Robert Andrews
Title
Cited by
Cited by
Year
Survey and critique of techniques for extracting rules from trained artificial neural networks
R Andrews, J Diederich, AB Tickle
Knowledge-based systems 8 (6), 373-389, 1995
13371995
The truth will come to light: Directions and challenges in extracting the knowledge embedded within trained artificial neural networks
AB Tickle, R Andrews, M Golea, J Diederich
IEEE Transactions on Neural Networks 9 (6), 1057-1068, 1998
5221998
Rule extraction from a constrained error back propagation MLP
R Andrews, S Geva
Proc. 5th Australian Conference on Neural Networks, 9-12, 1994
871994
Event log imperfection patterns for process mining: Towards a systematic approach to cleaning event logs
S Suriadi, R Andrews, AHM ter Hofstede, MT Wynn
Information Systems 64, 132-150, 2017
762017
Rule extraction from local cluster neural nets
R Andrews, S Geva
Neurocomputing 47 (1-4), 1-20, 2002
592002
RULEX & CEBP Networks as the Basis for a Rule Refinement System
R Andrews, S Geva
Hybrid problems, hybrid solutions 27, 1, 1995
471995
Inserting and extracting knowledge from constrained error back-propagation networks.
R Andrews
Proceedings of the 6th Australian Conference on Neural Networks, 1995
441995
Lessons from past, current issues, and future research directions in extracting the knowledge embedded in artificial neural networks
AB Tickle, F Maire, G Bologna, R Andrews, J Diederich
International Workshop on Hybrid Neural Systems, 226-239, 1998
331998
Rules and local function networks
R Andrews, S Geva
Proceedings of the Workshop on Rule Extraction From Trained Artificial …, 1996
291996
Rule extraction from trained artificial neural networks
R Andrews
Neural network analysis, architectures and algorithms, 61-99, 1997
271997
An evaluation and comparison of techniques for extracting and refining rules from artificial neural networks
R Andrews, R Cable, J Diederich, S Geva, M Golea, R Hayward, ...
QUT NRC (February 1996), 1996
271996
Lessons from the field: A reflection on teaching SAP R/3 and ERP implementation issues
G Stewart, G Gable, R Andrews, M Rosemann, T Chan
AMCIS 1999 Proceedings, 277, 1999
251999
On the effects of initialising a neural network with prior knowledge
R Andrews, S Geva
ICONIP'99. ANZIIS'99 & ANNES'99 & ACNN'99. 6th International Conference on …, 1999
131999
Rule-Extraction from trained neural networks: Different techniques for the determination of herbicides for the plant protection advisory system PRO_PLANT
U Visser, A Tickle, R Hayward, R Andrews
Proc. of the rule extraction from trained ANN workshop, Brighton, UK, 133-139, 1996
111996
Semi-supervised log pattern detection and exploration using event concurrence and contextual information
X Lu, D Fahland, R Andrews, S Suriadi, MT Wynn, AHM ter Hofstede, ...
OTM Confederated International Conferences" On the Move to Meaningful …, 2017
102017
Refining Expert Knowledge with an Artificial Neural Network.
R Andrews, S Geva
ICONIP (2), 847-850, 1997
101997
Detection and interactive repair of event ordering imperfection in process logs
PM Dixit, S Suriadi, R Andrews, MT Wynn, AHM ter Hofstede, JCAM Buijs, ...
International Conference on Advanced Information Systems Engineering, 274-290, 2018
82018
A review of techniques for extracting rules from trained artificial neural networks
R Andrews, AB Tickle, J Diederich
Clinical applications of artificial neural networks, 256-297, 2001
62001
Healthcare process analysis
R Andrews, S Suriadi, M Wynn, AH ter Hofstede
Process Modelling and Management for HealthCare; CRC Press: Boca Raton, FL, USA, 2017
52017
Leveraging data quality to better prepare for process mining: an approach illustrated through analysing road trauma pre-hospital retrieval and transport processes in Queensland
R Andrews, MT Wynn, K Vallmuur, AHM Ter Hofstede, E Bosley, M Elcock, ...
International journal of environmental research and public health 16 (7), 1138, 2019
42019
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