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Di Fatta, G. (2019) Association rules and frequent patterns. In: Ranganathan, S., Nakai, K. and Schonbach, C. (eds.) Encyclopedia of Bioinformatics and Computational Biology. Elsevier, pp. 367-373. ISBN 9780128114322 doi: https://doi.org/10.1016/B978-0-12-809633-8.20333-6
Mariani, M., Di Fatta, G. and Di Felice, M. (2018) Understanding customer satisfaction with services by leveraging big data: the role of services attributes and consumers’ cultural background. IEEE Access. ISSN 2169-3536 doi: https://doi.org/10.1109/ACCESS.2018.2887300
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Katti, A., Di Fatta, G., Naughton, T. and Engelmann, C. (2018) Epidemic failure detection and consensus for extreme parallelism. International Journal of High Performance Computing Applications, 32 (5). pp. 729-743. ISSN 1094-3420 doi: https://doi.org/10.1177/1094342017690910
Hong, X., Di Fatta, G., Chen, H. and Wang, S. (2018) Sparse least squares support vector regression for nonstationary systems. In: 2018 International Joint Conference on Neural Networks (IJCNN), 8-13 Jul 2018, Rio.
Song, X., Jiang, X., Gao, J., Cai, Z. and Hong, X. (2018) Functional locality preserving projection for dimensionality reduction. In: 2018 International Joint Conference on Neural Networks (IJCNN), 8-13,July,2018, Rio.
Ojha, V. K., Snasel, V. and Abraham, A. (2018) Multiobjective programming for type-2 hierarchical fuzzy inference trees. IEEE Transactions on Fuzzy Systems, 26 (2). pp. 915-936. ISSN 1063-6706 doi: https://doi.org/10.1109/TFUZZ.2017.2698399
Thorne, T. (2018) Approximate inference of gene regulatory network models from RNA-Seq time series data. BMC Bioinformatics, 19. 127. ISSN 1471-2105 doi: https://doi.org/10.1186/s12859-018-2125-2
Ojha, V. K., Schiano, S., Wu, C.-Y., Snásel, V. and Abraham, A. (2018) Predictive modeling of die filling of the pharmaceutical granules using the flexible neural tree. Neural Computing and Applications, 29 (7). pp. 467-481. ISSN 0941-0643 doi: https://doi.org/10.1007/s00521-016-2545-8
Hong, X. and Gao, J. (2018) Estimating the square root of probability density function on Riemannian manifold. Expert Systems: International Journal of Knowledge Engineering. e12266. ISSN 1468-0394 doi: https://doi.org/10.1111/exsy.12266
Ayiad, M. M. and Di Fatta, G. (2018) Agreement in epidemic data aggregation. In: The 23rd IEEE International Conference on Parallel and Distributed Systems (ICPADS), Dec. 15-17, 2017, Shenzhen, China.
Ayiad, M. M. and Di Fatta, G. (2018) Robust epidemic aggregation under churn. In: The 10th International Conference on Internet and Distributed Computing System 2017 (IDCS 2017), 11 -13 December 2017, Mana Island Resort & Spa, Fiji, pp. 173-185.
Gafson, A. R., Thorne, T., McKechnie, C. I. J., Jimenez, B., Nicholas, R. and Matthews, P. M. (2018) Lipoprotein markers associated with disability from multiple sclerosis. Scientific Reports, 8. 17026. ISSN 2045-2322 doi: https://doi.org/10.1038/s41598-018-35232-7
Leppänen, T., Savaglio, C., Lovén, L., Russo, W., Di Fatta, G., Riekki, J. and Fortino, G. (2018) Developing agent-based smart objects for IoT edge computing: mobile crowdsensing use case. In: 11th International Conference on Internet and Distributed Computing Systems (IDCS 2018), 11-13 October 2018, Tokyo, Japan, pp. 235-247.
