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1
Content available remote Data filtering using dynamic particles method
100%
Rauch Ł. , Kusiak J.
Computer Assisted Mechanics and Engineering Sciences
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2007
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tom Vol. 14, No. 2
353-360
EN
The identification of the industrial processes is a complex problem, especially in the case of signals denoising. The holistic approaches used for signal denoising processes are recently considered in various types of applications in the domain of experimental simulations, feature extraction and identification. A new signal filtering method based on the dynamic particles (DP) approach is presented. It employs physics principles for the signal smoothing. The presented method was validated in the identification of two kinds of input data sets: artificially generated data according to a given function y = f (X) and the data obtained in laboratory mechanical tests of metals. The algorithm of the DP method and the results of calculations are presented. The obtained results were compared with commonly used denoising techniques including weighted average, neural networks and wavelet analysis. Moreover the assessment of the results' quality is introduced.
2
Content available remote Application of soft computing in uncertainty analysis
100%
Martowicz A. , Pieczara J. , Uhl T.
Computer Assisted Mechanics and Engineering Sciences
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2007
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tom Vol. 14, No. 2
293-305
EN
The paper deals with the application of soft computing used in uncertainty analysis in the field of structural dynamics. Employing Genetic Algorithms, fuzzy sets theory as well as interval algebra authors show quite useful extension of well known approaches of solving eigenproblems considering assumed model uncertainties. During performed calculation, ranges of the first natural frequency of a simple FE model are found and then compared to those ones obtained with Monte Carlo simulation. As input uncertain parameters some of material properties are taken into account. The main objective of the work is to highlight possible advantages of the application in terms of reducing computation time meant for uncertainty analyses.
3
Content available remote An example of application of soft computing in experimental modal analysis
100%
Lisowski W. , Góral G. , Uhl T.
Computer Assisted Mechanics and Engineering Sciences
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2007
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tom Vol. 14, No. 2
277-292
EN
The paper deals with application of AI tools in experimental modal analysis. The example of Stabilization Diagram processing, that is an intermediate stage of modal parameter estimation procedure, was selected. In order to automate decision-making carried out during Stabilization Diagram processing a set of tools employing: fuzzy reasoning and artificial neural nets was applied. The application of these tools enabled to ease and shorten execution time of Stabilization Diagram processing. Additionally, the result of processing has become operator-independent.
4
Content available Predicting buildings construction cost overruns on the basis of cost overruns structure
86%
Car-Pusic D. , Tijanic K. , Marovic I. , Mladen M.
Przegląd Naukowy. Inżynieria i Kształtowanie Środowiska
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2020
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tom 29
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nr 3[89]
5
Content available remote Back analysis of microplane model parameters using soft computing methods
86%
Kučerová A. , Lepš M. , Zeman J.
Computer Assisted Mechanics and Engineering Sciences
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2007
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tom Vol. 14, No. 2
219-242
EN
A new procedure based on layered feed-forward neural networks for the microplane material model parameters identification is proposed in the present paper. Novelties are usage of the Latin Hypercube Sampling method for the generation of training sets, a systematic employment of stochastic sensitivity analysis and a genetic algorithm-based training of a neural network by an evolutionary algorithm. Advantages and disadvantages of this approach together with possible extensions are thoroughly discussed and analyzed.
6
Content available Predicting buildings construction cost overruns on the basis of cost overruns structure
86%
Car-Pušić D. , Tijanić K. , Marović I. , Mlađen M.
Przegląd Naukowy Inżynieria i Kształtowanie Środowiska
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2020
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tom Vol. 29, No. 3
366--376
EN
In construction practice, contractually agreed costs are often exceeded, which interferes with the sustainable realization of construction projects. The research described in this paper covers 24 new construction, renovation and reconstruction projects in the Republic of Croatia realized in the years 2006 to 2017, in order to analyse the occurrence of cost overruns more precisely with regard to the source of the overruns. It was found that additional work is the main source of cost overruns: firstly, additional work as a result of the client’s change orders and then unforeseen construction work as a result of unforeseen circumstances. As for the additional works, they are carried out at the client’s request and are not necessary for the safety and stability of the building. Using linear regression and “soft computing” methods, the possibility of modelling the relationship between contractually agreed and realized construction costs with satisfactory accuracy was tested. The model with the values of the natural logarithms of the variables, modelled according to the time–cost model of Bromilow, proved to be of the highest accuracy.
7
Metodyka heurystycznego modelowania obiektów i procesów dynamicznych w diagnostyce i sterowaniu
72%
Moczulski W.
Pomiary Automatyka Kontrola
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2005
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tom R. 51, nr 9 bis
39--41
PL
W referacie opisano grupę metod heurystycznego modelowania obiektów i procesów dynamicznych, rozwijanych w zespole autora Wynikowe modele planuje się zastosować do diagnostyki obiektów i procesów wspartej modelowo. Oprócz znanych metod modelowania miękkiego, jak zastosowanie sieci neuronowych i neuronowo-rozmytych, rozwijane są oryginalne metody reprezentacji procesów o atrybutach ciągłych oraz dyskretnych, które stosowane są w diagnostyce opartej na przypadkach. Szczególnym problemem jest w tym wypadku określenie odpowiedniej miary analogii (podobieństwa) przypadków. Do najbardziej zaawansowanych należy metoda projekcji i selekcji atrybutów z wykorzystaniem projekcji przestrzeni atrybutów w wielowymiarową przestrzeń regresorów, oraz selekcji z zastosowaniem algorytmu SVM i algorytmu genetycznego. Referat kończą bardzo skrótowe opisy zastosowań wybranych metod do modelowania dwóch różnych procesów, z których pierwszy dotyczy diagnostyki procesu produkcyjnego, a drugi - oceny stanu eksploatacyjnego maszyny.
EN
The paper deals with brief description of a group of methods of heuristic modeling dynamic objects and processes, whose methods are developed in the author's research group. Resulting models are to be applied for model-based diagnostics of objects and processes. Apart from known methods of soft modeling such as ANN and KNN, original methods of representation of processes whose attributes arc both continuous and discrete ones are developed, providing the opportunity to employ CBR approach. In this case definition of respective measure of analogy (similarity) of cases is very crucial. The most advanced method involves projection and selection of attributes with the use of projection of the space of attributes into multidimensional space of rcgressors, and selection with the application of SVM and genetic algorithms. Two distinct applications of the methods are also briefly discussed. The first deals with diagnostics of an industrial process, while the other is targeted to diagnostics of operational state of a machine.
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