Advances in Systems Science and Applications <p><strong><em>Advances in Systems Science and Applications </em></strong><strong>(<em>ASSA</em>) </strong>is an international peer-reviewed open-source online academic journal. Its&nbsp;scope covers all major aspects of systems (and processes) analysis, modeling, simulation, and control, ranging from theoretical and methodological developments to a large variety of application areas. Survey articles and innovative results are also welcome.</p> <p>ASSA is aimed at the audience of scientists, engineers and researchers working in the framework of these problems. ASSA should be a platform on which researchers will be able to communicate and discuss both their specialized issues and interdisciplinary problems of systems analysis and its applications in science and industry, including data science, artificial intelligence, material science, manufacturing, transportation, power and energy, ecology, corporate management, public&nbsp;governance, finance, and many others.</p> International Institute for General Systems Studies, Pennsylvania, USA en-US Advances in Systems Science and Applications 1078-6236 Organization of traffic flows’ simulation aimed at establishment of integral characteristics of their dynamics <p>The paper presents an approach aimed at the study of various aspects of traffic passage through a multi-lane road that is based on computational experiments. Microscopic simulation based on models of the type “leader-following models” is considered to be the most adequate and the most accurate means for performing them. The leader-following model of the entire traffic flows in a city road network acquires the more holistic form via the formalism of hybrid dynamic systems or, in other words, event-switched systems. The general formalization of this approach is presented and the corresponding representation of multi-lane traffic according to this approach is presented. The latter includes the detailed formal description of the traffic flow carrier with a certain traffic organization as well as the description of conditions for drivers’ choice of acceleration/braking and lane change according to incentive motives for it and positions and speeds of neighboring vehicles and the vehicle itself. Organization of computational experiments allowing to establish the dependence of the average speed of traffic on the density of incoming flows, the distribution of various types of vehicles and their drivers, road organization and other factors in a multi-lane road is considered. It is demonstrated in what way they allow to evaluate quantitatively the dependence of the road throughput on the above factors. Results of calculations are presented and analyzed.</p> Andrey Valuev Anatoliy Alexeevich Solovyev ##submission.copyrightStatement## 2018-08-23 2018-08-23 18 2 1 10 10.25728/assa.2018.18.2.620 Surrogates for the matrix l0-quasinorm in sparse feedback design: Numerical study of the efficiency <pre>Some formulations of the optimal control problem require the resulting controller to be sparse; i.e., to contain zero elements in the gain matrix.</pre> <pre>On one hand, sparse feedback leads to the drop of performance as compared to the optimal control; on the other hand, it confers useful properties to the system. For instance, sparse controllers allow to design distributed systems with decentralized feedback.</pre> <pre>Some sparse formulations require the gain matrix of the controller to have a special sparse structure which is characterized by the presence of zero rows</pre> <pre>in the matrix. In this paper, various approximations to the number of nonzero rows of a matrix are considered and applied to sparse feedback design</pre> <pre>in optimal control problems for linear systems. Along with a popular approach based on using the matrix $\ell_1$-norm, more complex nonconvex surrogates</pre> <pre>are proposed and discussed, those surrogates being minimized via special numerical procedures.</pre> <pre>The efficiency of the approximations is compared via numerical experiments.</pre> Alexey Bykov Pavel Shcherbakov ##submission.copyrightStatement## 2018-08-23 2018-08-23 18 2 11 25 10.25728/assa.2018.18.2.604 Plasma Control in Tokamaks. Part 1. <p>Various concepts of tokamaks as leaders in solving the controlled thermonuclear fusion problem are presented. The evolution of tokamaks from round in vertical cross-section tokamaks with a large aspect ratio up to tokamaks with a small aspect ratio including spherical ones is characterized. The classification of modern tokamaks according to their poloidal systems with the location of the poloidal field coils inside and outside of the toroidal field coil is given, taking into account the presence of coils inside a vacuum vessel to stabilize the plasma position. The methods of plasma diagnostics by magnetic measurements outside the plasma, actuators for both plasma magnetic and kinetic control, associated with plasma additional heating, plasma magnetic and kinetic models, instabilities and disruptions of a plasma discharge are described.</p> Yuri Vladimirovich Mitrishkin Pavel Sergeyevich Korenev Artem Andreyevich Prokhorov Nikolay Mikhailovich Kartsev Mikhail Ivanovich Patrov ##submission.copyrightStatement## 2018-08-23 2018-08-23 18 2 26 52 10.25728/assa.2018.18.2.598 Use of neural network models in the market risk management <p>This topic is of high relevance due to the fact that many currently available mathematical market risk assessment models contain many limitations for their effective use. However, these limitations are often not feasible, what leads to a decrease in forecast accuracy. To avoid this, more accurate models are necessary. Neural network-based models can show a more precise result due to their basic property – nonlinearity.</p> <p>The interest in neural networks re-emerged only after some important theoretical results were attained in the early eighties&nbsp; and new hardware developments increased the processing capacities.</p> <p>Artificial neural networks can be most adequately characterised as «computational models» with particular properties such as the ability to adapt or learn, to generalise, or to cluster or organise data, and which operation is based on parallel processing.</p> <p>The task of this paper is to build a model that can enable us to assess a market risk for a company.</p> <p>The primary goal of this paper is to determine a lower bound of the yield to be forecast by the neural network model with a certain level of significance. Current actual yields will be fed to the neural network output, and some factors will be fed to the neural network input.