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Response surface method-based optimization of outer rotor permanent magnet synchronous motor
Vahid Rafiee, Jawad Faiz, 2019, izvirni znanstveni članek

Opis: The Finite Element Method (FEM) is a prominent analysis approach. Although it is applicable for simulation and optimization of electrical machines, FEM is a very time-consuming technique. One of the approaches to shorten the optimization runtime is the use of surrogate models instead of FEM. In this paper, the design and optimization of an outer rotor permanent magnet synchronous motor for a hybrid vehicle are investigated. Response surface methodology (RSM) with four input variables is integrated with a sequential quadratic programming algorithm for optimization. Before the optimization, the performance of the surrogate model in the prediction of untried points is validated. Finally, the optimal motor is simulated by FEM to verify the results of RSM-based optimization, and the outputs of both models are compared.
Ključne besede: response surface surrogate method, outer rotor permanent magnet synchronous motor, sequential quadratic programming optimization
Objavljeno v DKUM: 05.12.2023; Ogledov: 29; Prenosov: 0
.pdf Celotno besedilo (683,42 KB)
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Generalised fuzzy linear programming
Janez Usenik, Maja Žulj, 2023, izvirni znanstveni članek

Opis: Linear programming is one of the widely used methods for optimising business systems, which includes organisational, financial, logistic and control subsystems of energy systems in general. It is possible to express numerous real-world problems in a form of linear program and then solve by simplex method [1]. In the development of linear programming, we are facing a number of upgrades and generalisations, as well as replenishment. Particularly interesting in recent years is an option that decision variables and coefficients are fuzzy numbers. In this case we are dealing with fuzzy linear programming. If we also include in a fuzzy linear program a generalisation with respect to Wolfe’s modified simplex method [1], we obtain a generalised fuzzy linear program (GFLP). Usenik and Žulj introduced methods for solving those programs and proved the existence of the optimal solution in [2]. In the article, the simplex algorithm which enables the determining of an optimal solution for GFLP is described. There is a numerical example at the end of the article that illustrates the algorithm.
Ključne besede: linear programming, fuzzy linear programming, generalised linear programming, generalised fuzzy linear programmin
Objavljeno v DKUM: 11.10.2023; Ogledov: 76; Prenosov: 4
.pdf Celotno besedilo (21,53 MB)
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Editorial: combined water and heat integration in the process industries
Elvis Ahmetović, Ignacio E. Grossmann, Zdravko Kravanja, François Marechal, Jiri Klemeš, Luciana E. Savulescu, Dong Hongguang, 2022, predgovor, uvodnik, spremna beseda

Opis: Water and energy are resources that are used in large quantities in different sectors (domestic, agricultural, and industrial). Based on data on global water and energy consumption in the world over the recent past, as well as forecasts for the coming years, a continuous trend of increasing water and energy consumption can be observed. ...
Ključne besede: water integration, heat integration, systematic methods, pinch analysis, mathematical programming, heat-integrated water networks, optimisation, process industry
Objavljeno v DKUM: 18.08.2023; Ogledov: 139; Prenosov: 12
.pdf Celotno besedilo (505,83 KB)
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Using Artificial Intelligence in Software Development: a case analysis
Patricija Vrentuša, 2023, magistrsko delo

Opis: In this work, we talk about artificial intelligence and its impact on software development. We define the AI concept, the software development process, and the various uses of AI in programming. We put a special focus on the ethical aspects of AI. In the empirical part, we analyzed the AI pair programming tool created by Microsoft called GitHub Copilot. We examine several usage examples, as well as the opinions of developers that have been using GitHub Copilot. We found that the AI pair programmer tool helps programmers increase productivity and automate mundane tasks to concentrate on more complex and interesting parts of software development. However, some programmers raise concerns about unethical concepts connected to the development of GitHub Copilot, implying violations of original code author copyrights. We discuss current licenses, other possible solutions, and the morality of building AI on open-sourced repositories. Moreover, many believe that the future will be increasingly intertwined with AI in all industries and that the only way to preserve (software development) jobs is to keep learning and being innovative and creative. Programmers say that almost certainly their job will not vanish because of AI advancement; only the scope of their work will change.
Ključne besede: AI, software development, ethics, AI pair programming, GitHub Copilot.
Objavljeno v DKUM: 21.02.2023; Ogledov: 702; Prenosov: 111
.pdf Celotno besedilo (1,49 MB)

