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1.
Design of row-based flexible manufacturing system with evolutionary computation
Mirko Ficko, Jože Balič, 2008, objavljeni znanstveni prispevek na konferenci

Opis: This paper discusses design of flexible manufacturing systems (FMSs) in one or multiple rows. Evolutionary computation, particularly genetic algorithms (GAs) proved to be successful in search of optimal solution for this type of problems. The model of solution, the most suitable way of coding the solutions into the organisms and the selected evolutionary and genetic operators are presented. In this connection, the most favourable number of rows and the sequence of devices in the individual row are established by means of genetic algorithms (GAs). In the end the test results of the application made and the analysis are discussed.
Ključne besede: flexible manufacturing system design, genetic algorithms, evolutionary computation, intelligent manufacturing systems, artificial intelligence
Objavljeno: 31.05.2012; Ogledov: 1074; Prenosov: 53
URL Povezava na celotno besedilo

2.
Genetic equation for the cutting force in ball-end milling
Matjaž Milfelner, Janez Kopač, Franc Čuš, Uroš Župerl, 2005, izvirni znanstveni članek

Opis: The paper presents the development of the genetic equation for the cutting force for ball-end milling process. The development of the equation combines different methods and technologies like evolutionary methods, manufacturing technology, measuring and control technology and intelligent process technology with the adequate hardware and software support. Ball-end milling is a very common machining process in modern manufacturing processes. The cutting forces play the important role for the selection of the optimal cutting parameters in ball-end milling. In many cases the cutting forces in ball-end milling are calculated by equation from the analytical cutting force model. In the paper the genetic equation for the cutting forces in ball-end milling is developed with the use of the measured cutting forces and genetic programming. The experiments were made with the system for the cutting force monitoring in ball-end milling process. The obtained results show that the developed genetic equation fits very well with the experimental data. The developed genetic equation can be used for the cutting force estimation and optimization of cutting parameters. The integration of the proposed method will lead to the reduction in production costs and production time, flexibility in machining parameter selection, and improvement of product quality.
Ključne besede: milling, ball-end mill, optimization, cutting forces, cutting parameters, genetic algorithms
Objavljeno: 01.06.2012; Ogledov: 1128; Prenosov: 61
URL Povezava na celotno besedilo

3.
Prediction of maintenance of sinus rhythm after electrical cardioversion of atrial fibrillation by non-deterministic modelling
Petra Žohar, Miha Kovačič, Miran Brezočnik, Matej Podbregar, 2005, izvirni znanstveni članek

Opis: Atrial fibrillation (AF) is the most common rhythm disorder. Because of the high recurrence rate of AF after cardioversion and because of potential side effects of electrical cardioversion, it is clinically important to predict persistence of sinus rhythm after electrical cardioversion before it is attempted. The aim of our study was the development of a mathematical model by"genetic" programming (GP), a non-deterministic modelling technique, which would predict maintenance of sinus rhythm after electrical cardioversion of persistent AF. PATIENTS AND METHODS: Ninety-seven patients with persistent AF lasting more than 48 h, undergoing the first attempt at transthoracic cardioversion were included in this prospective study. Persistence of AF before the cardioversion attempt, amiodarone treatment, left atrial dimension,mean, standard deviation and approximate entropy of ECG R-R intervals were collected. The data of 53 patients were randomly selected from the database and used for GP modelling; the other 44 data sets were used for model testing. RESULTS: In 23 patients sinus rhythm persisted at 3 months. In the other 21 patients sinus rhythm was not achieved or its duration was less than 3 months. The model developed by GP failed to predict maintenance ofsinus rhythm at 3 months in one patient and in six patients falsely predicted maintenance of sinus rhythm. Positive and negative likelihood ratiosof the model for testing data were 4.32 and 0.05, respectively. Using this model 15 of 21 (71.4%) cardioversions not resulting in sinus rhythm at 3 months would have been avoided, whereas 22 of 23 (95.6%) cardioversions resulting in sinus rhythm at 3 months would have been administered. CONCLUSION: This model developed by GP, including clinical data, ECG data from the time-domain and nonlinear dynamics can predict maintenance of sinus rhythm. Further research is needed to explore its utility in the present or anexpanded form.
Ključne besede: optimisation methods, evolutionary optimisation methods, genetic algorithms, genetic programming, defibrillation, cardiac arrest prediction, atrial fibrillation, electrical cardioversion, prediction
Objavljeno: 01.06.2012; Ogledov: 1188; Prenosov: 36
URL Povezava na celotno besedilo

4.
Evolutionary programming of CNC machines
Miha Kovačič, Miran Brezočnik, Ivo Pahole, Jože Balič, Borut Kecelj, 2005, izvirni znanstveni članek

Opis: The paper proposes a new concept for programming of CNC machines. The concept based on genetic algorithms assures evolutionary generation and optimization of NC programs on the basis of CAD models of manufacturing environment. The structure, undergoing simulated evolution, is the population of NC programs. The NC programs control the machine which performs simple elementary motions. During the evolution the machine movement becomes more and more complex and intelligent solutions emerge gradually as a result of the interaction between machine movements and manufacturing environment. The examples of evolutionary programming of CNC lathe and CNC milling machine tool for different complexities of the blanks and products are presented. The proposed concept showed a high degree of universality, efficiency, and reliability and it can be also simply adopted to other CNC machines.
Ključne besede: manufacturing systems, NC-programming, CNC lathes, simulated evolution, genetic algorithms
Objavljeno: 01.06.2012; Ogledov: 898; Prenosov: 57
URL Povezava na celotno besedilo

