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Tytuł:
A Neural Network Model for Object Mask Detection in Medical Images
Autorzy:
Tereikovskyi, Igor
Korchenko, Oleksander
Bushuyev, Sergey
Tereikovskyi, Oleh
Ziubina, Ruslan
Veselska, Olga
Powiązania:
https://bibliotekanauki.pl/articles/2200721.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
model
neural network
object mask
medical images
Opis:
In modern conditions in the field of medicine, raster image analysis systems are becoming more widespread, which allow automating the process of establishing a diagnosis based on the results of instrumental monitoring of a patient. One of the most important stages of such an analysis is the detection of the mask of the object to be recognized on the image. It is shown that under the conditions of a multivariate and multifactorial task of analyzing medical images, the most promising are neural network tools for extracting masks. It has also been determined that the known detection tools are highly specialized and not sufficiently adapted to the variability of the conditions of use, which necessitates the construction of an effective neural network model adapted to the definition of a mask on medical images. An approach is proposed to determine the most effective type of neural network model, which provides for expert evaluation of the effectiveness of acceptable types of models and conducting computer experiments to make a final decision. It is shown that to evaluate the effectiveness of a neural network model, it is possible to use the Intersection over Union and Dice Loss metrics. The proposed solutions were verified by isolating the brachial plexus of nerve fibers on grayscale images presented in the public Ultrasound Nerve Segmentation database. The expediency of using neural network models U-Net, YOLOv4 and PSPNet was determined by expert evaluation, and with the help of computer experiments, it was proved that U-Net is the most effective in terms of Intersection over Union and Dice Loss, which provides a detection accuracy of about 0.89. Also, the analysis of the results of the experiments showed the need to improve the mathematical apparatus, which is used to calculate the mask detection indicators.
Źródło:
International Journal of Electronics and Telecommunications; 2023, 69, 1; 41--46
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Proposed Merging Methods of Digital Elevation Model Based on Artificial Neural Network and Interpolation Techniques for Improved Accuracy
Autorzy:
Alemam, Mustafa K.
Yong, Bin
Sani-Mohammed, Abubakar
Powiązania:
https://bibliotekanauki.pl/articles/27314479.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Centrum Badań Kosmicznych PAN
Tematy:
digital elevation model
GIS
artificial neural network
interpolation methods
SRTM
Opis:
The digital elevation model (DEM) is one of the most critical sources of terrain elevations, which are essential in various geoscience applications. Most of these applications need precise elevations, which are available at a high cost. Thus, sources like the Shuttle Radar Topography Mission (SRTM) DEM are frequently accessible to all users but with low accuracy. Consequently, many studies have tried to improve the accuracy of DEMs acquired from these free sources. Importantly, using the SRTM DEM is not recommended for an area that partly contains high-accuracy data. Thus, there is a need for a merging technique to produce a merged DEM of the whole area with improved accuracy. In recent years, advancements in geographic information systems (GIS) have improved data analysis by providing tools for applying merging techniques (like the minimum, maximum, last, first, mean, and blend (conventional methods)) to improve DEMs. In this article, DEM merging methods based on artificial neural network (ANN) and interpolation techniques are proposed. The methods are compared with other existing methods in commercial GIS software. The kriging, inverse distance weighted (IDW), and spline interpolation methods were considered for this investigation. The essential step for achieving the merging stage is the correction surface generation, which is used for modifying the SRTM DEM. Moreover, two cases were taken into consideration, i.e., the zeros border and the H border. The findings show that the proposed DEM merging methods (PDMMs) improved the accuracy of the SRTM DEM more than the conventional methods (CDMMs). The findings further show that the PDMMs of the H border achieved higher accuracy than the PDMMs of the zeros border, while kriging outperformed the other interpolation methods in both cases. The ANN outperformed all methods with the highest accuracy. Its improvements in the zeros and H border respectively reached 22.38% and 75.73% in elevation, 34.67% and 54.83% in the slope, and 40.28% and 52.22% in the aspect. Therefore, this approach would be cost-effective, especially in critical engineering projects.
