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Predicting defibrillation success by "genetic" programming in patients with out-of-hospital cardiac arrest
Matej Podbregar, Miha Kovačič, Aleksandra Podbregar-Marš, Miran Brezočnik, 2003, izvirni znanstveni članek

Opis: In some patients with ventricular fibrillation (VF) there may be a better chance of successful defibrillation after a period of chest compression and ventilation before the defibrillation attempt. It is therefore important to know whether a defibrillation attempt will be successful. The predictive powerof a model developed by "genetic" programming (GP) to predict defibrillation success was studied. Methods and Results: 203 defibrillations were administered in 47 patients with out-of-hospital cardiac arrest due to a cardiac cause. Maximal amplitude, a total energy of power spectral density, and the Hurst exponent of the VF electrocardiogram (ECG) signal were included in the model developed by GP. Positive and negative likelihood ratios of the model for testing data were 35.5 and 0.00, respectively. Using a model developed by GP on the complete database, 120 of the 124 unsuccessful defibrillations would have been avoided, whereas all of the 79 successful defibrillations would have been administered. Conclusion: The VF ECG contains information predictive of defibrillation success. The model developed by GP, including data from the time-domain, frequency-domain and nonlinear dynamics, could reduce the incidence of unsuccessful defibrillations.
Ključne besede: optimisation methods, evolutionary optimisation methods, genetic algorithms, genetic programming, defibrillation, cardiac arrest prediction
Objavljeno v DKUM: 01.06.2012; Ogledov: 1846; Prenosov: 95
URL Povezava na celotno besedilo

A model of data flow in lower CIM levels
Igor Drstvenšek, Ivo Pahole, Jože Balič, 2004, izvirni znanstveni članek

Opis: After years of work in fields of computer-integrated manufacturing (CIM), flexible manufacturing systems (FMS), and evolutionary optimisation techniques, several models of production automation were developed in our laboratories. The last model pools the discoveries that proved their effectiveness in the past models. It is based on the idea of five levels CIM hierarchy where the technological database (TDB) represents a backbone of the system. Further on the idea of work operation determination by an analyse of the production system is taken out of a model for FMS control system, and finally the approach to the optimisation of production is supported by the results of evolutionary based techniques such as genetic algorithms and genetic programming.
Ključne besede: computer integrated manufacturing, flexible manufacturing systems, evolutionary optimisation techniques, production automation, CIM hierarchy, technological databases, production optimisation, genetic algorithms, genetic programming
Objavljeno v DKUM: 01.06.2012; Ogledov: 2087; Prenosov: 101
URL Povezava na celotno besedilo

Prediction of surface roughness with genetic programming
Miran Brezočnik, Miha Kovačič, Mirko Ficko, 2004, izvirni znanstveni članek

Opis: In this paper we propose genetic programming to predict surface roughness in end-milling. Two independent data sets were obtained on the basis of measurement: training data set and testing data set. Spindle speed, feed rate,depth of cut, and vibrations are used as independent input variables (parameters), while surface roughness as dependent output variable. On the basis of training data set, different models for surface roughness were developed by genetic programming. Accuracy of the best model was proved with the testing data. It was established that the surface roughness is most influenced by the feed rate, whereas the vibrations increase the prediction accuracy.
Ključne besede: end milling, surface roughness, prediction of surface roughness, genetic programming
Objavljeno v DKUM: 01.06.2012; Ogledov: 1948; Prenosov: 129
URL Povezava na celotno besedilo

A strategy for MINLP synthesis of flexible and operable processes
Zorka Novak-Pintarič, Zdravko Kravanja, 2004, izvirni znanstveni članek

Opis: Abstract This paper presents a sequential two-stage strategy for the stochastic synthesis of chemical processes in which flexibility and static operability (the ability to adjust manipulated variables) are taken into account. In the first stage, the optimal flexible structure and optimal oversizing of the process units are determined in order to assure feasibility of design for a fixed degree of flexibility. In the second stage, the structural alternatives and additional manipulative variables are included in the mathematical model in order to introduce additional degrees of freedom for efficient control. The expected value of the objective function is approximated in both stages by a novel method, which relies on optimization at the central basic point (CBP). The latter is determined by a simple set-up procedure based on calculations of the objective functionćs conditional expectations for uncertain parameters. The feasibility is assured by simultaneous consideration of critical vertices. The important feature of the proposed stochastic model is that its size depends mainly on the number of design variables and not on the number of uncertain parameters. The strategy is illustrated by two examples for heat exchanger network synthesis.
Ključne besede: chemical processing, process synthesis, MINLP, mixed integer nonlinear programming, flexibility, operability, controllability, steady state model
Objavljeno v DKUM: 01.06.2012; Ogledov: 2418; Prenosov: 95
URL Povezava na celotno besedilo

Evolutionary approach for cutting forces prediction in milling
Miha Kovačič, Jože Balič, Miran Brezočnik, 2004, izvirni znanstveni članek

