Temat: network simulation - Prolib Integro

Skocz do pozycji: 1.

Tytuł:: Automatic calibration and sensitivity analysis of DISPRIN model parameters: A case study on Lesti watershed in East Java, Indonesia
Kalibracja automatyczna i analiza czułości parametrów modelu DISPRIN: Przypadek zlewni Lesti w prowincji Jawa Wschodnia, Indonezja
Autorzy:: Sulianto, S.
Bisri, M.
Limantara, L. M.
Sisinggih, D.
Tematy:: differential evolution
Dee Investigation Simulation Program for Regulating Network (DISPRIN)
model
Lesti watershed
simulation
ewolucja różnicowa
model DISPRIN
symulacja
zlewnia Lesti; Pokaż więcej
Wydawca:: Instytut Technologiczno-Przyrodniczy
Powiązania:: https://bibliotekanauki.pl/articles/947273.pdf Link otwiera się w nowym oknie
Opis:: The Dee Investigation Simulation Program for Regulating Network (DISPRIN) model consists of eight tanks that are mutually interconnected. It contains 25 parameters involved in the process of transforming rainfall into runoff data. This complexity factor is the appeal to be explored in order to more efficiently. Parameterization process in this research is done by using Differential Evolution (DE) algorithm while parameters sensitivity analysis is done by using Monte Carlo simulation method. Software application models of merging the two concepts are called DISPRIN25-DE model and compiled using code program M-FILE from MATLAB. Results of research on Lesti watershed at the control point Tawangrejeni automatic water level recorder (AWLR) station (319.14 km²) in East Java Indonesia indicate that the model can work effectively for transforming rainfall into runoff data series. Model performance at the calibration stage provide value of NSE = 0.871 and PME = 0.343 while in the validation stage provide value of NSE = 0.823 and PME = 0.180. Good performance in the calibration process indicates that DE algorithm is able to solve problems of global optimization of the equations system with a large number of variables. The results of the sensitivity analysis of 25 parameters showed that 3 parameters have a strong sensitivity level, 7 parameters with a medium level and 15 other parameters showed weak sensitivity level to performance of DISPRIN model.
Model DISPRIN składa się z ośmiu zbiorników wzajemnie ze sobą połączonych. Zawiera 25 parametrów zaangażowanych w proces transformacji danych opadowych w dane odpływu. Ten czynnik złożoności skłania do podjęcia badań celem zwiększenia wydajności. W badaniach prezentowanych w niniejszej pracy proces parametryzacji zrealizowano, stosując algorytm zróżnicowanej ewolucji (DE), podczas gdy analizę czułości przeprowadzono z użyciem metody symulacji Monte Carlo. Modele aplikacji polegające na łączeniu dwóch koncepcji nazywane są DISPRIN25-DE i są kompilowane za pomocą programu M-FILE z MATLAB. Wyniki badań zlewni Lesti (319,14 km²) w punkcie kontrolnym stacji Tawangrejeni z automatycznym pomiarem poziomu wody w prowincji Jawa Wschodnia w Indonezji wskazują, że model może efektywnie działać w celu przekształcenia opadów w serie danych o odpływie. Na etapie kalibracji model dostarczył wartości NSE = 0,871 i PME = 0,343, a na etapie walidacji wartości NSE = 0.823 i PME = 0,180. Dobre rezultaty w procesie kalibracji wskazują, że algorytm DE jest zdolny rozwiązywać problemy globalnej optymalizacji systemu równań z dużą liczbą zmiennych. Wyniki analizy czułości 25 parametrów wykazały, że 3 parametry mają wysoką czułość, 7 – pośrednią, a 15 innych parametrów cechuje niski poziom czułości na zachowanie modelu DISPRIN.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: QoS Extensions for Flow-Awareness Networks
Autorzy:: Kaczmarek, Sylwester
Wolff, Maciej
Tematy:: FSA
flow network
QoS
MBAC
simulation; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/2074139.pdf Link otwiera się w nowym oknie
Opis:: The paper contains a description and research results of the proposal for distributed QoS extensions for Flow-Based Networking. These QoS extensions let the network accept or reject flows based on current network load and QoS promises for each of the flows. Proposed solution consists of two distributed components, each of them performing in every node, measurement system and access control. The solution could be applied in any network architecture that is able to distinguish flows and routers in this architecture contains flow state table. Proposed approach was verified by simulation, in FSA architecture. Verification was done for six different network structures servicing two traffic classes (MRS, ARS). The results of the simulation tests have confirmed that the average time delay and packet loss ratio in the network with proposed extensions are below thresholds and meet the requirements recommended by ITU-T.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Optimization of Distribution System Reliability
Autorzy:: Zemite, L.
Gerhards, J.
Gorobetz, M.
Levchenkov, A.