Automatic compiler/interpreter generation from programs for domain-specific languages using semantic inference : doktorska disertacija
Željko Kovačević, 2022, doktorska disertacija

Opis: Presented doctoral dissertation describes a research work on Semantic Inference, which can be regarded as an extension of Grammar Inference. The main task of Grammar Inference is to induce a grammatical structure from a set of positive samples (programs), which can sometimes also be accompanied by a set of negative samples. Successfully applying Grammar Inference can result only in identifying the correct syntax of a language. But, when valid syntactical structures are additionally constrained with context-sensitive information the Grammar Inference needs to be extended to the Semantic Inference. With the Semantic Inference a further step is realised, namely, towards inducing language semantics. In this doctoral dissertation it is shown that a complete compiler/interpreter for small Domain-Specific Languages (DSLs) can be generated automatically solely from given programs and their associated meanings using Semantic Inference. For the purpose of this research work the tool LISA.SI has been developed on the top of the compiler/interpreter generator tool LISA that uses Evolutionary Computations to explore and exploit the enormous search space that appears in Semantic Inference. A wide class of Attribute Grammars has been learned. Using Genetic Programming approach S-attributed and L-attributed have been inferred successfully, while inferring Absolutely Non-Circular Attribute Grammars (ANC-AG) with complex dependencies among attributes has been achieved by integrating a Memetic Algorithm (MA) into the LISA.SI tool.
Ključne besede: Grammatical Inference, Semantic Inference, Genetic Programming, Attribute Grammars, Memetic Algorithm, Domain-Specific Languages
Objavljeno v DKUM: 17.02.2022; Ogledov: 918; Prenosov: 107
.pdf Celotno besedilo (3,59 MB)

Cloud Computing Deployment and Management : A Collection of Exercises and Tasks with Solutions
Aleš Zamuda, drugo učno gradivo

Opis: The subject Cloud Computing Deployment and Management is included in the second-cycle Bologna Study Programme Computer Science and Information Technologies as a full-time study unit. This document presents study material for computer exercises in this subject. After an introduction, then individual tasks with solutions to the computer exercises in the subsequent chapters are provided. This is followed by a list of archived files containing the computer format of the provided solutions.
Ključne besede: cloud computing, virtualization, parallel programming, distributed programming, virtual computing environments, high-performance computing
Objavljeno v DKUM: 11.09.2020; Ogledov: 1098; Prenosov: 52
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Prepoznavanje položaja in orientacije objekta s strojnim vidom vodenega robotskega sistema
Sebastjan Spital, 2018, diplomsko delo

Opis: V diplomskem delu je predstavljeno zajemanje in obdelava slike s spletno kamero Logitech v programu LabView z dodanimi moduli. LabView komunicira s krmilnikom robota Mitshubishi, kateri prejme informacijo o koordinatah in prestavi objekt.
Ključne besede: Strojni vid, zajemanje slike, obdelava slike, komunikacija Ethernet, LabView, kamera Logitech, robot Mitshubishi, Ciros Programming
Objavljeno v DKUM: 21.01.2019; Ogledov: 1431; Prenosov: 111
.pdf Celotno besedilo (2,00 MB)

A practical method for the optimal design of continuous footing using ant-colony optimization
Boonchai Ukritchon, Suraparb Keawsawasvong, 2016, izvirni znanstveni članek

