David Tian - researchr alias

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Viewing Publication 1 - 18 from 18

2024

Incorporating the COM-B Model for Behavior Change into an Agent-Based Model of Smoking Behaviors: An Object-Oriented DesignDavid Tian, Hazel Y. Squires, Charlotte Buckley, Duncan Gillespie, Harry Tattan-Birch, Lion Shahab, Robert West, Alan Brennan, Jamie Brown, Robin C. Purshouse. wsc 2024: 252-263 [doi]

2023

A filter-predictor polynomial feature based machine learning approach to predicting preterm birth from cervical electrical impedance spectroscopyDavid Tian, Zi Qiang Lang, Di Zhang, Dilly O. Anumba. bspc, 80(Part):104345, 2023. [doi]

On-device Real-time Custom Hand Gesture RecognitionEsha Uboweja, David Tian, Qifei Wang, Yi Chun Kuo, Joe Zou, Lu Wang, George Sung, Matthias Grundmann. iccvw 2023: 4275-4279 [doi]

2021

PyRoboCar: A Low-cost Deep Neural Network-based Autonomous CarGordon Hendry, Seth Harris, Ryan Goodwin, Leonid Neverov, Yunkai Xiao, David Tian, Yang Song. mcs 2021: 1-5 [doi]

2018

A Constraint-Based Random Search Algorithm for Optimizing Neural Network Architectures and Ensemble Construction in Detecting Loss of Coolant Accidents in Nuclear Power PlantsDavid Tian, Jiamei Deng, Gopika Vinod, T. V. Santhosh. dese 2018: 237-243 [doi]

A constraint-based genetic algorithm for optimizing neural network architectures for detection of loss of coolant accidents of nuclear power plantsDavid Tian, Jiamei Deng, Gopika Vinod, T. V. Santhosh, Hissam Tawfik. ijon, 322:102-119, 2018. [doi]

A Neural Networks Design Methodology for Detecting Loss of Coolant Accidents in Nuclear Power PlantsDavid Tian, Jiamei Deng, Gopika Vinod, T. V. Santhosh, Hissam Tawfik. In Mohammed M. Alani, Hissam Tawfik, Mohammed Saeed, Obinna Anya, editors, Applications of Big Data Analytics, Trends, Issues, and Challenges. pages 43-61, Springer, 2018. [doi]

Failure Modes Detection of Nuclear Systems Using Machine LearningDavid Tian, Jiamei Deng, Enrico Zio, Francesco Di Maio, Fucheng Liao. dsa 2018: 35-43 [doi]

2013

2012

Frequency scaling of power reclamation networks in outphasing PA architecturesDavid Tian, L. Richard Carley, David S. Ricketts. iscas 2012: 1058-1061 [doi]

2011

Core-generating approximate minimum entropy discretization for rough set feature selection in pattern classificationDavid Tian, Xiao-Jun Zeng, John A. Keane. ijar, 52(6):863-880, 2011. [doi]

Core-Generating Discretization for Rough Set Feature SelectionDavid Tian, Xiao-Jun Zeng, John A. Keane. trs, 13:135-158, 2011. [doi]

2010

Classification of micro-array gene expression data using neural networksDavid Tian, Keith Burley. ijcnn 2010: 1-8 [doi]

2009

Effective rough set feature selection via core-generating approximate minimum entropy discretizationDavid Tian. PhD thesis, University of Manchester, UK, 2009. [doi]

2007

Core-generating Approximate Minimum Entropy Discretization for Rough Set Feature Selection: An Experimental InvestigationDavid Tian, John A. Keane, Xiao-Jun Zeng. fuzzIEEE 2007: 1-6 [doi]

2006

Evaluating the effect of rough set feature selection on the performance of decision treesDavid Tian, John A. Keane, Xiao-Jun Zeng. grc 2006: 57-62 [doi]

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