Impact of data normalization on stock index forecasting SC Nayak, BB Misra, HS Behera International Journal of Computer Information Systems and Industrial …, 2014 | 251 | 2014 |
ACFLN: artificial chemical functional link network for prediction of stock market index SC Nayak, BB Misra, HS Behera Evolving Systems 10 (4), 567-592, 2019 | 64 | 2019 |
Artificial chemical reaction optimization of neural networks for efficient prediction of stock market indices SC Nayak, BB Misra, HS Behera Ain Shams Engineering Journal 8 (3), 371-390, 2017 | 63 | 2017 |
Index prediction with neuro-genetic hybrid network: A comparative analysis of performance SC Nayak, BB Misra, HS Behera 2012 International conference on computing, communication and applications, 1-6, 2012 | 62 | 2012 |
Estimating stock closing indices using a GA-weighted condensed polynomial neural network SC Nayak, BB Misra Financial Innovation 4 (1), 21, 2018 | 54 | 2018 |
A chemical-reaction-optimization-based neuro-fuzzy hybrid network for stock closing price prediction SC Nayak, BB Misra Financial Innovation 5 (1), 38, 2019 | 37 | 2019 |
Extreme learning with chemical reaction optimization for stock volatility prediction SC Nayak, BB Misra Financial Innovation 6 (1), 16, 2020 | 32 | 2020 |
Development and Performance Evaluation of Adaptive Hybrid Higher Order Neural Networks for Exchange Rate Prediction SC Nayak I.J. Intelligent Systems and Applications 9 (8), 71-85, 2017 | 32 | 2017 |
An adaptive second order neural network with genetic-algorithm-based training (ASONN-GA) to forecast the closing prices of the stock market SC Nayak, BB Misra, HS Behera International Journal of Applied Metaheuristic Computing (IJAMC) 7 (2), 39-57, 2016 | 29 | 2016 |
Efficient financial time series prediction with evolutionary virtual data position exploration SC Nayak, BB Misra, HS Behera Neural Computing and Applications, 2017 | 28 | 2017 |
Evaluation of normalization methods on neuro-genetic models for stock index forecasting SC Nayak, BB Misra, HS Behera 2012 World Congress on Information and Communication Technologies, 602-607, 2012 | 26 | 2012 |
Improving software reliability prediction accuracy using CRO-based FLANN AK Behera, SC Nayak, CSK Dash, S Dehuri, M Panda Innovations in Computer Science and Engineering: Proceedings of the Fifth …, 2019 | 20 | 2019 |
COA-HONN: cooperative optimization algorithm based higher order neural networks for stock forecasting SC Nayak, MD Ansari Recent Advances in Computer Science and Communications (Formerly: Recent …, 2021 | 19 | 2021 |
Artificial chemical reaction optimization based neural net for virtual data position exploration for efficient financial time series forecasting SC Nayak, BB Misra, HS Behera Ain Shams Engineering Journal 9 (4), 1731-1744, 2018 | 19 | 2018 |
A fireworks algorithm based Pi-Sigma neural network (FWA-PSNN) for modelling and forecasting chaotic crude oil price time series SC Nayak EAI Endorsed Transactions on Energy Web 7 (28), e2-e2, 2020 | 18 | 2020 |
On developing and performance evaluation of adaptive second order neural network with GA-based training (ASONN-GA) for financial time series prediction SC Nayak, BB Misra, HS Behera Advancements in applied metaheuristic computing, 231-263, 2018 | 17 | 2018 |
Fluctuation prediction of stock market index by adaptive evolutionary higher order neural networks SC Nayak, BB Misra, HS Behera International Journal of Swarm Intelligence 2 (2-4), 229-253, 2016 | 17 | 2016 |
Hybridzing chemical reaction optimization and artificial neural network for stock future index forecasting SC Nayak, BB Misra, HS Behera 2013 1st International Conference on Emerging Trends and Applications in …, 2013 | 17 | 2013 |
A pi-sigma higher order neural network for stock index forecasting SC Nayak, BB Misra, HS Behera Computational Intelligence in Data Mining-Volume 2: Proceedings of the …, 2015 | 16 | 2015 |
Forecasting foreign exchange rates using CRO based different variants of FLANN and performance analysis KK Sahu, SR Sahu, SC Nayak, HS Behera International Journal of Computational Systems Engineering 2 (4), 190-208, 2016 | 15 | 2016 |