5.
A model of simulation environment for prediction and optimisation of production processes
Igor Drstvenšek, Mirko Ficko, Ivo Pahole, Jože Balič, 2004, izvirni znanstveni članek

Opis: Paper describes means and methods for computer based optimisation of production processes using a new approach based on technological database (TDB) with genetic algorithm incorporated into a database management system (DBMS). The TDB serves as a store of tools and machine tools from which they can be assigned to different work operations. Work operations are basic entities of orders placed into queues. The goal of the model is to find available resources from the TDB in order to empty the queue in shortest time with lowest costs. To this purpose the model consist the technological database whose DBMS includes a genetic algorithm based optimiser. It checks the orders queue and searches for appropriate combinations of tools and machine tools from the TDB, which can be combined into needed work operations. It also performs an optimisation of time and costs according to so called static parameters of tools and machine tools.
Ključne besede: production processes, simulation, process planning, technological databases, genetic algorithms
Objavljeno: 01.06.2012; Ogledov: 1024; Prenosov: 53
URL Povezava na celotno besedilo

6.
Designing the layout of single- and multiple-rows flexible manufacturing system by genetic algorithms
Mirko Ficko, Miran Brezočnik, Jože Balič, 2004, izvirni znanstveni članek

Opis: The paper presents a model of designing of the flexible manufacturing system (FMS) in one or multiple rows with genetic algorithms (GAs). First the reasons for studying the layout of devices in the FMS are discussed. After studying the properties of the FMS and perusing the methods of layout designing the genetic algorithms methods was selected as the most suitable method for designing the FMS. The genetic algorithm model, the most suitable way of coding the solutions into the organisms and the selected evolutionary and genetic operators are presented. In the model, the automated guided vehicles (AGVs) for transport between components of the FMS were used. In this connection, the most favourable number of rows and the sequence of devices in the individual row are established by means of genetic algorithms. In the end the test results of the application made and the analysis are discussed.
Ključne besede: flexible manufacturing systems, facility layout, optimization, genetic algorithms
Objavljeno: 01.06.2012; Ogledov: 949; Prenosov: 49
URL Povezava na celotno besedilo

7.
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: 01.06.2012; Ogledov: 1122; Prenosov: 46
URL Povezava na celotno besedilo

8.
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: 01.06.2012; Ogledov: 927; Prenosov: 45
URL Povezava na celotno besedilo

9.
AGRA: analysis of gene ranking algorithms
Simon Kocbek, Rune Saetre, Gregor Štiglic, Jin-Dong Kim, Igor Pernek, Yoshimasa Tsuruoka, Peter Kokol, Sophia Ananiadou, Jun-ichi Tsujii, 2011, kratki znanstveni prispevek

Opis: Often, the most informative genes have to be selected from different gene setsand several computer gene ranking algorithms have been developed to cope with the problem. To help researchers decide which algorithm to use, we developed the Analysis of Gene Ranking Algorithms (AGRA) system that offers a novel technique for comparing ranked lists of genes. The most important feature of AGRA is that no previous knowledge of gene ranking algorithms is needed for their comparison. Using the text mining system FACTA (Tsuruoka et al., 2008), AGRA defines what we call Biomedical Concept Space (BCS) for each gene list and offers comparison of the gene lists in six different BCS categories. The uploaded gene lists can be compared using two different methods. In the first method, the overlap between each pair of two gene lists of BCSs is calculated. The second method offers a text field where specific biomedical concept can be entered. AGRA searches for this concept in each genelistsć BCS, highlights the rank of the concept and offers a visual representation of concepts ranked above and below it.
Ključne besede: genetic algorithms, genetski algoritmi
Objavljeno: 05.06.2012; Ogledov: 1137; Prenosov: 43
URL Povezava na celotno besedilo

10.
Development of a web application for dynamic production scheduling in small and medium enterprises
Davorin Kofjač, Andrej Knaflič, Miroljub Kljajić, 2010, izvirni znanstveni članek

Opis: This article describes the development of a web-based dynamic job-shop scheduling system for small and medium enterprises. In large enterprises, scheduling is mainly performed with appropriate technology by human experts; many small and medium enterprises lack the resources to implement such a task. The main objective was to develop a cost-effective, efficient solution for job-shop scheduling in small and medium enterprises with an emphasis on accessibility, platform independence and ease of use. For these reasons, we decided to develop a web-based solution with the main emphasis on the development of an intelligent and dynamic user interface. The solution is built upon modular programming principles and enables dynamic scheduling on the basis of artificial intelligence, i.e. genetic algorithms. The solution has been developed as a standalone information system, which allows the management of virtually all scheduling activities through an administration panel. In addition, the solution covers the five main functionalities that completely support the scheduling process, i.e. making an inventory of resources available in the company, using it in the process of production planning, collecting data on production activities, distribution of up-to-date information and insight over events in the system.
Ključne besede: dynamic job-shop scheduling, genetic algorithms, web application development
Objavljeno: 10.07.2015; Ogledov: 633; Prenosov: 165
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