Publications

Google Scholar

2022

  • M. S³oñski:

2021

  • M. S³oñski:

2020

  • M. S³oñski:

2019

  • M. S³oñski:

2019

  • M. S³oñski:

2018

2017

2016

2015

2014

  • M. S³oñski: Bayesian machine learning in analysis of selected identification problems of mechanics of materials and structures. Publishing House of Cracow University of Technology, monograph no. 473, Civil Engineering series, ISSN 0860-097X, 2014.
  • M. S³oñski: Sequential stochastic identification of elastic constants using Lamb waves and particle filters. Computer Assisted Meth. Eng. Sci., (21) 1: pp. 15-26, 2014 CAMES.
  • M. Tekieli, M. S³oñski: Particle filtering for computer vision-based identification of frame model parameters. Computer Assisted Meth. Eng. Sci., (21) 1: pp. 39-48, 2014 CAMES.

2013

2012

  • M. S³oñski: Gaussian mixture model for time-series based structural damage identification, Computer Assisted Meth. Eng. Sci., (19) 4: pp. 331-338, 2012 CAMES
  • M. S³oñski: Gaussian mixture model and Bayesian methods in time series-based structural damage detection, ECCOMAS 2012 Congress, Vienna, Austria, September 10-14, 2012
  • M. Tekieli, M. S³oñski: DriastSystem: a computer vision based system for real time traffic sign detection and recognition. In Artificial Intelligence and Soft Computing. Springer Berlin Heidelberg, pp. 608-616, 2012.

2011

  • M. S³oñski: Bayesian neural networks and Gaussian processes in identification of concrete properties, Computer Assisted Mech. Eng. Sci., (18) 4: pp. 291-302, 2011 CAMES
  • M. S³oñski: Bayesian neural networks in mechanics of structures and materials, 57th Scientific Conference of the Committee on Civil Engineering and Hydroengineering of the Polish Academy of Sciences, 18-22.09.2011, Rzeszow-Krynica, Poland.
  • M. S³oñski: Bayesian neural networks for HPC compressive strength prediction, 7th International Conference on Analytical Models and New Concepts in Concrete and Masonry Structures, 13-15 June 2011, Cracow, Poland.
  • M. S³oñski: Time series based structural damage localization with Gaussian mixture models, 19th International Conference on Computer Methods in Mechanics, CMM-2011, 09-12 May 2011, Warsaw, Poland.
  • M. S³oñski: Gaussian mixture model for time-series based structural damage detection, In: Proceedings of the 2nd ECCOMAS International Symposium on Inverse Problems in Mechanics of Structures and Materials (IPM 2011), Rzeszów-Sieniawa, Poland, 27-30 April 2011. Book of abstracts. Ed. by Z. Waszczyszyn and L. Ziemiañski. Rzeszów University of Technology. Department of Structural Mechanics. Faculty of Civil and Environmental Engineering. Rzeszów: Publishing House of Rzeszów University of Technology, 2011, pp.95-96.

2010

  • M. S³oñski: A comparison of model selection methods for compressive strength prediction of high-performance concrete using neural networks, Computers and Structures, 88 (2010), pp. 1248-1253. Full paper
  • M. S³oñski: Structure damage localization based on the relevance vector machine, IV European Conference on Computational Mechanics, ECCM-2010, Paris, France, 2010.
  • Z. Waszczyszyn, M. S³oñski: Selected problems of Artificial Neural Networks Development, book chapter in Advances of Soft Computing in Engineering, CISM International Centre for Mechanical Sciences, Courses and Lectures series, n. 512, Springer WienNewYork, 2010.

2009

2008

  • Z. Waszczyszyn, M. S³oñski, B. Miller and G. Pi±tkowski: Bayesian Neural Networks in the regression analysis of structural mechanics problems, 8th. World Congress on Computational Mechanics and 5th. European Congress on Computational Methods in Applied Sciences and Engineering, 30 June - 4 July 2008, Venice, Italy.
  • Z. Waszczyszyn, M. S³oñski: Maximum of Marginal Likelihood criterion instead of cross-validation for designing of Artificial Neural Networks, The Eighth International Conference on Artificial Intelligence and Soft Computing, June 22-26, 2008, Zakopane.