Źródło:
Artificial Satellites. Journal of Planetary Geodesy; 2023, 58, 3; 122--170
2083-6104
Pojawia się w:
Artificial Satellites. Journal of Planetary Geodesy
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Applications of generative models with a latent observation subspace in vibrodiagnostics
Autorzy:
Puchalski, Andrzej
Komorska, Iwona
Powiązania:
https://bibliotekanauki.pl/articles/27313835.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
Tematy:
vibration signal
deep neural network
generative adversarial network
GAN model
synthetic subspace
sygnał wibracyjny
głęboka sieć neuronowa
GAN
wibrodiagnostyka
Opis:
The vibration signal is one of the most essential diagnostic signals, the analysis of which allows for determining the dynamic state of the monitored machine set. In the era of cyber-physical industrial systems, making diagnostic decisions involves the study of large databases from previous registers and data downloaded from machines in real-time. However, the recorded signals mainly concern the operational status of the monitored object. Insufficient training data regarding failure states hinders the operation of classification algorithms. Progress in machine learning has created a new avenue for the advancement of diagnostic methods based on models. These methods now have the capability to produce signals through random sampling from a hidden space or generate fresh instances of input data from noise. The article suggests the use of a Generative Adversarial Network (GAN) model as a tool to create synthetic measurement observations for vibration monitoring. The effectiveness of the synthetic data generation algorithm was verified on the example of the vibration signal recorded during tests of the drive system of a motor vehicle.
Źródło:
Diagnostyka; 2023, 24, 4; art. no. 2023413
1641-6414
2449-5220
Pojawia się w:
Diagnostyka
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Development of an Information Security System Based on Modeling Distributed Computer Network Vulnerability Indicators of an Informatization Object
Autorzy:
Lakhno, Valerii
Alimseitova, Zhuldyz
Kalaman, Yerbolat
Kryvoruchko, Olena
Desiatko, Alona
Kaminskyi, Serhii
Powiązania:
https://bibliotekanauki.pl/articles/27311974.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
information security
informatization object
distributed computing network
mathematical model
vulnerability coefficient
virtualization
IDS
SIEM
Opis:
A methodology for development for distributed computer network (DCN) information security system (IS) for an informatization object (OBI) was proposed. It was proposed to use mathematical modeling at the first stage of the methodology. In particular, a mathematical model was presented based on the use of the apparatus of probability theory to calculate the vulnerability coefficient. This coefficient allows one to assess the level of information security of the OBI network. Criteria for assessing the acceptable and critical level of risks for information security were proposed as well. At the second stage of the methodology development of the IS DCN system, methods of simulation and virtualization of the components of the IS DCN were used. In the course of experimental studies, a model of a protected DCN has been built. In the experimental model, network devices and DCN IS components were emulated on virtual machines (VMs). The DCN resources were reproduced using the Proxmox VE virtualization system. IPS Suricata was deployed on RCS hosts running PVE. Splunk was used as SIEM. It has been shown that the proposed methodology for the formation of the IS system for DCN and the model of the vulnerability coefficient makes it possible to obtain a quantitative assessment of the levels of vulnerability of DCN OBI.
Źródło:
International Journal of Electronics and Telecommunications; 2023, 69, 3; 475--483
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Effect of ship neural domain shape on safe and optimal trajectory
Autorzy:
Lisowski, J.
Powiązania:
https://bibliotekanauki.pl/articles/24201475.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
artificial neural network model
method for optimization
dynamic programming method
ship safety domain
safe ship control
path planning
multi-object decision model
computer simulation
Opis:
This article presents the task of safely guiding a ship, taking into account the movement of many other marine units. An optimally neural modified algorithm for determining a safe trajectory is presented. The possible shapes of the domains assigned to other ships as traffic restrictions for the particular ship were subjected to a detailed analysis. The codes for the computer program Neuro-Constraints for generating these domains are presented. The results of the simulation tests of the algorithm for a navigational situation are presented. The safe trajectories of the ship were compared at different distances, changing the sailing conditions and ship sizes.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2023, 17, 1; 185--191
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fault location of distribution network with distributed generation based on Karrenbauer transform and support vector machine regression
Autorzy:
Wang, Siming
Zhao, Kaikai
Powiązania:
https://bibliotekanauki.pl/articles/24202729.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
distributed generation
distribution network fault location
fault type
Karrenbauer transform
agent prediction model
SVR
support vector regression
Opis:
As the capacity and scale of distribution networks continue to expand, and distributed generation technology is increasingly mature, the traditional fault location is no longer applicable to an active distribution network and "two-way" power flow structure. In this paper, a fault location method based on Karrenbauer transform and support vector machine regression (SVR) is proposed. Firstly, according to the influence of Karrenbauer transformation on phase angle difference before and after section fault in a low-voltage active distribution network, the fault regions and types are inferred preliminarily. Then, in the feature extraction stage, combined with the characteristics of distribution network fault mechanism, the fault feature sample set is established by using the phase angle difference of the Karrenbauer current. Finally, the fault category prediction model based on SVR was established to solve the problem of a single-phase mode transformation modulus and the indistinct identification of two-phase short circuits, then more accurate fault segments and categories were obtained. The proposed fault location method is simulated and verified by building a distribution network system model. The results show that compared with other methods in the field of fault detection, the fault location accuracy of the proposed method can reach 98.56%, which can enhance the robustness of rapid fault location.
