Select Publications
Book Chapters
2019, 'Multi-step-ahead Cyclone Intensity Prediction with Bayesian Neural Networks', in , pp. 282 - 295, http://dx.doi.org/10.1007/978-3-030-29911-8_22
,2017, 'Bayesian neural learning via langevin dynamics for chaotic time series prediction', in , pp. 564 - 573, http://dx.doi.org/10.1007/978-3-319-70139-4_57
,2017, 'Co-evolutionary multi-task learning for modular pattern classification', in , pp. 692 - 701, http://dx.doi.org/10.1007/978-3-319-70136-3_73
,2017, 'Dynamic cyclone wind-intensity prediction using co-evolutionary multi-task learning', in , pp. 618 - 627, http://dx.doi.org/10.1007/978-3-319-70139-4_63
,2017, 'Multi-task modular backpropagation for feature-based pattern classification', in , pp. 558 - 566, http://dx.doi.org/10.1007/978-3-319-70136-3_59
,2017, 'Towards an affective computational model for machine consciousness', in , pp. 897 - 907, http://dx.doi.org/10.1007/978-3-319-70139-4_91
,2016, 'Chaotic feature selection and reconstruction in time series prediction', in , pp. 3 - 11, http://dx.doi.org/10.1007/978-3-319-46675-0_1
,2016, 'Coevolutionary feature selection and reconstruction in neuro-evolution for time series prediction', in , pp. 285 - 297, http://dx.doi.org/10.1007/978-3-319-28270-1_24
,2016, 'Competitive Island cooperative neuro-evolution of feedforward networks for time series prediction', in , pp. 160 - 170, http://dx.doi.org/10.1007/978-3-319-28270-1_14
,2016, 'Evolutionary multi-task learning for modular training of feedforward neural networks', in , pp. 37 - 46, http://dx.doi.org/10.1007/978-3-319-46672-9_5
,2016, 'Memetic cooperative neuro-evolution for chaotic time series prediction', in , pp. 299 - 308, http://dx.doi.org/10.1007/978-3-319-46675-0_33
,2016, 'Reverse neuron level decomposition for cooperative neuro-evolution of feedforward networks for time series prediction', in , pp. 171 - 182, http://dx.doi.org/10.1007/978-3-319-28270-1_15
,2016, 'Unconstrained face detection from a mobile source using convolutional neural networks', in , pp. 567 - 576, http://dx.doi.org/10.1007/978-3-319-46672-9_63
,2015, 'Coevolutionary recurrent neural networks for prediction of rapid intensification in wind intensity of tropical cyclones in the south pacific region', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 43 - 52, http://dx.doi.org/10.1007/978-3-319-26555-1_6
,2015, 'Competitive island-based cooperative coevolution for efficient optimization of large-scale fully-separable continuous functions', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 137 - 147, http://dx.doi.org/10.1007/978-3-319-26555-1_16
,2015, 'Enhancing competitive island cooperative neuro-evolution through backpropagation for pattern classification', in , pp. 293 - 301, http://dx.doi.org/10.1007/978-3-319-26532-2_32
,2015, 'Multi-island competitive cooperative coevolution for real parameter global optimization', in , pp. 127 - 136, http://dx.doi.org/10.1007/978-3-319-26555-1_15
,2015, 'Neuron-synapse level problem decomposition method for cooperative neuro-evolution of feedforward networks for time series prediction', in , pp. 90 - 100, http://dx.doi.org/10.1007/978-3-319-26555-1_11
,2015, 'Scaling up multi-island competitive cooperative coevolution for real parameter global optimisation', in , pp. 34 - 48, http://dx.doi.org/10.1007/978-3-319-26350-2_4
,2012, 'Application of cooperative convolution optimization for 13C metabolic flux analysis: Simulation of isotopic labeling patterns based on tandem mass spectrometry measurements', in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 178 - 187, http://dx.doi.org/10.1007/978-3-642-34859-4_18
,2010, 'An encoding scheme for cooperative coevolutionary feedforward neural networks', in , pp. 253 - 262, http://dx.doi.org/10.1007/978-3-642-17432-2_26
,2009, 'Solving the forward kinematics of the 3RPR planar parallel manipulator using a hybrid meta-heuristic paradigm', in Proceedings of IEEE International Symposium on Computational Intelligence in Robotics and Automation, CIRA, pp. 177 - 182, http://dx.doi.org/10.1109/CIRA.2009.5423213
,Journal articles
2024, 'A clustering and graph deep learning-based framework for COVID-19 drug repurposing', Expert Systems with Applications, 249, http://dx.doi.org/10.1016/j.eswa.2024.123560
,2024, 'A review of ensemble learning and data augmentation models for class imbalanced problems: Combination, implementation and evaluation', Expert Systems with Applications, 244, http://dx.doi.org/10.1016/j.eswa.2023.122778