Raoult, B., Di Fatta, G., Pappenberger, F. and Lawrence, B. (2018) Fast retrieval of weather analogues in a multi-petabytes archive using wavelet-based fingerprints. In: International Conference on Computational Science, 11-13 June 2018, Wuxi, China, pp. 697-710. doi: https://doi.org/10.1007/978-3-319-93701-4_55
Le, T., Stahl, F., Gaber, M. M., Gomes, J. B. and Di Fatta, G. (2017) On expressiveness and uncertainty awareness in rule-based classification for data streams. Neurocomputing, 265. 127- 141. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2017.05.081
Yang, J., Wang, H., Lu, W., Li, B., Badii, A. and Meng, Q. (2017) A no-reference optical flow-based quality evaluator for stereoscopic videos in curvelet domain. Information Sciences, 414. pp. 133-146. ISSN 0020-0255 doi: https://doi.org/10.1016/j.ins.2017.05.051
Poonpakdee, P. and Di Fatta, G. (2017) Robust and efficient membership management in large-scale dynamic networks. Future Generation Computer Systems, 75. pp. 85-93. ISSN 0167-739X doi: https://doi.org/10.1016/j.future.2017.02.033
Tennant, M., Stahl, F., Rana, O. and Gomes, J. B. (2017) Scalable real-time classification of data streams with concept drift. Future Generation Computer Systems, 75. pp. 187-199. ISSN 0167-739X doi: https://doi.org/10.1016/j.future.2017.03.026
Hong, X. and Chen, S. (2017) Recursive least squares semi-blind beamforming for MIMO using decision directed adaptation and constant modulus criterion. International Journal of Automation and Computing, 14 (4). pp. 442-449. ISSN 1476-8186 doi: https://doi.org/10.1007/s11633-017-1087-6
Ojha, V. K., Dutta, P. and Chaudhuri, A. (2017) Identifying hazardousness of sewer pipeline gas mixture using classification methods: a comparative study. Neural Computing and Applications, 28 (6). pp. 1343-1354. ISSN 0941-0643 doi: https://doi.org/10.1007/s00521-016-2443-0
Chen, S., Hong, X., Khalaf, E. F., Morfeq, A., Alotaibi, N. D. and Harris, C. J. (2017) Single-carrier frequency-domain equalization with hybrid decision feedback equalizer for Hammerstein channels containing nonlinear transmit amplifier. IEEE Transactions on Wireless Communications, 16 (5). pp. 3341-3354. ISSN 1536-1276 doi: https://doi.org/10.1109/TWC.2017.2681083
Salehe, B. R., Jones, C. I., Di Fatta, G. and McGuffin, L. (2017) RAPIDSNPs: A new computational pipeline for rapidly identifying key genetic variants reveals previously unidentified SNPs that are significantly associated with individual platelet responses. PLoS ONE, 12 (4). e0175957. ISSN 1932-6203 doi: https://doi.org/10.1371/journal.pone.0175957
Ojha, V. K., Abraham, A. and Snasel, V. (2017) Metaheuristic design of feedforward neural networks: a review of two decades of research. Engineering Applications of Artificial Intelligence, 60. pp. 97-116. ISSN 0952‐1976 doi: https://doi.org/10.1016/j.engappai.2017.01.013
Shakir Hammoodi, M., Stahl, F., Tennant, M. and Badii, A. (2017) Towards real-time feature tracking technique using adaptive micro-clusters. Expert Update, 17 (1). ISSN 1465-4091 (Special Issue on the 1st BCS SGAI Workshop on Data Stream Mining Techniques and Applications)
van der Schaaf, M., Donkers, J., Slof, B., Moonen-van Loon, J., van Tartwijk, J., Driessen, E., Badii, A., Serban, O. and Ten Cate, O. (2017) Improving workplace-based assessment and feedback by an E-portfolio enhanced with learning analytics. Educational Technology Research and Development, 65 (2). pp. 359-380. ISSN 1556-6501 doi: https://doi.org/10.1007/s11423-016-9496-8
Ojha, V. K., Abraham, A. and Snásel, V. (2017) Ensemble of heterogeneous flexible neural trees using multiobjective genetic programming. Applied Soft Computing, 52. pp. 909-924. ISSN 1568-4946 doi: https://doi.org/10.1016/j.asoc.2016.09.035
Wu, J., Meng, Q., Deng, S., Huang, H., Wu, Y. and Badii, A. (2017) Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks. PLoS ONE, 12 (2). e0172323. ISSN 1932-6203 doi: https://doi.org/10.1371/journal.pone.0172323