Opis: The objective of this paper is to present a practical method for the optimal design of a continuous footing subjected to vertical and horizontal loads. The design problem of finding the optimal size of footing as well as the minimum steel reinforcement is formulated in a nonlinear minimization form. The continuous footing is subjected to the vertical and horizontal loads acting on the top of the column. There are four design variables in the design problem, i.e., the width of the footing, the thickness of the footing, the soil-embedment depth, and the amount of steel reinforcement. The required geotechnical constraints include the bearing capacity, overturning, as well as global sliding and local sliding at the footing corners. Short-term stability and long-term stability are considered simultaneously in the same formulation. The structural constraints are enforced to control the shear force and bending moment within the section resistance. The formulation of the problem’s constraints leads to the nonlinear programming, whose objective function is to minimize the total cost of the footing material, including the concrete and steel reinforcement. The optimal solution is solved using the ant-colony optimization algorithm MIDACO. The proposed optimization method is demonstrated through the actual design of the footing for supporting a large machine moving on rails.
Ključne besede: optimal design, footing, stability, nonlinear programming, ant-colony optimization
Objavljeno v DKUM: 18.06.2018; Ogledov: 1163; Prenosov: 73
.pdf Celotno besedilo (446,51 KB)
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New computational models for better predictions of the soil-compression index
Ahmet Demir, 2015, izvirni znanstveni članek

Opis: The compression index is one of the important soil parameters that are essential for geotechnical designs. Because laboratory and in-situ tests for determining the compression index (Cc) value are laborious, time consuming and costly, empirical formulas based on soil parameters are commonly used. Over the years a number of empirical formulas have been proposed to relate the compressibility to other soil parameters, such as the natural water content, the liquid limit, the plasticity index, the specific gravity. These empirical formulas provide good results for a specific test set, but cannot accurately or reliably predict the compression index from various test sets. The other disadvantage is that they tend to use a single parameter to estimate the compression index (Cc), even though Cc exhibits spatial characteristics depending on several soil parameters. This study presents the potential for Genetic Expression Programming (GEP) and the Adaptive Neuro-Fuzzy (ANFIS) computing paradigm to predict the compression index from soil parameters such as the natural water content, the liquid limit, the plastic index, the specific gravity and the void ratio. A total of 299 data sets collected from the literature were used to develop the models. The performance of the models was comprehensively evaluated using several statistical verification tools. The predicted results showed that the GEP and ANFIS models provided fairly promising approaches to the prediction of the compression index of soils and could provide a better performance than the empirical formulas.
Ključne besede: compression index, statistical analysis, genetic expression programming, adaptive neuro-fuzzy, empirical equations
Objavljeno v DKUM: 14.06.2018; Ogledov: 1213; Prenosov: 74
.pdf Celotno besedilo (274,65 KB)
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The anchored pile wall optimization using NLP approach
Helena Vrecl-Kojc, 2005, izvirni znanstveni članek

Opis: The type of a retaining structure as well as the structure configuration mainly depends on geological conditions. If geological, urban and other data allow an alternative, the costs should also be considered as an important factor. In geotechnical practise, pile walls are especially used in excavations, in the erection of traffic facilities and in the sanitation of landslides. This paper is aimed at presenting economical differences between cantilever and anchoring pile walls and the impact of different parameters on costs. The optimization method, which uses mathematical programming, gives an optimal solution to geometry, self-manufacturing costs, and other characteristics of the structure in a uniform optimization process. This paper presents the optimization process using the nonlinear programming (NLP) approach for the anchored pile wall. The application presented only serves to confirm the effectiveness of the proposed optimization method. Therefore, the retaining structure is situated in homogeneous non-cohesive soil at three different soil friction angles of 35°, 30° and 25°. The generalized analytical method, the USA method, which was first introduced by Bowles [3], isused in the application. The analysis of the results shows the impact of parameters, the main controlling factors, configuration geometry and savings. The optimal results allowed from 18 up to 47 per cent savings compared to the cantilever pile wall depending on ground and structure input data and the excavation depth.
Ključne besede: civil engineering, optimum design, retaining structures, USA analytical method, nonlinear programming
Objavljeno v DKUM: 16.05.2018; Ogledov: 1129; Prenosov: 63
.pdf Celotno besedilo (216,45 KB)
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