Hybrid artificial immune system in identification of room acoustic properties

The paper deals with an application of a hybrid artificial immune system (HAIS) to the identification problems. The HAIS is applied to identify complex impedances of room walls. This approach is based on the mechanism discovered in biological immune systems. The numerical example demonstrates that the method based on immune computation is an effective technique for solving computer aided in identification problem.

[1]  Sunan Wang,et al.  A novel immune evolutionary algorithm incorporating chaos optimization , 2006, Pattern Recognit. Lett..

[2]  Tadeusz Burczynski,et al.  Sequential and Distributed Evolutionary Computations in Structural Optimization , 2004, ICAISC.

[3]  Stephanie Forrest,et al.  Coverage and Generalization in an Artificial Immune System , 2002, GECCO.

[4]  Tadeusz Burczyński,et al.  Immune Computing: Intelligent Methodology and Its Applications in Bioengineering and Computational Mechanics , 2010 .

[5]  Eugeniusz Zieniuk,et al.  Genetic Algorithms Based on a New System of Integral Equations in Identification of Material Constants for Anisotropic Media , 2001 .

[6]  F. Rochinha,et al.  A genetic algorithm applied to composite elastic parameters identification , 2004 .

[7]  Dariusz Mrozek,et al.  An Improved Method for Protein Similarity Searching by Alignment of Fuzzy Energy Signatures , 2011, Int. J. Comput. Intell. Syst..

[8]  Abdullah Al Mamun,et al.  An evolutionary artificial immune system for multi-objective optimization , 2008, Eur. J. Oper. Res..

[9]  Wilkins Aquino,et al.  Surrogate-Model Accelerated Random Search algorithm for global optimization with applications to inverse material identification , 2007 .

[10]  Tadeusz Burczyński,et al.  Topological evolutionary computing in the optimal design of 2D and 3D structures , 2007 .

[11]  Graeme Fairweather,et al.  The method of fundamental solutions for scattering and radiation problems , 2003 .

[12]  Wacław Kuś,et al.  Immune identification of piezoelectric material constants using BEM , 2011 .

[13]  Du Xiuli,et al.  STRUCTURAL PHYSICAL PARAMETER IDENTIFICATION BASED ON EVOLUTIONARY-SIMPLEX ALGORITHM AND STRUCTURAL DYNAMIC RESPONSE , 2003 .

[14]  Kevin Warwick,et al.  Genetic least squares for system identification , 1999, Soft Comput..

[15]  Rafael Gallego,et al.  Combining topological sensitivity and genetic algorithms for identification inverse problems in anisotropic materials , 2007 .

[16]  Jonathan Timmis,et al.  Artificial immune systems as a novel soft computing paradigm , 2003, Soft Comput..

[17]  Jorge Nocedal,et al.  On the limited memory BFGS method for large scale optimization , 1989, Math. Program..

[18]  P. Manach,et al.  Material parameters identification: Gradient-based, genetic and hybrid optimization algorithms , 2008 .

[19]  Simon N. Chandler-Wilde,et al.  Boundary element methods for acoustics , 2007 .

[20]  Wang Sun-an,et al.  A novel immune evolutionary algorithm incorporating chaos optimization , 2006 .

[21]  Franck Sgard,et al.  Low‐frequency assessment of the in situ acoustic absorption of materials in rooms: an inverse problem approach using evolutionary optimization , 2002 .

[22]  Alina Momot,et al.  Improving Performance of Protein Structure Similarity Searching by Distributing Computations in Hierarchical Multi-Agent System , 2010, ICCCI.

[23]  Abdul Ahad,et al.  Basics of Immunology , 2011 .

[24]  Tadeusz Burczyński,et al.  Genetic generation of 2D and 3D structures , 2003 .

[25]  Rong-Song He,et al.  Identification of effective elastic constants of composite plates based on a hybrid genetic algorithm , 2009 .