A hybrid ETS–ANN model for time series forecasting S Panigrahi, HS Behera Engineering applications of artificial intelligence 66, 49-59, 2017 | 230 | 2017 |
Time series forecasting of price of agricultural products using hybrid methods SK Purohit, S Panigrahi, PK Sethy, SK Behera Applied Artificial Intelligence 35 (15), 1388-1406, 2021 | 72 | 2021 |
A study on leading machine learning techniques for high order fuzzy time series forecasting S Panigrahi, HS Behera Engineering Applications of Artificial Intelligence 87, 103245, 2020 | 72 | 2020 |
A novel probabilistic intuitionistic fuzzy set based model for high order fuzzy time series forecasting RM Pattanayak, HS Behera, S Panigrahi Engineering Applications of Artificial Intelligence 99, 104136, 2021 | 64 | 2021 |
A modified sine cosine algorithm with ensemble search agent updating schemes for small signal stability analysis MK Kar, S Kumar, AK Singh, S Panigrahi International Transactions on Electrical Energy Systems 31 (11), e13058, 2021 | 42 | 2021 |
Forecasting of sunspot time series using a hybridization of ARIMA, ETS and SVM methods S Panigrahi, RM Pattanayak, PK Sethy, SK Behera Solar Physics 296 (1), 6, 2021 | 39 | 2021 |
High-order fuzzy time series forecasting by using membership values along with data and support vector machine RM Pattanayak, S Panigrahi, HS Behera Arabian Journal for Science and Engineering 45 (12), 10311-10325, 2020 | 38 | 2020 |
Reactive power management by using a modified differential evolution algorithm MK Kar, S Kumar, AK Singh, S Panigrahi Optimal Control Applications and Methods 44 (2), 967-986, 2023 | 36 | 2023 |
Effect of normalization techniques on univariate time series forecasting using evolutionary higher order neural network S Panigrahi, HS Behera International Journal of Engineering and Advanced Technology 3 (2), 280-285, 2013 | 32 | 2013 |
A cost-effective computer-vision based breast cancer diagnosis PK Sethy, C Pandey, MR Khan, SK Behera, K Vijaykumar, S Panigrahi Journal of Intelligent & Fuzzy Systems 41 (5), 5253-5263, 2021 | 30 | 2021 |
A novel high order hesitant fuzzy time series forecasting by using mean aggregated membership value with support vector machine RM Pattanayak, HS Behera, S Panigrahi Information Sciences 626, 494-523, 2023 | 29 | 2023 |
On-tree fruit monitoring system using IoT and image analysis SK Behera, PK Sethy, SK Sahoo, S Panigrahi, SC Rajpoot Concurrent Engineering 29 (1), 6-15, 2021 | 28 | 2021 |
Time series forecasting using evolutionary neural network S Panigrahi, Y Karali, HS Behera International Journal of Computer Applications 75 (10), 2013 | 27 | 2013 |
A novel chemical reaction optimization algorithm for higher order neural network training. KK Sahu, S PANIGRAHI, HS Behera Journal of Theoretical & Applied Information Technology 53 (3), 2013 | 23 | 2013 |
Normalize time series and forecast using evolutionary neural network S Panigrahi, Y Karali, HS Behera International Journal of Engineering Research & Technology 2 (9), 2518-2522, 2013 | 21 | 2013 |
An enhanced GWO algorithm with improved explorative search capability for global optimization and data clustering G Shial, S Sahoo, S Panigrahi Applied Artificial Intelligence 37 (1), 2166232, 2023 | 18 | 2023 |
Exploiting deep and hand-crafted features for texture image retrieval using class membership R Yelchuri, JK Dash, P Singh, A Mahapatro, S Panigrahi Pattern Recognition Letters 160, 163-171, 2022 | 18 | 2022 |
A non-probabilistic neutrosophic entropy-based method for high-order fuzzy time-series forecasting RM Pattanayak, HS Behera, S Panigrahi Arabian Journal for Science and Engineering 47 (2), 1399-1421, 2022 | 18 | 2022 |
A multi-step-ahead fuzzy time series forecasting by using hybrid chemical reaction optimization with pi-sigma higher-order neural network RM Pattanayak, HS Behera, S Panigrahi Computational Intelligence in Pattern Recognition: Proceedings of CIPR 2019 …, 2020 | 17 | 2020 |
A modified differential evolution algorithm trained pi-sigma neural network for pattern classification S Panigrahi, AK Bhoi, Y Karali Int J Soft Comput Eng 3 (5), 133-136, 2013 | 17 | 2013 |