2007

  • Z. Waszczyszyn and M. S³oñski: Criterion of Maximum Marginal Likelihood instead of Cross-Validation for Design of Artificial Neural Networks (in Polish), Folia Scientiarum Universitatis Technicae Resoviensis, 243, 2007, pp. 173-185,
  • M. S³oñski: HPC strength prediction using Bayesian neural networks , Computer Assisted Mech. Eng. Sci., 14: 2007, No. 2, pp. 345-352. Abstract
  • M. S³oñski: Robust prediction of mechanical properties of HPC with Bayesian neural networks, 17th International Conference on Computer Methods in Mechanics, CMM-2007, £ód¼-Spa³a, 2007.
  • Z. Waszczyszyn and M. S³oñski: From deterministic to Bayesian neural networks: Some applications in structural mechanics, 17th International Conference on Computer Methods in Mechanics, CMM-2007, £ód¼-Spa³a, 2007.
  • Z. Waszczyszyn and M. S³oñski: Simulation of displacement response spectra using Bayesian neural networks, 17th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering, COMPDYN-2007, Crete, 2007.
  • Z. Waszczyszyn and M. S³oñski: From deterministic to Bayesian neural networks: Some applications in structural mechanics, 13th Inter-Institute Seminar for Young Researchers, Vienna, May 16-18, 2007
  • M. S³oñski: A Bayesian approach for the estimation of model parameters, 13th Inter-Institute Seminar for Young Researchers, Vienna, May 16-18, 2007

2006

  • M. S³oñski: Bayesian regression approaches on example of concrete fatigue failure prediction, Computer Assisted Mech. Eng. Sci., 13: 2006, No. 4, pp. 655-668. Abstract
  • Z. Waszczyszyn and M. S³oñski: Bayesian neural networks for prediction of response spectra, Foundations of Civil and Environmental Eng., 7, 2006, pp. 343-361, Abstract

2005

  • M. S³oñski: Prediction of concrete fatigue durability using Bayesian neural networks, Computer Assisted Mech. Eng. Sci., 12: 2005, Nos 2/3, pp. 259-265. Abstract
  • M. S³oñski: Concrete fatigue durability prediction with Gaussian processes and Bayesian neural networks, 16th International Conference on Computer Methods in Mechanics, CMM-2005, Czêstochowa, 2005.
  • M. S³oñski: HPC strength prediction using Bayesian neural networks, Proc. Symposium on Neural Networks and Soft Computing in Structural Engineering, NNSC-2005, Eds. Z. Waszczyszyn, M. S³oñski, Cracow, 2005.

2004

  • M. S³oñski: Prediction of concrete fatigue durability using Bayesian neural networks, Proc. Symposium on Methods of Artificial Intelligence, AI-METH 2004, Eds. T. Burczyñski, W. Cholewa, W. Moczulski, Gliwice, 2004. Full paper
  • M. S³oñski: Application of Bayesian neural networks to identification of concrete fatigue durability (in Polish), Symposium on Application of Artificial Neural Networks in Civil Engineering, Zielona Góra, 2004.

pre-2004

  • J. Szczêsny and M. S³oñski: Application of artificial neural networks to permeability assessment of dams foundation (in Polish), 10th International Conference on Dam Monitoring , Ed. M. Maciejewski, Kielce, 2003.
  • M. S³oñski and Z. Waszczyszyn: Neural prediction of water absorption in the sealing process of a dam grout curtain, Proc. Symposium on Methods of Artificial Intelligence, AI-METH 2002, Eds. T. Burczyñski, W. Cholewa, W. Moczulski, Gliwice, 2002, pp. 389-394. Abstract   Full paper
  • M. S³oñski: Application of ANFIS neuro-fuzzy system for prediction of concrete fatigue durability, 13th Inter-Institute Seminar for Young Researchers, Vienna, October 26-28, 2001 Abstract
  • M. S³oñski: Application of fuzzy modelling in planning of small water reservoirs systems in highland catchments. PhD thesis, CUT, Cracow, 2001. (in Polish).
  • Z. Waszczyszyn and M. S³oñski: Analysis of some problems of experimental mechanics and biomechanics by means the ANFIS neuro-fuzzy system, J. Theoretical Appl. Mech., 2, 38, 2000, pp. 429-445.
  • Z. Waszczyszyn and M. S³oñski: Analysis of some problems of experimental mechanics by ANFIS, 12th Inter-Institute Seminar on Nonlinear Computational Mechanics, Budapest, October 27-29, 2000,
  • Z. Waszczyszyn, K. Ku¼niar, R. Obia³a, M. S³oñski: Some new results and prospects of neural analysis of building vibration problem, Proc. 5th Intern. Conf. on Engineering Applications of Neural Networks, Ed. W. Duch, Warsaw, 1999, pp. 265-272. Full paper
  • Z. Waszczyszyn and M. S³oñski: Comparison of neuro-fuzzy systems and neural networks in some problems of mechanics of structures and materials, 11th Inter-Institute Seminar on Youth and Computational Mechanics, PHSEMINAR '99, Janowice, October 7-10, 1999
  • L. Mikulski and M.S³oñski: Warp and optimization of the thin-wall beams with a variable cross-section, Technical Transactions, Cracow University of Technology Publishing House, Series Civil Engineering, 4-B, 1997, pp.41-57, (in Polish)