 (29) The impact of resource dependence of the mechanisms of life on the spatial population dynamics of an in silico microbial communityA.J. Daly, J.M. Baetens and B. De Baets(2016) CHAOS. 26, 123121. |
| (28) On the compatibility of a crisp relation with a fuzzy equivalence relationB. De Baets, H. Bouremel and L. Zedam(2016) IRANIAN JOURNAL OF FUZZY SYSTEMS. 13, 15-31. |
| (27) Stability of cellular automata trajectories revisited: branching walks and Lyapunov profilesJ.M. Baetens and J. Gravner(2016) JOURNAL OF NONLINEAR SCIENCE. 26, 1329–1367. |
| (26) Stochastic simulation of precipitation-consistent daily reference evapotranspiration using vine copulasM.T. Pham, H. Vernieuwe, B. De Baets and N.E.C. Verhoest(2016) STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT. 30, 2197-2214. |
| (25) Large-scale distance metric learning for k-nearest neighbours regressionB. Nguyen, C. Morell and B. De Baets(2016) NEUROCOMPUTING. 214, 805-814. |
| (24) Spatially explicit modelling of the Belgian major endurance event `The 100 km Dodentocht'S. Van Nieuland, J.M. Baetens and B. De Baets(2016) PLOS ONE. 11, e0164981. |
| (23) Long-term dynamics in local host-parasite interactions linked to regional population trendsZ. Ladin, V. d’Amico, J.M. Baetens, R.R. Roth and W.G. Shriver(2016) ECOSPHERE. 7, e01420. |
| (22) Predicting metapopulation responses to conservation in human-dominated landscapesZ. Ladin, V. d’Amico, J.M. Baetens, R.R. Roth and W.G. Shriver(2016) FRONTIERS IN ECOLOGY AND EVOLUTION. 4, 122. |
| (21) Focal copulas: a common framework for various classes of semilinear copulasT. Jwaid, B. De Baets and H. De Meyer(2016) MEDITERRANEAN JOURNAL OF MATHEMATICS. 13, 2911-2934. |
| (20) The scorix: a popular representation of votes revisitedR. Pérez-Fernández, M. Rademaker and B. De Baets(2016) INTERNAT. J. APPROXIMATE REASONING. 78, 241-251. |
| (19) Exact and efficient top-K inference for multi-target prediction by querying separable linear relational modelsM. Stock, K. Dembczyński, B. De Baets and W. Waegeman(2016) DATA MINING AND KNOWLEDGE DISCOVERY. 30, 1370-1394. |
| (18) Classification of cellular automata through texture analysisN. Rosa da Silva, J.M. Baetens, M.W. da Silva Oliveira, B. De Baets and O.M. Bruno(2016) INFORMATION SCIENCES. 370-371, 33-49. |
| (17) Opportunistic mobile air pollution monitoring: a case study with city wardens in AntwerpJ. Van den Bossche, J. Theunis, B. Elen, J. Peters, D. Botteldooren and B. De Baets(2016) ATMOSPHERIC ENVIRONMENT. 141, 408-421. |
| (16) Multivariate upper semi-linear copulasJ.J. Arias García, H. De Meyer and B. De Baets(2016) INFORMATION SCIENCES. 360, 289-300. |
| (15) Needles: large-scale genomic prediction with marker-by-environment interactionA. De Coninck, B. De Baets, D. Kourounis, F. Verbosio, O. Schenk, S. Maenhout and J. Fostier(2016) GENETICS. 203, 543-555. |
| (14) A clone-based representation of the fuzzy tolerance or equivalence relations a strict order relation is compatible withB. De Baets, L. Zedam and A. Kheniche(2016) FUZZY SETS AND SYSTEMS. 296, 35-50. |
| (13) Computation and visualisation of the accuracy of old maps using differential distortion analysisM. Claeys Boùùaert, B. De Baets, S. Vervust, T. Neutens, P. De Maeyer and N. Van de Weghe(2016) INTERNAT. J. OF GEOGRAPHICAL INFORMATION SCIENCE. 30, 1255-1280. |
| (12) Separability criteria for the evaluation of boundary detection benchmarksC. Lopez-Molina, H. Bustince and B. De Baets(2016) IEEE TRANSACTIONS ON IMAGE PROCESSING. 25, 1047-1055. |
| (11) Representations of votes facilitating monotonicity-based ranking rules: from votrix to votexR. Pérez-Fernández, M. Rademaker, P. Alonso, I. Díaz, S. Montes and B. De Baets(2016) INTERNAT. J. APPROXIMATE REASONING. 73, 87-107. |
| (10) In silico substrate dependence increases community productivity, threatens biodiversityA.J. Daly, J.M. Baetens and B. De Baets(2016) PHYSICAL REVIEW E. 93, 042414. |
| (9) Twofold consensus for boundary detection ground truthC. Lopez-Molina, B. De Baets and H. Bustince(2016) INTERNAT. J. KNOWLEDGE-BASED SYSTEMS. 98, 162-171. |
| (8) The potential of milk fatty acids as biomarkers for methane emissions in dairy cows: a quantitative multi-study survey of literature dataJ. Castro-Montoya, S. De Campeneere, B. De Baets and V. Fievez(2016) JOURNAL OF AGRICULTURAL SCIENCE. 154, 515-531. |
| (7) A historical account of types of fuzzy sets and their relationshipsH. Bustince, E. Barrenechea, M. Pagola, J. Fernandez, Z.S. Xu, B. Bedregal, J. Montero, H. Hagras, F. Herrera and B. De Baets(2016) IEEE TRANSACTIONS ON FUZZY SYSTEMS. 24, 179-194. |
| (6) Data prevalence matters when assessing species' responses using data-driven species distribution modelsS. Fukuda and B. De Baets(2016) ECOLOGICAL INFORMATICS. 32, 69-78. |
| (5) Data-driven recipe completion using machine learning methodsM. De Clercq, M. Stock, B. De Baets and W. Waegeman(2016) TRENDS IN FOOD SCIENCE & TECHNOLOGY. 49, 1-13. |
| (4) Compatibility of fuzzy relationsA. Kheniche, B. De Baets and L. Zedam(2016) INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS. 31, 240-256. |
| (3) Prediction of specialty coffee cup quality based on near infrared spectra of green coffee beansK. Tolessa, M. Rademaker, B. De Baets and P. Boeckx(2016) TALANTA. 150, 367-374. |
| (2) Multivariate Bertino copulasJ.J. Arias García, H. De Meyer and B. De Baets(2016) JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS. 434, 1346-1364. |
| (1) A review of the relationships between implication, negation and aggregation functions from the point of view of material implicationA. Pradera, G. Beliakov, H. Bustince and B. De Baets(2016) INFORMATION SCIENCES. 329, 357-380. |