Źródło:
Archives of Electrical Engineering; 2023, 72, 2; 461--481
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Network of trust relationships in the remote work model
Autorzy:
Wawrzynek, Łukasz
Powiązania:
https://bibliotekanauki.pl/articles/27313421.pdf
Data publikacji:
2023
Wydawca:
Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
Tematy:
social network analysis
trust networks
work model
analiza sieci społecznościowych
sieci zaufania
model pracy
Opis:
Purpose: The article aimed to identify differences in the density of the trust network of team members in different work models (on-site, hybrid, and remote) and to identify opportunities for building knowledge and innovation in such work models based on the trust there. The method of experiment and a social networks analysis (SNA) was used to achieve the goal. Design/methodology/approach: The research is based on an experiment as part of a strategic business simulation game. The participants of the investigation are MBA students. The variable in the experiment is the work model. In these three different situations, relationships developed in teams are identified. Based on the identified relationships, visualizations of the trust network were built. Findings: The research confirmed that the hybrid and remote work models minimize the number of trust ties between team members. The network of trust based on the identified relationships is less dense. The decline in confidence leads to the conclusion that a company's innovation and ability to generate new knowledge are now under threat based only on group resources. Research limitations/implications: Research is based on an experiment. The group subjected to the investigation is MBA students. The limited duration of the experiment may limit the formation of networks of trust (based on long-term, deep relationships). See also a summary. Practical implications: The results indicate apparent differences in the density of trust relations between the organization's participants in the three analyzed work models. This points directly to the need to adjust tools supporting the development of innovation and knowledge creation for remote work models, different from those known from traditional (on-site) work models. Originality/value: The study shows that trust relationships, e are more challenging to achieve in remote working conditions than in traditional work models. It gives managers guidelines on what tools (such as SNA) they can use to identify relationships between people in new work models.
Źródło:
Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska; 2023, 169; 691--705
1641-3466
Pojawia się w:
Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimising pedestrian flow in a topological network using various pairwise speed-density models
Autorzy:
Khalid, Ruzelan
Nawawi, Mohd Kamal Mohd
Ishak, Nurhanis
Baten, Md Azizul
Powiązania:
https://bibliotekanauki.pl/articles/29127975.pdf
Data publikacji:
2023
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
topological network
speed-density model
optimal arrival rate
network flow model
pedestrian flow
Opis:
A speed-density model can be utilised to efficiently flow pedestrians in a network. However, how each model measures and optimises the performance of the network is rarely reported. Thus, this paper analyses and optimises the flow in a topological network using various speed-density models. Each model was first used to obtain the optimal arrival rates to all individual networks. The optimal value of each network was then set as a flow constraint in a network flow model. The network flow model was solved to find the optimal arrival rates to the source networks. The optimal values were then used to measure their effects on the performance of each available network. The performance results of the model were then compared with that of other speed-density models. The analysis of the results can help decision-makers understand how arrival rates propagate through traffic and determine the level of the network throughputs.
Źródło:
Operations Research and Decisions; 2023, 33, 4; 53--69
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Photovoltaic power prediction based on improved grey wolf algorithm optimized back propagation
Autorzy:
He, Ping
Dong, Jie
Wu, Xiaopeng
Yun, Lei
Yang, Hua
Powiązania:
https://bibliotekanauki.pl/articles/27309934.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
BP neural network
photovoltaic power generation
PSO–GWO model
PSO–GWO–BP prediction model
particle swarm optimization
gray wolf optimization
back propagation
standard grey wolf algorithm
Opis:
At present, the back-propagation (BP) network algorithm widely used in the short-term output prediction of photovoltaic power stations has the disadvantage of ignoring meteorological factors and weather conditions in the input. The existing traditional BP prediction model lacks a variety of numerical optimization algorithms, such that the prediction error is large. The back-propagation (BP) neural network is easy to fall into local optimization thus reducing the prediction accuracy in photovoltaic power prediction. In order to solve this problem, an improved grey wolf optimization (GWO) algorithm is proposed to optimize the photovoltaic power prediction model of the BP neural network. So, an improved grey wolf optimization algorithm optimized BP neural network for a photovoltaic (PV) power prediction model is proposed. Dynamic weight strategy, tent mapping and particle swarm optimization (PSO) are introduced in the standard grey wolf optimization (GWO) to construct the PSO–GWO model. The relative error of the PSO–GWO–BP model predicted data is less than that of the BP model predicted data. The average relative error of PSO–GWO–BP and GWO–BP models is smaller, the average relative error of PSO–GWO–BP model is the smallest, and the prediction stability of the PSO–GWO–BP model is the best. The model stability and prediction accuracy of PSO–GWO–BP are better than those of GWO–BP and BP.
