A Comparison of Clustering and Prediction Methods for Identifying Key Chemical–Biological Features Affecting Bioreactor Performance
暂无分享,去创建一个
Bhushan Gopaluni | Yiting Tsai | Susan A. Baldwin | Lim C. Siang | Bhushan Gopaluni | S. Baldwin | Yiting Tsai
[1] Wendy R. Fox,et al. Finding Groups in Data: An Introduction to Cluster Analysis , 1991 .
[2] Lennart Ljung,et al. System Identification: Theory for the User , 1987 .
[3] Donald Geman,et al. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[4] Eduardo F. Morales,et al. An Introduction to Reinforcement Learning , 2011 .
[5] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[6] Beatriz de la Iglesia,et al. Clustering Rules: A Comparison of Partitioning and Hierarchical Clustering Algorithms , 2006, J. Math. Model. Algorithms.
[7] Hong Han,et al. Variable selection using Mean Decrease Accuracy and Mean Decrease Gini based on Random Forest , 2016, 2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS).
[8] Sirish L. Shah,et al. An Introduction to Alarm Analysis and Design , 2009 .
[9] Dianhui Wang,et al. Stochastic Configuration Networks: Fundamentals and Algorithms , 2017, IEEE Transactions on Cybernetics.
[10] Carl E. Rasmussen,et al. The Infinite Gaussian Mixture Model , 1999, NIPS.
[11] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[12] Wei-Yin Loh,et al. Classification and regression trees , 2011, WIREs Data Mining Knowl. Discov..
[13] Sirish L. Shah,et al. An Overview of Industrial Alarm Systems: Main Causes for Alarm Overloading, Research Status, and Open Problems , 2016, IEEE Transactions on Automation Science and Engineering.
[14] Leo Breiman,et al. Bagging Predictors , 1996, Machine Learning.
[15] Jason Weston,et al. A unified architecture for natural language processing: deep neural networks with multitask learning , 2008, ICML '08.
[16] Keaton Larson Lesnik,et al. Predicting Microbial Fuel Cell Biofilm Communities and Bioreactor Performance using Artificial Neural Networks. , 2017, Environmental science & technology.
[17] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[18] Achim Zeileis,et al. Conditional variable importance for random forests , 2008, BMC Bioinformatics.
[19] C. Quince,et al. Dirichlet Multinomial Mixtures: Generative Models for Microbial Metagenomics , 2012, PloS one.
[20] E. Alzate. Modelos de mezclas Bernoulli con regresión logística: una aplicación en la valoración de carteras de crédito , 2020 .
[21] J. Raes,et al. Microbial interactions: from networks to models , 2012, Nature Reviews Microbiology.
[22] A Dennis Lemly,et al. Aquatic selenium pollution is a global environmental safety issue. , 2004, Ecotoxicology and environmental safety.
[23] Pedro Larrañaga,et al. A review of feature selection techniques in bioinformatics , 2007, Bioinform..
[24] Brian J. McGill,et al. A network approach for inferring species associations from co-occurrence data , 2016 .
[25] Hans-Peter Kriegel,et al. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.
[26] Klaus-Robert Müller,et al. Introduction to machine learning for brain imaging , 2011, NeuroImage.
[27] Achim Zeileis,et al. Bias in random forest variable importance measures: Illustrations, sources and a solution , 2007, BMC Bioinformatics.
[28] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[29] Akira Sasaki,et al. Statistical Mechanics of Population: The Lattice Lotka-Volterra Model , 1992 .
[30] George Cybenko,et al. Approximation by superpositions of a sigmoidal function , 1989, Math. Control. Signals Syst..
[31] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[32] Lu Zhang,et al. Data-Based Predictive Control for Wastewater Treatment Process , 2018, IEEE Access.
[33] Jan M. Maciejowski,et al. Predictive control : with constraints , 2002 .
[34] Kurt Hornik,et al. Multilayer feedforward networks are universal approximators , 1989, Neural Networks.
[35] Thomas F. Edgar,et al. Process Dynamics and Control , 1989 .
[36] Heng-Tze Cheng,et al. Wide & Deep Learning for Recommender Systems , 2016, DLRS@RecSys.
[37] William M. Campbell,et al. Support vector machines for speaker and language recognition , 2006, Comput. Speech Lang..
[38] Xiaoli Chai,et al. Effect of different carbon sources on denitrification performance, microbial community structure and denitrification genes. , 2018, The Science of the total environment.
[39] Junfei Qiao,et al. Multiobjective design of fuzzy neural network controller for wastewater treatment process , 2018, Appl. Soft Comput..
[40] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[41] J. A. Hartigan,et al. A k-means clustering algorithm , 1979 .
[42] Hongzhe Li. Microbiome, Metagenomics, and High-Dimensional Compositional Data Analysis , 2015 .
[43] P. Rousseeuw. Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .
[44] David J. Edwards,et al. Hypothesis Testing and Power Calculations for Taxonomic-Based Human Microbiome Data , 2012, PloS one.
[45] R. Sokal,et al. THE COMPARISON OF DENDROGRAMS BY OBJECTIVE METHODS , 1962 .
[46] Karoline Faust,et al. Multi-stability and the origin of microbial community types , 2017, The ISME Journal.
[47] Geoffrey E. Hinton,et al. Learning representations by back-propagating errors , 1986, Nature.
[48] Yongmei Cheng,et al. A Comparison of Methods for Clustering 16S rRNA Sequences into OTUs , 2013, PloS one.
[49] E. Mcarthur,et al. RCLUS, A NEW PROGRAM FOR CLUSTERING ASSOCIATED SPECIES: A DEMONSTRATION USING A MOJAVE DESERT PLANT COMMUNITY DATASET , 2006 .
[50] Ali S. Hadi,et al. Finding Groups in Data: An Introduction to Chster Analysis , 1991 .
[51] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[52] Y. Takeuchi. Global Dynamical Properties of Lotka-Volterra Systems , 1996 .
[53] Junfei Qiao,et al. Adaptive fuzzy neural network control of wastewater treatment process with multiobjective operation , 2018, Neurocomputing.
[54] J. Laurie Snell,et al. Markov Random Fields and Their Applications , 1980 .
[55] Martin Grube,et al. Analyzing the antagonistic potential of the lichen microbiome against pathogens by bridging metagenomic with culture studies , 2015, Front. Microbiol..
[56] Kevin P. Murphy,et al. Machine learning - a probabilistic perspective , 2012, Adaptive computation and machine learning series.
[57] D. Sejdinovic,et al. Detecting causal associations in large nonlinear time series datasets , 2018 .
[58] D. R. Cutler,et al. Utah State University From the SelectedWorks of , 2017 .