1. NARX Deep Convolutional Fuzzy System for Modelling Nonlinear Dynamic ProcessesMarjan Golob, 2023, original scientific article Abstract: This paper presents a new approach for modelling nonlinear dynamic processes (NDP). It is based on a nonlinear autoregressive with exogenous (NARX) inputs model structure and a deep convolutional fuzzy system (DCFS). The DCFS is a hierarchical fuzzy structure, which can overcome the deficiency of general fuzzy systems when facing high dimensional data. For relieving the curse of dimensionality, as well as improving approximation performance of fuzzy models, we propose combining the NARX with the DCFS to provide a good approximation of the complex nonlinear dynamic behavior and a fast-training algorithm with ensured convergence. There are three NARX DCFS structures proposed, and the appropriate training algorithm is adapted. Evaluations were performed on a popular benchmark—Box and Jenkin’s gas furnace data set and the four nonlinear dynamic test systems. The experiments show that the proposed NARX DCFS method can be successfully used to identify nonlinear dynamic systems based on external dynamics structures and nonlinear static approximators.
Keywords: process identification, input-output modelling, NARX model, decomposed fuzzy system, hierarchical fuzzy system, deep convolutional fuzzy system
Published in DKUM: 30.11.2023; Views: 422; Downloads: 11
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2. Use of a simulation environment and metaheuristic algorithm for human resource management in a cyber-physical systemHankun Zhang, Borut Buchmeister, S. Liu, Robert Ojsteršek, 2019, independent scientific component part or a chapter in a monograph Keywords: simulation modelling, evolutionary computation, cyber-physical system, heuristic kalman algorithm, human resource management
Published in DKUM: 06.06.2019; Views: 1430; Downloads: 432
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3. Systems methodology for strategic decision-making in complex healthcare systemTadeja Jere Lazanski, 2017, original scientific article Abstract: Systems methodology as a support for strategic decision- making will be discussed in the paper. A society will be presented as a complex system, which is comprised of many smaller, complex systems as its component parts. The healthcare system is one of them. The support to the strategic decision-making in a healthcare system will be shown through systems thinking and systems modelling. We will develop models of a healthcare system in frame of a systems dynamics; a qualitative causal loop diagram (CLD), which helps us to discuss the challenges categorically and a quantitative model, which is a simulation model. Both models illustrate the discussed methodology.
Keywords: systems methodology, healthcare system, strategic decision-making, systems thinking, modelling
Published in DKUM: 09.10.2018; Views: 1565; Downloads: 73
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4. Next generation logistics : technologies and applicationsBorut Jereb, 2017, scientific monograph Abstract: The scientific monograph “Next Generation Logistics: Technologies and Applications” focuses on smart system modelling approaches to some logistics problems, sustainability applications on warehousing technologies as well as investment and management of logistics systems. The monograph includes nine chapters that approach to logistical problems from practical requirements.
The reader will find both mathematical modelling approaches to some warehousing, supply chain problems as well as management related issues in the related problems. Since it also includes some case studies in the chapters, this monograph contributes the next generation logistics in both theoretical and practical ways.
Keywords: logistics, computer technologies, smart system modelling, warehousing, investment, management, logistics systems
Published in DKUM: 09.05.2018; Views: 1482; Downloads: 85
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5. Systems approach to tourism : a methodology for defining complex tourism systemTadeja Jere Lazanski, 2017, original scientific article Abstract: Background and Purpose: The complexity of the tourism system, as well as modelling in a frame of system dynamics, will be discussed in this paper. The phaenomenon of tourism, which possesses the typical properties of global and local organisations, will be presented as an open complex system with all its elements, and an optimal methodology to explain the relations among them. The approach we want to present is due to its transparency an excellent tool for searching systems solutions and serves also as a strategic decision-making assessment. We will present systems complexity and develop three models of a complex tourism system: the first one will present tourism as an open complex system with its elements, which operate inside of a tourism market area. The elements of this system present subsystems, which relations and interdependencies will be explained with two models: causal-loop diagram and a simulation model in frame of systems dynamics.
Design/methodology/approach: Systems methodology will be shown as the appropriate one, when we discuss complex systems challenges. For illustration, systems approach and systems methodology will be applied to tourism models. With building a qualitative causal-loop diagram we will describe the tourism system complexity in forms of system%s elements relations. Mutual influences among the elements will be presented with positive and negative loops, which forms circles of reinforcement and balance. This will help us to discuss the problem categorically. The final model will follow the causal-loop diagram. This will be a simulation model in a frame of system dynamics as an illustration of the discussed methodology.
Results: The methodology offers the solution of effective and holistic promotion of complex tourism system transformation, which has the potential to go beyond the myth of sustainable tourism and create significant shifts in the approach and acting of the participants (elements of the system) involved. Systems approach brings to tourism and the society, in general, broader dimensions of thinking, the awareness interdependency, interconnectivity, and responsibility for the behaviour of a system, which can be observed by feedback loops.
