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A Study of Aquatic Toxicity Using Artificial Neural Networks.

, , , and . KES, volume 2774 of Lecture Notes in Computer Science, page 911-918. Springer, (2003)

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The Importance of Scaling in Data Mining for Toxicity Prediction., , , and . Journal of Chemical Information and Computer Sciences, 42 (5): 1250-1255 (2002)Using Pareto points for model identification in predictive toxicology., , and . J. Cheminformatics, (2013)Combining Classifiers of Pesticides Toxicity through a Neuro-fuzzy Approach., , , and . Multiple Classifier Systems, volume 2364 of Lecture Notes in Computer Science, page 293-303. Springer, (2002)Toxicity risk assessment from heterogeneous uncertain data with possibility-probability distribution., and . FUZZ-IEEE, IEEE, (2013)Integration strategies for toxicity data from an empirical perspective., and . UKCI, page 1-8. IEEE, (2014)Deep Quantile Regression for Unsupervised Anomaly Detection in Time-Series., and . SN Comput. Sci., 2 (6): 475 (2021)Quantum ReLU activation for Convolutional Neural Networks to improve diagnosis of Parkinson's disease and COVID-19., , , and . Expert Syst. Appl., (2022)Engineering Data- & Model-Driven Applications: EDMA-2017 special issue editorial., , and . Expert Syst. J. Knowl. Eng., (2021)Towards a Data Quality Framework for Heterogeneous Data., , , and . iThings/GreenCom/CPSCom/SmartData, page 155-162. IEEE Computer Society, (2017)Development of Multi-output Neural Networks for Data Integration - A Case Study., , , and . Innovations in Hybrid Intelligent Systems, volume 44 of Advances in Soft Computing, Springer, (2008)