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Mashud Rana
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2020 – today
- 2024
- [j7]Sarah Almaghrabi, Mashud Rana, Margaret Hamilton, Mohammad Saiedur Rahaman:
Multidimensional dynamic attention for multivariate time series forecasting. Appl. Soft Comput. 167: 112350 (2024) - [j6]Sarah Almaghrabi
, Mashud Rana, Margaret Hamilton
Multivariate solar power time series forecasting using multilevel data fusion and deep neural networks. Inf. Fusion 104: 102180 (2024) - [j5]Mashud Rana
Hierarchical Semi-Supervised Approach for Classifying Activities of Workers Utilising Indoor Trajectory Data. Internet Things 28: 101386 (2024) - 2023
- [c31]Mashud Rana, Ashfaqur Rahman, Mahathir Almashor
Automatic Classification of Sensors in Buildings: Learning from Time Series Data. AI (1) 2023: 367-378 - [c30]Mahathir Almashor
What's The Point: AutoEncoding Building Point Names. BuildSys 2023: 256-260 - [i5]Mashud Rana, Ashfaqur Rahman, Daniel V. Smith:
A Semi-supervised Approach for Activity Recognition from Indoor Trajectory Data. CoRR abs/2301.03134 (2023) - 2022
- [j4]Sarah Almaghrabi
Solar power time series forecasting utilising wavelet coefficients. Neurocomputing 508: 182-207 (2022) - [c29]Joel Janek Dabrowski, Ashfaqur Rahman, Andrew D. Hellicar, Mashud Rana
Deep Learning for Prawn Farming - Forecasting and Anomaly Detection. PAKDD (3) 2022: 29-41 - [i4]Joel Janek Dabrowski, Ashfaqur Rahman, Andrew D. Hellicar, Mashud Rana
Deep Learning for Prawn Farming: Forecasting and Anomaly Detection. CoRR abs/2205.06359 (2022) - [i3]Sarah Almaghrabi
Solar Power Time Series Forecasting Utilising Wavelet Coefficients. CoRR abs/2210.00269 (2022) - [i2]Peter Baumgartner, Daniel V. Smith, Mashud Rana, Reena Kapoor, Elena Tartaglia, Andreas Schutt, Ashfaqur Rahman, John Taylor
Movement Analytics: Current Status, Application to Manufacturing, and Future Prospects from an AI Perspective. CoRR abs/2210.01344 (2022) - 2021
- [c28]Yang Lin
SSDNet: State Space Decomposition Neural Network for Time Series Forecasting. ICDM 2021: 370-378 - [c27]Sarah Almaghrabi
Forecasting Regional Level Solar Power Generation Using Advanced Deep Learning Approach. IJCNN 2021: 1-7 - [c26]Sarah Almaghrabi
Spatially Aggregated Photovoltaic Power Prediction Using Wavelet and Convolutional Neural Networks. IJCNN 2021: 1-8 - [c25]Yang Lin
Temporal Convolutional Attention Neural Networks for Time Series Forecasting. IJCNN 2021: 1-8 - [i1]Yang Lin, Irena Koprinska, Mashud Rana:
SSDNet: State Space Decomposition Neural Network for Time Series Forecasting. CoRR abs/2112.10251 (2021) - 2020
- [j3]Mashud Rana
Investigating data-driven approaches to understand the interaction between water quality and physiological response of sentinel oysters in natural environment. Comput. Electron. Agric. 175: 105545 (2020) - [c24]Yang Lin
Solar Power Forecasting Based on Pattern Sequence Similarity and Meta-learning. ICANN (1) 2020: 271-283 - [c23]Yang Lin, Irena Koprinska, Mashud Rana
SpringNet: Transformer and Spring DTW for Time Series Forecasting. ICONIP (3) 2020: 616-628 - [c22]Yang Lin
Temporal Convolutional Neural Networks for Solar Power Forecasting. IJCNN 2020: 1-8 - [c21]Mashud Rana
A Data-driven Approach for Forecasting State Level Aggregated Solar Photovoltaic Power Production. IJCNN 2020: 1-8
2010 – 2019
- 2019
- [c20]Irena Koprinska, Mashud Rana
Dynamic Ensemble Using Previous and Predicted Future Performance for Multi-step-ahead Solar Power Forecasting. ICANN (4) 2019: 436-449 - [c19]Yang Lin
Pattern Sequence Neural Network for Solar Power Forecasting. ICONIP (5) 2019: 727-737 - 2018
- [c18]Mashud Rana
Comparison and Sensitivity Analysis of Methods for Solar PV Power Prediction. PAKDD (Workshops) 2018: 333-344 - 2017
- [c17]Zheng Wang, Irena Koprinska, Mashud Rana
Solar Power Forecasting Using Pattern Sequences. ICANN (2) 2017: 486-494 - [c16]Zheng Wang, Irena Koprinska, Mashud Rana
Solar power prediction using weather type pair patterns. IJCNN 2017: 4259-4266 - 2016
- [j2]Mashud Rana
Forecasting electricity load with advanced wavelet neural networks. Neurocomputing 182: 118-132 (2016) - [c15]Mashud Rana
Cooperative neuro-evolutionary recurrent neural networks for solar power prediction. CEC 2016: 4691-4698 - [c14]Mashud Rana
Extended Weighted Nearest Neighbor for Electricity Load Forecasting. ICANN (2) 2016: 299-307 - [c13]Zheng Wang, Irena Koprinska
Clustering based methods for solar power forecasting. IJCNN 2016: 1487-1494 - [c12]Mashud Rana
Solar power forecasting using weather type clustering and ensembles of neural networks. IJCNN 2016: 4962-4969 - 2015
- [j1]Irena Koprinska
Correlation and instance based feature selection for electricity load forecasting. Knowl. Based Syst. 82: 29-40 (2015) - [c11]Mashud Rana
Forecasting solar power generated by grid connected PV systems using ensembles of neural networks. IJCNN 2015: 1-8 - 2014
- [c10]Mashud Rana
Forecasting hourly electricity load profile using neural networks. IJCNN 2014: 824-831 - 2013
- [c9]Mashud Rana
Feature Selection for Neural Network-Based Interval Forecasting of Electricity Demand Data. ICANN 2013: 389-396 - [c8]Mashud Rana
Wavelet Neural Networks for Electricity Load Forecasting - Dealing with Border Distortion and Shift Invariance. ICANN 2013: 571-578 - [c7]Irena Koprinska
Combining pattern sequence similarity with neural networks for forecasting electricity demand time series. IJCNN 2013: 1-8 - [c6]Mashud Rana
Prediction intervals for electricity load forecasting using neural networks. IJCNN 2013: 1-8 - 2012
- [c5]Irena Koprinska
Electricity Load Forecasting: A Weekday-Based Approach. ICANN (2) 2012: 33-41 - [c4]Mashud Rana
Feature Selection for Electricity Load Prediction. ICONIP (2) 2012: 526-534 - [c3]Alexandra Kotillova, Irena Koprinska
Statistical and Machine Learning Methods for Electricity Demand Prediction. ICONIP (2) 2012: 535-542 - [c2]Mashud Rana
Electricity load forecasting using non-decimated wavelet prediction methods with two-stage feature selection. IJCNN 2012: 1-8 - 2011
- [c1]Irena Koprinska
Yearly and seasonal models for electricity load forecasting. IJCNN 2011: 1474-1481
Coauthor Index
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last updated on 2024-12-10 20:46 CET by the dblp team
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