Źródło:
Archives of Electrical Engineering; 2023, 72, 3; 613--628
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The Business Model of Industrial Networks in the Context of the Industry 4.0 Environment
Autorzy:
Grabowska, Sandra
Saniuk, Sebastian
Powiązania:
https://bibliotekanauki.pl/articles/27324208.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
industrial network
business model
industry 4.0
small and medium enterprises
personalization
Opis:
The article presents a business model based on an industrial network of companies capable of producing personalized products in an Industry 4.0 environment. Based on research conducted in Poland, in manufacturing companies, the critical problems associated with the implementation of Industry 4.0 technologies and the expected benefits associated with their implementation are addressed. The model’s task is to integrate a customer expecting personalized production with a network of companies with the appropriate production resources. The original achievement is the integration of the customer and the manufacturer around an e-business platform, which allows the rapid prototyping of a network of SME companies capable of realizing personalized production. The proposed model describes the architecture of enterprise cooperation under the conditions of implementing the Industry 4.0 concept and is dedicated to the SME sector. The model provides a basis for building prototypes of e-business platforms of small and medium-sized enterprises.
Źródło:
Management and Production Engineering Review; 2023, 14, 4; 41--47
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Small Wind Turbine Output Model for Spatially Constrained Remote Island Micro-Grids
Autorzy:
Žigman, D.
Meštrović, K.
Tomiša, T.
Powiązania:
https://bibliotekanauki.pl/articles/2172468.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
wind turbine
small wind turbine
decision tree model
artificial neural network model
random forest model
micro-grids
spatially constrained remote Island micro-grids
remote Island micro-grid
Opis:
Modelling operation of the power supply system for remote island communities is essential for its operation, as well as a survival of a modern society settled in challenging conditions. Micro-grid emerges as a proper solution for a sustainable development of a spatially constrained remote island community, while at the same time reflecting the power requirements of similar maritime subjects, such as large vessels and fleets. Here we present research results in predictive modelling the output of a small wind turbine, as a component of a remote island micro-grid. Based on a month-long experimental data and the machine learning-based predictive model development approach, three candidate models of a small wind turbine output were developed, and assessed on their performance based on an independent set of experimental data. The Random Forest Model out performed competitors (Decision Tree Model and Artificial Neural Network Model), emerging as a candidate methodology for the all-year predictive model development, as a later component of the over-all remote island micro-grid model.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2022, 16, 1; 143--146
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application perspective of digitalneural networks in the context of marine technologies
Autorzy:
Konon, V.
Konon, N.
Powiązania:
https://bibliotekanauki.pl/articles/24201415.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
marine technology
multi-layer perceptron
neural networks
digital neural networks
maritime industry
MLP algorithm
3D model
Artificial Neural Network
Opis:
This study is focused on the issue of digital neural networks’ implementation in the context of maritime industry. Various algorithms of such networks in the terms of the marine technologies have been reviewed in the current study in order to evaluate the effectiveness of the methodology and to propose a new concept of an artificial neural network’s application in this way. Fire-detection system simulation based on the thermal imagers’ data input had been developed to assess the efficiency of the concept suggested with a multi-layer perceptron (MLP) algorithm integrated into the designed 3d-model.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2022, 16, 4; 743--747
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Are Polish banks stable? A systemic risk analysis
Czy polskie banki są stabilne? Analiza ryzyka systemowego
Autorzy:
Misztal, P.
Łupiński, M.
Powiązania:
https://bibliotekanauki.pl/articles/2082365.pdf
Data publikacji:
2022
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
Tematy:
financial stability
systemic risk
network model
banking system
stabilność finansowa
ryzyko systemowe
model sieci
Opis:
The financial crisis that began in 2007 pointed out deficiencies in policy-makers’ responses to systemic risk. It turned out that not only individual bank insolvencies but also spillovers from negative externalities among entities can cause serious threats to the financial sector. During the last 10 years, many international and national initiatives were taken to strengthen the soundness of the financial system, introducing a macroprudential perspective to financial supervision. However, the recent COVID-19 pandemic resulted in a serious negative shock for many economies and their financial sectors. In this paper, using the network model we try to analyse how these recent unexpected developments affected the Polish banking sector with systemic risk. To analyse Polish bank stability we developed a formal stress-testing framework based on the network model that allowed systemic risk identification, modelling and measurement. We tried to integrate analysis of time and the cross-sectional nature of systemic risk.
