Thippa Reddy, N Khare International Journal of Engineering Research in Africa 24, 137-152, 2016 | 54 | 2016 |
Sentimental analysis for airline twitter data DD Das, S Sharma, S Natani, N Khare, B Singh IOP conference series: materials science and engineering 263 (4), 042067, 2017 | 45 | 2017 |
Constraint-based measures for DNA sequence mining using group search optimization algorithm K Lakshmanna, N Khare, N Khare International Journal of Intelligent Engineering and Systems 9 (3), 91-100, 2016 | 35 | 2016 |
FDSMO: frequent DNA sequence mining using FBSB and optimization K Lakshmanna, N Khare International Journal of Intelligent Engineering and Systems 9 (4), 157-166, 2016 | 33 | 2016 |
Mining dna sequence patterns with constraints using hybridization of firefly and group search optimization K Lakshmanna, N Khare Journal of Intelligent systems 27 (3), 349-362, 2018 | 31 | 2018 |
Deep learning for intelligent demand response and smart grids: A comprehensive survey QV Pham, M Liyanage, N Deepa, M VVSS, S Reddy, PKR Maddikunta, ... arXiv preprint arXiv:2101.08013, 2021 | 30 | 2021 |
An algorithm for mining multidimensional association rules using boolean matrix N Khare, N Adlakha, KR Pardasani 2010 International Conference on Recent Trends in Information …, 2010 | 22 | 2010 |
Karnaugh map model for mining association rules in large databases N Khare, N Adlakha, KR Pardasani International Journal of Computer and Network Security 1 (2), 16-21, 2009 | 19 | 2009 |
Sparse auto encoder driven support vector regression based deep learning model for predicting network intrusions D Preethi, N Khare Peer-to-Peer Networking and Applications 14 (4), 2419-2429, 2021 | 18 | 2021 |
An algorithm for mining multidimensional fuzzy association rules N Khare, N Adlakha, KR Pardasani arXiv preprint arXiv:0909.5166, 2009 | 18 | 2009 |
Deep learning for intelligent demand response and smart grids: A comprehensive survey P Boopathy, M Liyanage, N Deepa, M Velavali, S Reddy, ... Computer Science Review 51, 100617, 2024 | 16 | 2024 |