Hong, X., Gao, J. and Chen, S. (2017) Zero attracting recursive least squares algorithms. IEEE Transactions on Vehicular Technology, 66 (1). 213 -221. ISSN 0018-9545 doi: https://doi.org/10.1109/TVT.2016.2533664
Almutairi, M., Stahl, F. and Bramer, M. (2017) Improving modular classification rule induction with G-Prism using dynamic rule term boundaries. In: Bramer, M. and Petridis, M. (eds.) Artificial Intelligence XXXIV. Lecture Notes in Computer Science (10630). Springer, pp. 115-128. ISBN 9783319710785 doi: https://doi.org/10.1007/978-3-319-71078-5_9
Badii, A., Faulkner, R., Raval, R., Glackin, C. and Chollet, G. (2017) Accelerated encryption algorithms for secure storage and processing in the cloud. In: 2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP), 22-24 May 2017, Fez, Morocco, pp. 1-6. doi: https://doi.org/10.1109/ATSIP.2017.8075572
Chen, S., Hong, X., Khalaf, E. F., Alsaadi, F. E. and Harris, C. J. (2017) Comparative performance of complex-valued B-spline and polynomial models applied to iterative frequency-domain decision feedback equalization of Hammerstein channels. IEEE Transactions on Neural Networks and Learning Systems, 28 (12). pp. 2872-2884. ISSN 2162-237X doi: https://doi.org/10.1109/TNNLS.2016.2609001
Hong, X., Chen, S., Guo, Y. and Gao, J. (2017) l1-norm penalized orthogonal forward regression. International Journal of Systems Science, 48 (10). pp. 2195-2201. ISSN 0020-7721 doi: https://doi.org/10.1080/00207721.2017.1311383
Le, T., Stahl, F., Wrench, C. and Gaber, M. M. (2017) A statistical learning method to fast generalised rule induction directly from raw measurements. In: 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA), 18-20 Dec 2016, Anaheim, California, USA, pp. 935-938.
Pavlopoulou, N., Abushwashi, A., Stahl, F. and Scibetta, V. (2017) A text mining framework for Big Data. Expert Update, 17 (1). ISSN 1465-4091 (Special Issue on the 1st BCS SGAI Workshop on Data Stream Mining Techniques and Applications)
Chen, H., Gong, Y., Hong, X. and Chen, S. (2016) A fast adaptive tunable RBF network for nonstationary systems. IEEE Transactions on Cybernetics, 46 (12). pp. 2683-2692. ISSN 2168-2267 doi: https://doi.org/10.1109/TCYB.2015.2484378
Chen, S., Hong, X., Khalaf, E., Alsaadi, F. E. and Harris, C. J. (2016) Complex-valued B-spline neural network and its application to iterative frequency-domain decision feedback equalization for Hammerstein communication systems. In: IJCNN 2016, 25-29, July, 2016, Vancouver.
Fu, Y., Gao, J., Tien, D., Lin, Z. and Hong, X. (2016) Tensor LRR and sparse coding-based subspace clustering. IEEE Transactions on Neural Networks and Learning Systems, 27 (10). pp. 2120-2133. ISSN 2162-237X doi: https://doi.org/10.1109/TNNLS.2016.2553155
Ayiad, M., Katti, A. and Di Fatta, G. (2016) Agreement in epidemic information dissemination. In: International Conference on Internet and Distributed Computing Systems, 28-30 Sept 2016, Wuhan, China, pp. 95-106. doi: https://doi.org/10.1007/978-3-319-45940-0_9
Zhang, Q.-H., Moen, J., Lockwood, M., McCrea, I., Zhang, B.-C., McWilliams, K. A., Zong, Q.-G., Zhang, S.-R., Ruohoniemi, J. M., Thomas, E. G., Dunlop, M. W., Liu, R.-Y., Yang, H.-G., Hu, H.-Q.and Lester, M. (2016) Polar cap patch transportation beyond the classic scenario. Journal of Geophysical Research: Space Physics, 121 (9). pp. 9063-9074. ISSN 2169-9402 doi: https://doi.org/10.1002/2016JA022443
Adedoyin-Olowe, M., Gaber, M. M., Dancausa, C., Stahl, F. and Gomes, J. B. (2016) A rule dynamics approach to event detection in Twitter with its application to sports and politics. Expert Systems with Applications, 55. pp. 351-360. ISSN 0957-4174 doi: https://doi.org/10.1016/j.eswa.2016.02.028
Hong, X. and Junbin, G. (2016) A fast algorithm to estimate the square root of probability density function. In: AI2016, Thirty-sixth SGAI International Conference on Artificial Intelligence,, Dec,13-15, 2016 , Cambridge.