Conclusions: Findings about meaningfulness of systems thinking presented in the paper, are rarely presented to tourism society systemically and with the aim of designing sustainable complex tourism system. They show new approach, systems awareness and teaches thinking %out of the box%. Consequently, the sustainable behaviour is achieved: tourism supply and demand meet on responsible base and they connect to responsible stakeholders.
Keywords: systems approach, complexity, tourism system, modelling, system dynamics
Published in DKUM: 22.01.2018; Views: 1144; Downloads: 209
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6. Quantitative model for economic analyses of information security investment in an enterprise information systemRok Bojanc, Borka Jerman-Blažič, 2012, original scientific article Abstract: The paper presents a mathematical model for the optimal security-technology investment evaluation and decision-making processes based on the quantitative analysis of security risks and digital asset assessments in an enterprise. The model makes use of the quantitative analysis of different security measures that counteract individual risks by identifying the information system processes in an enterprise and the potential threats. The model comprises the target security levels for all identified business processes and the probability of a security accident together with the possible loss the enterprise may suffer. The selection of security technology is based on the efficiency of selected security measures. Economic metrics are applied for the efficiency assessment and comparative analysis of different protection technologies. Unlike the existing models for evaluation of the security investment, the proposed model allows direct comparison and quantitative assessment of different security measures. The model allows deep analyses and computations providing quantitative assessments of different options for investments, which translate into recommendations facilitating the selection of the best solution and the decision-making thereof. The model was tested using empirical examples with data from real business environment.
Keywords: modelling, security technology, economic metrics, investment, enterprise information system
Published in DKUM: 22.01.2018; Views: 1235; Downloads: 386
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7. A statistical model for shutdowns due to air quality control for a copper production decision support systemKhalid Aboura, 2015, original scientific article Abstract: Background: In the mid-1990s, a decision support system for copper production was developed for one of the largest mining companies in Australia. The research was conducted by scientists from the largest Australian research center and involved the use of simulation to analyze options to increase production of a copper production facility.
Objectives: We describe a statistical model for shutdowns due to air quality control and some of the data analysis conducted during the simulation project. We point to the fact that the simulation was a sophisticated exercise that consisted of many modules and the statistical model for shutdowns was essential for valid simulation runs.
Method: The statistical model made use of a full year of data on daily downtimes and used a combination of techniques to generate replications of the data.
Results: The study was conducted with a high level of cooperation between the scientists and the mining company. This contributed to the development of accurate estimates for input into a support system with an EXCEL based interface.
Conclusion: The environmental conditions affected greatly the operations of the production facility. A good statistical model was essential for the successful simulation and the high budget expansion decision that ensued.
Keywords: decision support system, simulation, statistical modelling
Published in DKUM: 28.11.2017; Views: 1317; Downloads: 335
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8. System dynamic models as decision-making tools in agritourismTadeja Jere Lazanski, 2016, original scientific article Abstract: Agritourism as a type of niche tourism is a complex and softly defined phaenomenon. The demands for fast and integrated decision regarding agritourism and its interconnections with environment, economy (investments, traffic) and social factors (tourists) is urgent. Many different methodologies and methods master softly structured questions and dilemmas with global and local properties. Here we present methods of systems thinking and system dynamics, which were first brought into force in the educational and training area in the form of different computer simulations and later as tools for decision-making and organisational re-engineering. We develop system dynamics models in order to present accuracy of methodology. These models are essentially simple and can serve only as describers of the activity of basic mutual influences among variables. We will pay the attention to the methodology for parameter model values determination and the so-called mental model. This one is the basis of causal connections among model variables. At the end, we restore a connection between qualitative and quantitative models in frame of system dynamics.
Keywords: agritourism, multi-criteria decision-making, modelling, system dynamics
Published in DKUM: 14.11.2017; Views: 1279; Downloads: 199
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10. Some simple approaches to planning the inventory of spare components of an industrial systemAlenka Brezavšček, Alenka Hudoklin, 2010, published scientific conference contribution Abstract: Two variants of a simple stochastic model for planning the inventory of spare components supporting maintenance of an industrial system are developed. In both variants, the aim is to determine how many spare components are needed at the beginning of a planning interval to fulfil demand for corrective replacements during this interval. Under the first variant, the acceptable probability of spare shortage during the planning interval is chosen as a decision variable while in the second variant, the adequate spare inventory level is assessed taking into account the expected number of component failures within the planning interval. Calculation of the number of spare components needed depends on the form of the probability density function of component failure times. Different statistical density functions that are useful to describe this function are presented. Advantages and disadvantages of using a particular density function in our model are discussed. The applicability of the model is given through illustrative numerical examples.
Keywords: industrial system, maintenance, corrective replacement, spare components, inventory planning, stochastic modelling
Published in DKUM: 06.06.2012; Views: 2080; Downloads: 149
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