Fuzzy grey relational analysis for software effort estimation M Azzeh, D Neagu, PI Cowling Empirical Software Engineering 15 (1), 60-90, 2010 | 113 | 2010 |
Information quality framework for e-learning systems M Alkhattabi, D Neagu, A Cullen Knowledge Management & E-Learning: An International Journal 2 (4), 340-362, 2010 | 97 | 2010 |
Assessing information quality of e-learning systems: a web mining approach M Alkhattabi, D Neagu, A Cullen Computers in Human Behavior 27 (2), 862-873, 2011 | 91 | 2011 |
Interpreting random forest classification models using a feature contribution method A Palczewska, J Palczewski, RM Robinson, D Neagu Integration of reusable systems, 193-218, 2014 | 84 | 2014 |
Analogy-based software effort estimation using Fuzzy numbers M Azzeh, D Neagu, PI Cowling Journal of Systems and Software 84 (2), 270-284, 2011 | 81 | 2011 |
Machine learning algorithms: a study on noise sensitivity E Kalapanidas, N Avouris, M Craciun, D Neagu Proc. 1st Balcan Conference in Informatics, 356-365, 2003 | 67 | 2003 |
Social media analysis for product safety using text mining and sentiment analysis H Isah, P Trundle, D Neagu 2014 14th UK workshop on computational intelligence (UKCI), 1-7, 2014 | 62 | 2014 |
Data governance in predictive toxicology: A review X Fu, A Wojak, D Neagu, M Ridley, K Travis Journal of cheminformatics 3 (1), 1-16, 2011 | 59 | 2011 |
Improving analogy software effort estimation using fuzzy feature subset selection algorithm M Azzeh, D Neagu, P Cowling Proceedings of the 4th international workshop on Predictor models in …, 2008 | 58 | 2008 |
The importance of scaling in data mining for toxicity prediction P Mazzatorta, E Benfenati, D Neagu, G Gini Journal of chemical information and computer sciences 42 (5), 1250-1255, 2002 | 58 | 2002 |
Interpreting random forest models using a feature contribution method A Palczewska, J Palczewski, RM Robinson, D Neagu 2013 IEEE 14th International Conference on Information Reuse & Integration …, 2013 | 50 | 2013 |
Computational intelligence: engineering of hybrid systems MG Negoita, D Neagu, V Palade Springer Science & Business Media, 2005 | 49 | 2005 |
Validation of counter propagation neural network models for predictive toxicology according to the OECD principles: a case study M Vračko, V Bandelj, P Barbieri, E Benfenati, Q Chaudhry, M Cronin, ... SAR and QSAR in Environmental Research 17 (3), 265-284, 2006 | 47 | 2006 |
Interpretation of trained neural networks by rule extraction V Palade, DC Neagu, RJ Patton International Conference on Computational Intelligence, 152-161, 2001 | 37 | 2001 |
Predictive model representation and comparison: Towards data and predictive models governance M Makhtar, DC Neagu, M Ridley 2010 UK Workshop on Computational Intelligence (UKCI), 1-6, 2010 | 30 | 2010 |
Towards a fuzzy expert system on toxicological data quality assessment L Yang, D Neagu, MTD Cronin, M Hewitt, SJ Enoch, JC Madden, ... Molecular informatics 32 (1), 65-78, 2013 | 28 | 2013 |
Software project similarity measurement based on fuzzy C-means M Azzeh, D Neagu, P Cowling International Conference on software process, 123-134, 2008 | 28 | 2008 |
Software effort estimation based on weighted fuzzy grey relational analysis M Azzeh, D Neagu, P Cowling Proceedings of the 5th International Conference on Predictor Models in …, 2009 | 27 | 2009 |
Fusing integrated visual vocabularies-based bag of visual words and weighted colour moments on spatial pyramid layout for natural scene image classification Y Alqasrawi, D Neagu, PI Cowling Signal, Image and Video Processing 7 (4), 759-775, 2013 | 26 | 2013 |
Stemming techniques for Arabic words: A comparative study MY Al-Nashashibi, D Neagu, AA Yaghi 2010 2nd International Conference on Computer Technology and Development …, 2010 | 24 | 2010 |