Wrench, C., Stahl, F., Di Fatta, G., Karthikeyan, V. and Nauck, D. D. (2016) Data stream mining of event and complex event streams: a survey of existing and future technologies and applications in big data. In: Atzmueller, M., Oussena, S. and Roth-Berghofer, T. (eds.) Enterprise Big Data Engineering, Analytics, and Management. IGI Global, pp. 24-47. ISBN 9781522502937 doi: https://doi.org/10.4018/978-1-5225-0293-7
Wang, Y., Zhang, Q. -H., Jayachandran, P. T., Lockwood, M., Zhang, S. -R., Moen, J., Xing, Z. -Y., Ma, Y. -Z. and Lester, M. (2016) A comparison between large-scale irregularities and scintillations in the polar ionosphere. Geophysical Research Letters, 43 (10). pp. 4790-4798. ISSN 1944-8007 doi: https://doi.org/10.1002/2016GL069230
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Hong, X. and Gao, J. (2016) Manifold optimization for nonnegative coefficient logistic regression. In: IJCNN 2016, 25-29, July, 2016, Vancouver.
Sun, Y., Gao, J., Hong, X., Mishra, B. and Yin, B. (2016) Heterogeneous tensor decomposition for clustering via manifold optimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38 (3). pp. 476-489. ISSN 0162-8828 doi: https://doi.org/10.1109/TPAMI.2015.2465901
Hong, X., Chen, S. and Becerra, V. (2016) Sparse density estimator with tunable kernels. Neurocomputing, 173 (3). pp. 1976-1982. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2015.08.021
Almutairi, M., Stahl, F., Jennings, M., Le, T. and Bramer, M. (2016) Towards expressive modular rule induction for numerical attributes. In: Thirty-sixth SGAI International Conference on Artificial Intelligence, 13-15 DECEMBER 2016, Cambridge, UK, pp. 229-235.
Chen, H., Gong, Y. and Hong, X. (2016) A new adaptive multiple modelling approach for non-linear and non-stationary systems. International Journal of Systems Science, 47 (9). pp. 2100-2110. ISSN 0020-7721 doi: https://doi.org/10.1080/00207721.2014.973926
Hammoodi, M., Stahl, F. and Tennant, M. (2016) Towards online concept drift detection with feature selection for data stream classification. In: 22nd European Conference on Artificial Intelligence, 29th August – 2nd September, The Hague, Holland, pp. 1549-1550.
Lester, M., Ong, L. and Schäfer, M. (2016) Information flow analysis for a dynamically typed language with staged metaprogramming. Journal of Computer Security, 24 (5). pp. 541-582. ISSN 0926-227X doi: https://doi.org/10.3233/JCS-160557
Thorne, T. (2016) NetDiff – Bayesian model selection for differential gene regulatory network inference. Scientific Reports, 6 (1). 39224. ISSN 2045-2322 doi: https://doi.org/10.1038/srep39224
Wrench, C., Stahl, F., Le, T., Di Fatta, G., Karthikeyan, V. and Nauck, D. (2016) A method of rule induction for predicting and describing future alarms in a telecommunication network. In: Thirty-sixth SGAI International Conference on Artificial Intelligence, 13-15 December 2016, Cambridge, UK, pp. 309-323.
Thorne, T. (2015) Empirical likelihood tests for nonparametric detection of differential expression from RNA-seq data. Statistical Applications in Genetics and Molecular Biology, 14 (6). pp. 575-583. ISSN 2194-6302 doi: https://doi.org/10.1515/sagmb-2015-0095
Di Fatta, G., Reade, J., Jaworska, S. and Nanda, A. (2015) Big social data and political sentiment: the tweet stream during the UK General Election 2015 campaign. In: The 8th IEEE International Conference on Social Computing and Networking (SocialCom 2015), Dec. 19-21, 2015, Chengdu, China.