Kryzys finansowy 2007+ ujawnił braki w reakcji decydentów politycznych na ryzyko systemowe. Okazało się, że nie tylko upadki poszczególnych banków, ale także negatywne efekty zewnętrzne wśród podmiotów mogą spowodować poważne zagrożenie dla sektora finansowego. W ciągu ostatnich 10 lat podjęto wiele międzynarodowych i krajowych inicjatyw mających na celu wzmocnienie stabilności systemu finansowego, wprowadzając perspektywę makroostrożnościową do nadzoru finansowego. Jednak ostatnie pandemie COVID19 okazały się poważnym negatywnym szokiem dla wielu gospodarek i ich sektorów finansowych. W niniejszym artykule, wykorzystując model sieciowy, staramy się przeanalizować, w jaki sposób te nieoczekiwane wydarzenia wpłynęły na polski sektor bankowy z ryzykiem systemowym. W celu analizy stabilności polskich banków opracowaliśmy formalne ramy testów warunków skrajnych oparte na modelu sieciowym, które umożliwiły identyfikację, modelowanie i pomiar ryzyka systemowego. Staraliśmy się zintegrować analizę czasu i przekrojowego charakteru ryzyka systemowego.
Źródło:
Zeszyty Naukowe Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie. Polityki Europejskie, Finanse i Marketing; 2022, 27[76]; 68-79
2081-3430
Pojawia się w:
Zeszyty Naukowe Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie. Polityki Europejskie, Finanse i Marketing
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Artificial neural network for solving the inverse kinematic model of a spatial and planar variable curvature continuum robot
Autorzy:
Ghoul, Abdelhamid
Kara, Kamel
Djeffal, Selman
Benrabah, Mahomed
Hadjili, Mohamed Laid
Powiązania:
https://bibliotekanauki.pl/articles/27309873.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
continuum robots
inverse kinematic model
artificial neural network
roboty kontinuum
odwrotny model kinematyczny
sztuczna sieć neuronowa
Opis:
In this paper, neural networks are presented to solve the inverse kinematic models of continuum robots. Firstly, the forward kinematic models are calculated for variable curvature continuum robots. Then, the forward kinematic models are implemented in the neural networks which present the position of the continuum robot’s end effector. After that, the inverse kinematic models are solved through neural networks without setting up any constraints. In the same context, to validate the utility of the developed neural networks, various types of trajectories are proposed to be followed by continuum robots. It is found that the developed neural networks are powerful tool to deal with the high complexity of the non-linear equations, in particular when it comes to solving the inverse kinematics model of variable curvature continuum robots. To have a closer look at the efficiency of the developed neural network models during the follow up of the proposed trajectories, 3D simulation examples through Matlab have been carried out with different configurations. It is noteworthy to say that the developed models are a needed tool for real time application since it does not depend on the complexity of the continuum robots' inverse kinematic models.
Źródło:
Archive of Mechanical Engineering; 2022, LXIX, 4; 595--613
0004-0738
Pojawia się w:
Archive of Mechanical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Calibration and validation of a macroscopic traffic flow model based on platoon dispersion and queue propagation
Autorzy:
Storani, Facundo
di Pace, Roberta
de Luca, Stefano
Memoli, Silvio
Powiązania:
https://bibliotekanauki.pl/articles/2173484.pdf
Data publikacji:
2022
Wydawca:
Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
Tematy:
network signal setting design
cell transmission model
platoon
dispersion model
calibration
validation
projekt ustawienia sygnału sieciowego
model transmisji komórki
pluton
model rozproszenia
kalibracja
walidacja
Opis:
This paper proposes a preliminary calibration and validation of a macroscopic traffic flow model for signalised junctions. In fact, on the network signal setting design problem, a reliable modelling approach must be adopted to acknowledge the traffic flow effects, considering two phenomena: queue dispersion and spillback. The proposed model is an extension of the space-time discrete Cell Transmission Model (CTM), which can simulate dispersion and horizontal queue. This preliminary calibration and validation use real-world data collected on an arterial of the city of Salerno (south of Italy). Results showed that the estimated parameters are consistent with the literature.
Źródło:
Zeszyty Naukowe. Transport / Politechnika Śląska; 2022, 114; 155--167
0209-3324
2450-1549
Pojawia się w:
Zeszyty Naukowe. Transport / Politechnika Śląska
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-15 z 233

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