Tematy:: distribution network
simulation
power supply reliability; Pokaż więcej
Wydawca:: EEEIC International Barbara Leonowicz Szabłowska
Powiązania:: https://bibliotekanauki.pl/articles/136268.pdf Link otwiera się w nowym oknie
Opis:: Reliability analysis of distribution systems has been attracting increasing attention. A special concern pertains to the distribution networks on which most failures occurs. The optimization of distribution system of breakers and power switches is a possible strategy to improve reliability. The paper describes development procedure for modelling restoring after a fault and calculating associated reliability indices and customers’ outage costs. The developed model of the network and reliability and outage costs calculating algorithm is suitable for multi-criteria analysis of the network. Proposed reliability and outage costs calculation algorithm is based on Monte Carlo simulation and genetic algorithm.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Deep learning classification and recognition method for milling surface roughness combined with simulation data
Autorzy:: Lu, Lingli
Yi, Huaian
Shu, Aihua
Qin, Jianhua
Lu, Enhui
Tematy:: milling surface
classification
deep neural network
simulation; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/2203367.pdf Link otwiera się w nowym oknie
Opis:: To address the problem that a deep neural network needs a sufficient number of training samples to have a good prediction performance, this paper firstly used the Z-Map algorithm to generate a simulated profile of the milling surface and construct an optical simulation model of surface imaging to supplement the training sample size of the neural network. Then the Deep CORAL model was used to match the textures of the simulated samples and the actual samples across domains to solve the problem that the simulated samples were not in the same domain as the actual milling samples. Experimental results have shown that high texture matching could be achieved between optical simulation images and actual images, laying the foundation for expanding the actual milled workpiece images with the simulation images. The deep convolutional neural model Xception was used to predict the classification of six classes of data sets with the inclusion of simulation images, and the accuracy was improved from 86.48% to 92.79% compared with the model without the inclusion of simulation images. The proposed method solves the problem of the need for a large number of samples for deep neural networks and lays the foundation for similar methods to predict surface roughness for different machining processes.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Requirements for logistics multimodal networks simulation
Wymagania dla symulacji logistycznych sieci multimodalnych
Autorzy:: Pawlewski, P.
Tematy:: simulation
modeling
multimodal network
symulacja
modelowanie
sieci multimodalne; Pokaż więcej
Wydawca:: Polskie Towarzystwo Zarządzania Produkcją
Powiązania:: https://bibliotekanauki.pl/articles/339665.pdf Link otwiera się w nowym oknie
Opis:: The author focuses his research mainly on the area of logistics, especially on problems related with logistics multi- modal networks. In the paper the basic characteristics and benefits from using multimodality and intermodality is presented. The author describes the multimodal and intermodal applications from the viewpoint of object simulation. The main Research Highlight of performed works is: definition of requirements for simulation in multimodal logistics networks. One of the main papers finding is distinction of characteristics features of multimodal networks, which enable the definition of requirements. These requirements are necessary for proper selection of tool for mode- ling and simulation logistics multimodal networks.
Główny obszar badań autora obejmuje logistykę, a szczególnie problemy związane z logistycznymi sieciami multimodalnymi. W prezentowanej pracy zostały przedstawione charakterystyki podejścia multimodalnego i intermodalne- go oraz korzyści wynikające z ich wykorzystania. Najważniejszym punktem realizowanych prac jest definicja wymagań stawianych budowaniu modeli symulacyjnych i realizacji symulacji w logistycznych sieciach multimodalnych. Jednym z najważniejszych efektów prezentowanej pracy jest wyróżnienie charakterystycznych cech sieci multimodalnych, umożliwiające definicję wymagań, które są nie- zbędne do poprawnego wyboru narzędzia, które będzie używane do modelowania i symulacji omawianych sieci.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Self-learning control algorithms used to manage the operating of an internal combustion engine
Autorzy:: Graba, Mariusz
Mamala, Jarosław
Bieniek, Andrzej
Tematy:: transport
simulation
combustion engines
environmental protection
neural network; Pokaż więcej
Wydawca:: Instytut Techniczny Wojsk Lotniczych
Powiązania:: https://bibliotekanauki.pl/articles/242942.pdf Link otwiera się w nowym oknie
Opis:: The article presents the possibility of using self-learning control algorithms to manage subassemblies of an internal combustion engine in order to reduce exhaust emissions to the natural environment. In compression ignition (CI) engines, the issue of emissions mainly concerns two components: particulate matter (PM) and nitrogen oxides (NOx). The work focuses mainly on the possibility of reducing the emission of nitrogen oxides. It is assumed that the particularly problematic points when it comes to excessive emission of harmful substances are the dynamic states in which combustion engines operate constantly. In dynamically changing operating points, it is very difficult to choose the right setting of actuators such as the exhaust gas recirculation (EGR) valve to ensure the correct operation of the unit and the minimum emission of these substances. In the light of the above, an attempt was made to develop a selflearning mathematical model, which can predict estimated emission levels