Opis: Knowing cutting forces is important for choosing cutting parameters for milling. Traditionally, cutting forces are calculated by equation which includes empirically measured specific cutting forces. In the article modelling of cutting forces with genetic programming is proposed, which imitates principles of living beings. Measurements have been made for two materials (aluminium alloy AlMgSi1 and steel 1.2343) and two different types of milling (conventional milling and STEP milling). For each material and type of milling parameters, tensile strength and hardness of workpiece, tool diameter, cutting depth, spindle speed, feeding and type of milling were monitored, and for each combination of milling parameters cutting forces were measured. On the basis of the experimental data, different models for cutting forces prediction were obtained by genetic programming. Research shows that genetically developed models fit the experimental data.
Ključne besede: milling, simulation, milling cutting forces prediction, genetic programming
Objavljeno v DKUM: 01.06.2012; Ogledov: 1413; Prenosov: 78
URL Povezava na celotno besedilo

Predicting stress distribution in cold-formed material with genetic programming
Miran Brezočnik, Leo Gusel, 2004, izvirni znanstveni članek

Opis: In this paper we propose a genetic programming approach to predict radial stress distribution in cold-formed material. As an example, cylindrical specimens of copper alloy were forward extruded and analysed by the visioplasticity method. They were extruded with different coefficients of friction. The values of three independent variables (i.e., radial and axial position of measured stress node, and coefficient of friction) were collected after each extrusion. These variables influence the value of the dependent variable, i.e., radial stress. On the basis of training data set, various different prediction models for radial stress distribution were developed during simulated evolution. Accuracy of the best models was proved with the testing data set. The research showed that by proposed approach the precise prediction models can be developed; therefore, it is widely used also in other areas in metal-forming industry, where the experimental data on the process are known.
Ključne besede: metal forming, stress distribution, prediction, genetic programming, modelling
Objavljeno v DKUM: 01.06.2012; Ogledov: 2086; Prenosov: 95
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An integrated strategy for the hierarchical multilevel MINLP synthesis of overall process flowsheets using the combined synthesis/analysis approach
Nataša Iršič Bedenik, Bojan Pahor, Zdravko Kravanja, 2004, izvirni znanstveni članek

Opis: This paper describes an integrated strategy for a hierarchical multilevel mixed-integer nonlinear programming (MINLP) synthesis of overall process schemes using a combined synthesis/analysis approach. The synthesis is carried out by multilevel-hierarchical MINLP optimization of the flexible superstructure, whilst the analysis is performed in the economic attainable region (EAR). The role of the MINLP synthesis step is to obtain a feasible and optimal solution of the multi-D process problem, and the role of the subsequent EAR analysis step is to verify the MINLP solution and in the feedback loop to propose any profitable superstructure modifications for the next MINLP. The main objective of the integrated synthesis is to exploit the interactions between the reactor network, separator network and the remaining part of the heat/energy integrated process scheme.
Ključne besede: multilevel MINLP, MINLP synthesis, attainable region, economic attainable region, concentration attainable region, continous stirred tank reactor, plug flow reactor, recycle reactor, nonlinear programming, mixed integer nonlinear programme
Objavljeno v DKUM: 01.06.2012; Ogledov: 2635; Prenosov: 106
URL Povezava na celotno besedilo

Optimisation of tree path pipe network with nonlinear optimisation method
Danijela Urbancl, Darko Goričanec, 2009, izvirni znanstveni članek

Opis: In this paper, the optimisation of pipe network with hot water is presented. The mathematical model, consisting of the nonlinear objective function and system of nonlinear equations for the hydraulics limitations is developed. On its basis, the computer program for determination optimal tree path with the use of simplex method was solved. For economic estimation the capitalised value method, which consider all costs of investment and operation was used. The results are presented for real case study network with 24 nodes and 33 pipe sectors.
Ključne besede: district heating, pipe network, optimisation, non-linear programming, simplex method
Objavljeno v DKUM: 01.06.2012; Ogledov: 2275; Prenosov: 99
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Genetic programming approach for the material flow curve determination of copper alloy - CuCrZr
Leo Gusel, Miran Brezočnik, Rebeka Rudolf, Ivan Anžel, Z. Lazarević, Nebojša Romčević, 2010, izvirni znanstveni članek

Opis: For the control of the forming process it is necessary to know as precisely as possible the flow curve of the formed material. The paper presents the determination of the equation for the flow curve of cooper alloy (CuCrZr) with artificial intelligence approach. The genetic programming method (GP) was used. It is an evolutionary optimization technique based on the Darwinist principles of the evolution of species and the survival of the fittest organisms. The main characteristic of GP is its non- deterministic way of computing. It is probably the most general approach out of evolutionary computation methods. The comparison between the experimental results, analytical solution and the solution obtained genetically clearly shows that the genetic programming method is a very promising approach.
Ključne besede: forming, flow curve, copper alloys, genetic programming
Objavljeno v DKUM: 01.06.2012; Ogledov: 1546; Prenosov: 30
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