,2024, 'A unified machine learning framework for basketball team roster construction: NBA and WNBA[Formula presented]', Applied Soft Computing, 153, http://dx.doi.org/10.1016/j.asoc.2024.111298
,2024, 'Sequential reversible jump MCMC for dynamic Bayesian neural networks', Neurocomputing, 564, http://dx.doi.org/10.1016/j.neucom.2023.126960
,2024, 'A Quantum-Inspired Predator–Prey Algorithm for Real-Parameter Optimization', Algorithms, 17, http://dx.doi.org/10.3390/a17010033
,2024, 'ReefCoreSeg: A Clustering-Based Framework for Multi-Source Data Fusion for Segmentation of Reef Drill Cores', IEEE Access, 12, pp. 12164 - 12180, http://dx.doi.org/10.1109/ACCESS.2023.3341156
,2023, 'Memory capacity of recurrent neural networks with matrix representation', Neurocomputing, 560, http://dx.doi.org/10.1016/j.neucom.2023.126824
,2023, 'Surrogate-assisted distributed swarm optimisation for computationally expensive geoscientific models', Computational Geosciences, 27, pp. 939 - 954, http://dx.doi.org/10.1007/s10596-023-10223-4
,2023, 'Gradient boosting Bayesian neural networks via Langevin MCMC', Neurocomputing, 558, http://dx.doi.org/10.1016/j.neucom.2023.126726
,2023, 'DeepGR4J: A deep learning hybridization approach for conceptual rainfall-runoff modelling', Environmental Modelling and Software, 169, http://dx.doi.org/10.1016/j.envsoft.2023.105831
,2023, 'Deep learning for COVID-19 topic modelling via Twitter: Alpha, Delta and Omicron', PLoS ONE, 18, http://dx.doi.org/10.1371/journal.pone.0288681
,2023, 'Reef-Insight: A Framework for Reef Habitat Mapping with Clustering Methods Using Remote Sensing', Information (Switzerland), 14, pp. 373 - 373, http://dx.doi.org/10.3390/info14070373
,2023, 'Unsupervised machine learning framework for discriminating major variants of concern during COVID-19', PLoS ONE, 18, http://dx.doi.org/10.1371/journal.pone.0285719
,2023, 'Cyclone trajectory and intensity prediction with uncertainty quantification using variational recurrent neural networks', Environmental Modelling and Software, 162, http://dx.doi.org/10.1016/j.envsoft.2023.105654
,2023, 'Physics-informed neural entangled-ladder network for inhalation impedance of the respiratory system', Computer Methods and Programs in Biomedicine, 231, http://dx.doi.org/10.1016/j.cmpb.2023.107421
,2023, 'An evaluation of Google Translate for Sanskrit to English translation via sentiment and semantic analysis', Natural Language Processing Journal, 4, pp. 100025 - 100025, http://dx.doi.org/10.1016/j.nlp.2023.100025
,2022, 'Bayesian neuroevolution using distributed swarm optimization and tempered MCMC[Formula presented]', Applied Soft Computing, 129, http://dx.doi.org/10.1016/j.asoc.2022.109528
,2022, 'CoviRx: A User-Friendly Interface for Systematic Down-Selection of Repurposed Drug Candidates for COVID-19', Data, 7, http://dx.doi.org/10.3390/data7110164
,2022, 'Evolutionary bagging for ensemble learning', Neurocomputing, 510, pp. 1 - 14, http://dx.doi.org/10.1016/j.neucom.2022.08.055
,2022, 'Spatio temporal hydrological extreme forecasting framework using LSTM deep learning model', Stochastic Environmental Research and Risk Assessment, 36, pp. 3467 - 3485, http://dx.doi.org/10.1007/s00477-022-02204-3
,2022, 'Artificial intelligence for topic modelling in Hindu philosophy: Mapping themes between the Upanishads and the Bhagavad Gita', PLoS ONE, 17, http://dx.doi.org/10.1371/journal.pone.0273476
,2022, 'Deep learning for predicting respiratory rate from biosignals', Computers in Biology and Medicine, 144, http://dx.doi.org/10.1016/j.compbiomed.2022.105338
,2022, 'A Comparative Study of Convolutional Neural Networks and Conventional Machine Learning Models for Lithological Mapping Using Remote Sensing Data', Remote Sensing, 14, http://dx.doi.org/10.3390/rs14040819
,2022, 'Distributed Bayesian optimisation framework for deep neuroevolution', Neurocomputing, 470, pp. 51 - 65, http://dx.doi.org/10.1016/j.neucom.2021.10.045
,2022, 'A review of machine learning in processing remote sensing data for mineral exploration', Remote Sensing of Environment, 268, http://dx.doi.org/10.1016/j.rse.2021.112750
,2022, 'Deep learning via LSTM models for COVID-19 infection forecasting in India', PLoS ONE, 17, http://dx.doi.org/10.1371/journal.pone.0262708
,2022, 'Revisiting Bayesian Autoencoders With MCMC', IEEE Access, 10, pp. 40482 - 40495, http://dx.doi.org/10.1109/ACCESS.2022.3163270
,2022, 'Semantic and Sentiment Analysis of Selected Bhagavad Gita Translations Using BERT-Based Language Framework', IEEE Access, 10, pp. 21291 - 21315, http://dx.doi.org/10.1109/ACCESS.2022.3152266
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