</p> Mariya Radosteva Vladimir Soloviev Vera Ivanyuk Anatoliy Tsvirkun ##submission.copyrightStatement## 2018-08-23 2018-08-23 18 2 53 58 10.25728/assa.2018.18.2.582 Specifics of Long-Term Forecasting for Global Gas Markets <p>The article presents a methodology for developing long-term forecasts for global gas markets using optimization modeling. This approach can be effectively used for an integrated analysis of the global gas market conjuncture, and assessment of management decisions in the gas industry in both the short and long term. It allows to develop complex scenarios, where sensitivity analysis to different local and global factors can be estimated, including changes in production costs and volumes by country and type of gas, changes of demand and demand side responses, perspectives of development of infrastructure for gas transportation and transformation of gas pricing mechanisms. The research demonstrates that production of natural gas will grow in all regions, except for Europe, and of all types of gas, including shale gas, coalbed methane, coal gasification and biogas. The competition between world gas producers will be quite tough both at developed and developing markets. Up to 2040 the volumes and routes of world gas trade will be mostly determined by Asian natural gas markets development, which are highly influenced by their future economic growth and national energy policies. The role of LNG for the global gas market will grow in the coming decades, so that pipeline gas supplies would partly function as swing supplies.</p> Vyacheslav Kulagin Anna Galkina ##submission.copyrightStatement## 2018-08-23 2018-08-23 18 2 59 62 10.25728/assa.2018.18.2.578 WGW: A Hybrid Approach Based on Whale and Grey Wolf Optimization Algorithms for Requirements Prioritization <p>Requirement engineering is the base phase of any software project, since this phase is concerned about requirements identification, processing and manipulation. The main source of these requirements is the project stakeholders with considering the project constraints and limitation. &nbsp;Number of requirement is varying for each project, so the requirements prioritization term comes for prioritizing the order of execution for software requirements according to the stakeholder's opinions and decisions. Various proposed optimization algorithms are employed to solve optimization problems; recently whale optimization (WO) algorithm is proposed in 2016 by Mirjalili which mimics the main characteristic of humpback whales which is the foraging method that is called bubble-net technique. &nbsp;On the other hand Grey wolf optimization (GWO) algorithm was proposed in 2014 in order to solve optimization problems by imitating the grey wolves hunting behavior. In this paper, a Hybrid approach based on Whale and Grey wolf optimization algorithms (WGW) is proposed by combining the advantages of each algorithm in order to prioritize the software requirements. Moreover, the data set that used in this paper is RALIC which a real software project’s requirements is in order to evaluate the proposed method. Thus, the proposed method shows 91% accuracy of requirements prioritization comparing with RALIC data sat. &nbsp;</p> Raja Masadeh Amjad Hudaib Abdullah Alzaqebah ##submission.copyrightStatement## 2018-08-23 2018-08-23 18 2 63 83 10.25728/assa.2018.18.2.576 Segregation model for dynamic frequency allocation <p>We apply the Schelling segregation model to the dynamic frequency allocation. An algorithm is introduced for agents segregation over initially unknown radio channels. We relate the number of algorithm iterations until complete agents' segregation to the number of agents, networks, and the other parameters via numerical experiment.</p> Alexander Vladimirovich Kuznetsov ##submission.copyrightStatement## 2018-08-23 2018-08-23 18 2 84 92 10.25728/assa.2018.18.2.542 Risk analysis in seawater desalination sector: a case study of Beni Saf Water Company “BWC” <p>In this present paper, a risk analysis approach is applied to an Algerian reverse osmosis seawater desalination plant using the MADS MOSAR method. &nbsp;MADS MOSAR method is a stepwise risk analysis approach containing many phases. Our work begins with analyzing a review of past accidents triggered by the Ben in Saf Water Company (BWC) seawater desalination plant locating in the Algerian coast in Ain Temouchent region and analyzing their similar seawater desalination plants (or plants that using similar and potential equipment). Then, the MADS MOSAR method will apply essentially for the macroscopic vision (Module A). The macroscopic vision corresponds to a main risk analysis.</p> <p>In the current case study, we were able to identify eight subsystems where sources and scenarios of hazards are identified, accident scenarios are assessed, recognized and ranked by "Severity×Probability" grid. We found twenty-six scenarios whose we were able to assess them in function of their probability and severity using "probability x severity" grid criteria. At the end of the analysis, we were able to define and suggest the most appropriate prevention and protection barriers for the potential elements in the studied seawater desalination plant, including pipelines, transformers, compressors, high pressure pumps, pressure vessels and energy recovery devices.</p> Mohammed Bouamri Hassiba Bouabdesselam ##submission.copyrightStatement## 2018-08-24 2018-08-24 18 2 93 106 10.25728/assa.2018.18.2.531 An Approach for Developing Context-aware Adaptive Information Systems <p><strong>The new AutoSAR adaptive platform makes mixed-critical automotive systems able to adapt themselves in response to hardware and software failures at runtime. However, mapping functions of these automotive systems and reserving bandwidth for them are still major challenges. In this paper, we propose a model-based approach for mapping functions of an automotive system to its hardware nodes and reserving their bandwidth. To do so, an architecture description language for automotive systems (i.e. EAST-ADL) is used to design an embedded system, and to specify its timing requirements. The design model is then used for identifying functions allocation and their bandwidth in different system configurations. To schedule the critical functions of the system, the Earliest Deadline First (EDF) is used, while the Constant Bandwidth Server (CBS) is used for scheduling the non-critical functions. The quality of service for the non-critical functions is determined by their reserved bandwidth. In addition, a Tabu search-based approach is used for mapping the system functions to hardware nodes. Furthermore, there is a temporal isolation between the critical and non-critical functions. Thus, overruns of the non-critical functions do not affect the timing guarantees of the critical functions, and the quality of service for the non-critical functions is maximized.</strong></p> Mahmoud Mohammed Hussein ##submission.copyrightStatement## 2018-08-24 2018-08-24 18 2 107 120 10.25728/assa.2018.18.2.539