Hong, X., Gao, J., Chen, S. and Zia, T. (2015) Sparse density estimation on the multinomial manifold. IEEE Transactions on Neural Networks and Learning Systems, 26 (11). pp. 2972-2977. ISSN 2162-237X doi: https://doi.org/10.1109/TNNLS.2015.2389273
Ramadan, B., Christen, P., Liang, H. and Gayler, R. W. (2015) Dynamic sorted neighborhood indexing for real-time entity resolution. Journal of Data and Information Quality, 6 (4). 15. ISSN 1936-1955 doi: https://doi.org/10.1145/2816821
Poonpakdee, P. and Di Fatta, G. (2015) Connectivity recovery in epidemic membership protocols. In: The 8th International Conference on Internet and Distributed Computing Systems, 2-4 Sep 2015, Windsor, UK, pp. 177-189. doi: https://doi.org/10.1007/978-3-319-23237-9_16
Wang, Q., Cui, M. and Liang, H. (2015) Semantic-aware blocking for entity resolution. IEEE Transactions on Knowledge and Data Engineering, 28 (1). pp. 166-180. ISSN 1558-2191 doi: https://doi.org/10.1109/TKDE.2015.2468711
Zhang, Q.-H., Lockwood, M., Foster, J. C., Zhang, S.-R., Zhang, B.-C., McCrea, I. W., Moen, J., Lester, M. and Ruohoniemi, J. M. (2015) Direct observations of the full Dungey convection cycle in the polar ionosphere for southward interplanetary magnetic field conditions. Journal of Geophysical Research: Space Physics, 120 (6). pp. 4519-4530. ISSN 2169-9402 doi: https://doi.org/10.1002/2015JA021172
Hong, X. and Gao, J. (2015) Sparse density estimation on multinomial manifold combining local component analysis. In: 2015 International Joint Conference on Neural Networks (IJCNN), 12-17, July, 2015, Killarney, Ireland.
Hong, X. and Gong, Y. (2015) A constrained recursive least squares algorithm for adaptive combination of multiple models. In: 2015 International Joint Conference on Neural Networks (IJCNN), 12-17, July, 2015, Killarney, Ireland.
Bron, E. E., Smits, M., van der Flier, W. M., Vrenken, H., Barkhof, F., Scheltens, P., Papma, J. M., Steketee, R. M.E., Orellana, C. M., Meijboom, R., Pinto, M., Meireles, J. R., Garrett, C., Bastos-Leite, A. J., Abdulkadir, A., Ronneberger, O., Amoroso, N., Bellotti, R., Cárdenas-Peña, D., Álvarez-Meza, A. M., Dolph, C. V., Iftekharuddin, K. M., Eskildsen, S. F., Coupé, P., Fonov, V. S., Franke, K., Gaser, C., Ledig, C., Guerrero, R., Tong, T., Gray, K. R., Moradi, E., Tohka, J., Routier, A., Durrleman, S., Sarica, A., Di Fatta, G., Sensi, F., Chincarini, A., Smith, G. M., Stoyanov, Z. V., Sørensen, L., Nielsen, M., Tangaro, S., Inglese, P., Wachinger, C., Reuter, M., van Swieten, J. C., Niessen, W. J. and Klein, S. (2015) Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: The CADDementia challenge. NeuroImage, 111. pp. 562-579. ISSN 1053-8119 doi: https://doi.org/10.1016/j.neuroimage.2015.01.048
Chen, S., Hong, X., Khalaf, E., Morfeq, A. and Alotaibi, N. D. (2015) Adaptive B-spline neural network based nonlinear equalization for high-order QAM systems with nonlinear transmit high power amplifier. Digital Signal Processing, 40. pp. 238-249. ISSN 1051-2004 doi: https://doi.org/10.1016/j.dsp.2015.02.006
Zliobaite, I., Budka, M. and Stahl, F. (2015) Towards cost-sensitive adaptation: when is it worth updating your predictive model? Neurocomputing, 150 (A). pp. 240-249. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2014.05.084
Ojha, V. K., Jackowski, K., Abraham, A. and Snásel, V. (2015) Dimensionality reduction, and function approximation of poly (lactic-co-glycolic acid) micro-and nanoparticle dissolution rate. International Journal of Nanomedicine, 10 (1). pp. 1119-1129. ISSN 1178-2013 doi: https://doi.org/10.2147/IJN.S71847
Al Ghamdi, S., Di Fatta, G. and Stahl, F. (2015) Optimisation techniques for parallel K-Means on MapReduce. In: Proceedings of the 8th International Conference on Internet and Distributed Computing Systems – Volume 9258, pp. 193-200.
