Chaos Theory Approach as Advanced Technique for GDI Spray Analysis

[1]  A. Montanaro,et al.  Flash Boiling Evidences of a Multi-Hole GDI Spray under Engine Conditions by Mie-Scattering Measurements , 2015 .

[2]  Teuvo Kohonen,et al.  Developments and applications of the self-organizing map and related algorithms , 1996 .

[3]  Kurt Hornik,et al.  FEED FORWARD NETWORKS ARE UNIVERSAL APPROXIMATORS , 1989 .

[4]  João Manuel R. S. Tavares,et al.  Evaluation of multilayer perceptron and self-organizing map neural network topologies applied on microstructure segmentation from metallographic images , 2009 .

[5]  BERNARD CAZELLES,et al.  How predictable is chaos? , 1992, Nature.

[6]  Gregory L. Baker,et al.  Chaotic Dynamics: An Introduction , 1990 .

[7]  A. Montanaro,et al.  Spray Characterization of a Single-Hole Gasoline Injector under Flash Boiling Conditions , 2014 .

[8]  G. Langella,et al.  Characterization of gas turbine burner instabilities by wavelet analysis of infrared images , 2016 .

[9]  G. Langella,et al.  A Statistical Method to Identify the Main Parameters Characterizing a Pressure Swirl Spray , 2013 .

[10]  Georg A. Gottwald,et al.  A new test for chaos in deterministic systems , 2004, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[11]  Subanatarajan Subbiah,et al.  An Intuitive Diagnostic Model for Gas Analyzers based on Self Organizing Maps , 2015 .

[12]  Dong-Kyun Kim,et al.  Assessment of the lake biomanipulation mediated by piscivorous rainbow trout and herbivorous daphnids using a self-organizing map: A case study in Lake Shirakaba, Japan , 2015, Ecol. Informatics.

[13]  T. Deliyannis,et al.  Means for detecting chaos and hyperchaos in nonlinear electronic circuits , 2002, 2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628).

[14]  Luigi Allocca,et al.  MODELLING OF PRIMARY BREAKUP PROCESS OF A GASOLINE DIRECT ENGINE MULTI-HOLE SPRAY , 2013 .

[15]  Sawada,et al.  Measurement of the Lyapunov spectrum from a chaotic time series. , 1985, Physical review letters.

[16]  Mario I. Chacon-Murguia,et al.  Fuzzy-neural self-adapting background modeling with automatic motion analysis for dynamic object detection , 2015 .

[17]  Lalit M. Patnaik,et al.  Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network , 2006, Biomed. Signal Process. Control..

[18]  Mauricio Barahona,et al.  Detection of nonlinear dynamics in short, noisy time series , 1996, Nature.

[19]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[20]  Caibin Zeng,et al.  Chaos detection and parameter identification in fractional-order chaotic systems with delay , 2013 .

[21]  Georg A. Gottwald,et al.  Testing for Chaos in Deterministic Systems with Noise , 2005 .

[22]  Otilia Elena Dragomir,et al.  Matlab Application of Kohonen Self-organizing Map to Classify Consumers' Load Profiles , 2014, ITQM.

[23]  G. Langella,et al.  Advanced Image Analysis of Two-Phase Flow inside a Centrifugal Pump , 2014 .

[24]  Luigi Allocca,et al.  Fuzzy Logic Approach to GDI Spray Characterization , 2016 .

[25]  Soteris A. Kalogirou,et al.  Artificial intelligence for the modeling and control of combustion processes: a review , 2003 .

[26]  Ken-ichi Funahashi,et al.  On the approximate realization of continuous mappings by neural networks , 1989, Neural Networks.

[27]  Matthew Nicol,et al.  Statistical properties of endomorphisms and compact group extensions , 2004 .

[28]  Eckmann,et al.  Liapunov exponents from time series. , 1986, Physical review. A, General physics.

[29]  Carlos Dafonte,et al.  Mixing numerical and categorical data in a Self-Organizing Map by means of frequency neurons , 2015, Appl. Soft Comput..