of selected substance basing on current measurement signals (e.g. air, pressure, crankshaft rotational speed, etc.). The article presents the results of the estimation of nitrogen oxides by the trained neural network in comparison to the values measured with the use of a sensor installed in the exhaust system. The presented levels of estimated and measured results are very similar to each other and shifted over time in favour of neural networks, where the information about the emission level appears much earlier. On the basis of the estimated level, it shall be possible to make an appropriate decision about specific settings of recirculation system components, such as the EGR valve. It is estimated that by using the chosen control method it is possible significantly to reduce the emission of harmful substances into the natural environment while maintaining dynamic properties of the engine.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: Examples of Simulation of the Alloying Elements Effect on Austenite Transformations During Continuous Cooling
Autorzy:: Trzaska, Jacek
Tematy:: CCT diagram
simulation
neural network
heat treatment
steel; Pokaż więcej
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:: https://bibliotekanauki.pl/articles/2049560.pdf Link otwiera się w nowym oknie
Opis:: The article shows examples of simulation of the chemical composition effect on austenite transformation during continuous cooling. The calculations used own neural model of CCT (Continuous Cooling Transformation) diagrams describing austenite transformations that occur during continuous cooling. The model allows to calculate a CCT diagrams of structural steels and engineering steels based on chemical composition of steel and austenitizing temperature. Examples of simulation shown herein are related to the effect of selected elements on the temperatures of phase transformations, hardness and volume fraction of ferrite, pearlite, bainite and martensite in steel.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: RED-LE: A Revised Algorithm for Active Queue Management
Autorzy:: Hassan, Samuel O.
Tematy:: active queue management
network congestion
router
RED-LE
simulation; Pokaż więcej
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Powiązania:: https://bibliotekanauki.pl/articles/2142301.pdf Link otwiera się w nowym oknie
Opis:: The random early detection (RED) algorithm was developed in 1993. Nearly three decades later, several improved variants have been proposed by scientists. The use of a (pure) linear function for computing packet drop probability has turned out to be a disadvantage, leading to the problem of large delays. Such a problem may be addressed by using linear and non-linear (i.e. as exponential) packet drop probability functions. This paper proposes a revised RED active queue management algorithm named RED-linear exponential (RED-LE). This variant involves an interplay of linear and exponential drop functions, in order to improve the performance of the original RED algorithm. More importantly, at low and moderate network traffic loads, the RED-LE algorithm employs the linear drop action. However, for high traffic loads, RED-LE employs the exponential function for computing the packet drop probability rate. Experimental results have shown that RED-LE effectively controls congestion and offers an improved network performance under different traffic loads.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: Neural networks for function approximation in dynamic modelling
Autorzy:: Nedbálek, J.
Tematy:: reliability
Monte Carlo
RBF neural network
simulation
temperature; Pokaż więcej
Wydawca:: Uniwersytet Morski w Gdyni. Polskie Towarzystwo Bezpieczeństwa i Niezawodności
Powiązania:: https://bibliotekanauki.pl/articles/2069707.pdf Link otwiera się w nowym oknie
Opis:: The paper demonstrates the comparsion of Monte Carlo simulation (MC) algorithm with the Radial Basis Function (RBF) neural network enhancement of the same algorithm in the reliability case study. In our test, we dispose of the tank containing liquid water – its temperature process variable evolves deterministicly according to the differential equation, which solution is known. All component failures are considered as a stochastic events. In the case of surpassing temperature treshhold of the liquid inside the tank, we interpret the situation as the system failure. With regard to process dynamics, we attempt to evaluate the tank system unreliability related to the initiative input parameters setting. The neural network is used in equation coeficients calculation, which is executed in each transient state. Due to the neural networks, for some of the initial component settings, we can achieve the results of computation faster than in classical way of coeficients calculating and substituting into the equation.
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: Estimating Port Network Traffic Capacity
Autorzy:: Bellsolà Olba, X.
Daamen, W.
Vellinga, T.
Hoogendoorn, S. P.
Tematy:: port capacity
network capacity
simulation
ports
waterway
traffic; Pokaż więcej
Wydawca:: Akademia Morska w Szczecinie. Wydawnictwo AMSz
Powiązania:: https://bibliotekanauki.pl/articles/135208.pdf Link otwiera się w nowym oknie
Opis:: Port capacity is a relevant parameter to estimate the expected performance of a port facility. Many simulation models have been used to predict traffic in ports and waterways, but they do not include provisions for estimating the port’s capacity. The innovative method presented here determines a Port Network Traffic Capacity (PNTC) based on simulation. This method estimates PNTC given the configuration and processing characteristics of the port. It can be a useful tool to apply while designing ports, because only a limited number of simulations are required to estimate of the capacity of the infrastructure under consideration.
Dostawca treści:: Biblioteka Nauki

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