Fu, Y., Gao, J., Hong, X. and Tien, D. (2015) Low rank representation on Riemannian manifold of symmetric positive definite matrices. In: Proceedings of the 2015 SIAM International Conference on Data Mining. SIAM, pp. 316-324. ISBN 9781611974010 doi: https://doi.org/10.1137/1.9781611974010.36
Hong, X. and Chen, S. (2015) Elastic net orthogonal forward regression. Neurocomputing, 148. pp. 551-560. ISSN 0925-2312 doi: https://doi.org/10.1016/j.neucom.2014.07.008
Hong, X., Chen, S., Gao, J. and Harris, C. J. (2015) Nonlinear identification using orthogonal forward regression with nested optimal regularization. IEEE Transactions on Cybernetics, 45 (12). pp. 2925-2936. ISSN 2168-2267 doi: https://doi.org/10.1109/TCYB.2015.2389524
Katti, A., Di Fatta, G., Naughton, T. and Engelmann, C. (2015) Scalable and fault tolerant failure detection and consensus. In: The 22nd European MPI Users’ Group Meeting (EuroMPI ’15), 21-23 September 2015, Bordeaux, France, Article No. 13. doi: https://doi.org/10.1145/2802658.2802660 (ISBN 9781450337953)
Liang, H. and Baldwin, T. (2015) A probabilistic rating auto-encoder for personalized recommender systems. In: Conference on Information and Knowledge Management, 19-23 October, Melbourne, Australia.
Spedding, A. L., Di Fatta, G. and Cannataro, M. (2015) A Genetic Algorithm for the selection of structural MRI features for classification of Mild Cognitive Impairment and Alzheimer’s Disease. In: The IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 9-12 Nov 2015, Washington D.C., pp. 1566-1571. doi: https://doi.org/10.1109/BIBM.2015.7359909
Spedding, A. L., Di Fatta, G. and Saddy, J. D. (2015) An LDA and probability-based classifier for the diagnosis of Alzheimer’s Disease from structural MRI. In: The IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 9-12 Nov 2015, Washington D.C.,, pp. 1404-1411. doi: https://doi.org/10.1109/BIBM.2015.7359883
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Tennant, M., Stahl, F. and Gomes, J. (2015) Fast adaptive real-time classification for data streams with concept drift. In: The 8th International Conference on Internet and Distributed Computing Systems, pp. 265-272.
Wrench, C., Stahl, F., Di Fatta, G., Karthikeyan, V. and Nauck, D. (2015) Towards expressive rule induction on IP network event streams. In: AI-2015 Thirty-fifth SGAI International Conference on Artificial Intelligence, 15-17 December 2015, Cambridge.
Hong, X., Chen, S., Gong, Y. and Harris, C. J. (2014) Nonlinear equalization of Hammerstein OFDM systems. IEEE Transactions on Signal Processing, 62 (21). pp. 5629-5639. ISSN 1053-587X doi: https://doi.org/10.1109/TSP.2014.2355773
Chen, H., Gong, Y., Hong, X. and Chen, S. (2014) Adaptive nonlinear equalizer using a mixture of gaussians based on-line density estimator. IEEE Transactions on Vehicular Technology, 63 (9). pp. 4265-4276. ISSN 0018-9545 doi: https://doi.org/10.1109/TVT.2014.2313458
Stahl, F. and Bramer, M. (2014) Random Prism: a noise-tolerant alternative to Random Forests. Expert Systems, 31 (5). pp. 411-420. ISSN 1468-0394 doi: https://doi.org/10.1111/exsy.12032 (special issue on innovative techniques and applications of artificial intelligence)
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