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    Wyświetlanie 1-10 z 10
    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continue to expand, and distributed generation technology is increasingly mature, the traditional fault location is no longer applicable to an active distribution network and "two-way" power flow structure.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:
    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:
    QIBMRMN: Design of a Q-Learning based Iterative sleep-scheduling & hybrid Bioinspired Multipath Routing model for Multimedia Networks
    Autorzy:
    Doorwar, Minaxi
    Malathi, P
    Powiązania:
    https://bibliotekanauki.pl/articles/27311958.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    multimedia
    network
    Q-learning
    GWO
    GA
    Adhoc
    QoS
    iterative
    process
    Opis:
    Multimedia networks utilize low-power scalar nodes to modify wakeup cycles of high-performance multimedia nodes, which assists in optimizing the power-toperformance ratios. A wide variety of machine learning models are proposed by researchers to perform this task, and most of them are either highly complex, or showcase low-levels of efficiency when applied to large-scale networks. To overcome these issues, this text proposes design of a Q-learning based iterative sleep-scheduling and fuses these schedules with an efficient hybrid bioinspired multipath routing model for largescale multimedia network sets. The proposed model initially uses an iterative Q-Learning technique that analyzes energy consumption patterns of nodes, and incrementally modifies their sleep schedules. These sleep schedules are used by scalar nodes to efficiently wakeup multimedia nodes during adhoc communication requests. These communication requests are processed by a combination of Grey Wolf Optimizer (GWO) & Genetic Algorithm (GA) models, which assist in the identification of optimal paths. These paths are estimated via combined analysis of temporal throughput & packet delivery performance, with node-to-node distance & residual energy metrics. The GWO Model uses instantaneous node & network parameters, while the GA Model analyzes temporal metrics in order to identify optimal routing paths. Both these path sets are fused together via the Q-Learning mechanism, which assists in Iterative Adhoc Path Correction (IAPC), thereby improving the energy efficiency, while reducing communication delay via multipath analysis. Due to a fusion of these models, the proposed Q-Learning based Iterative sleep-scheduling & hybrid Bioinspired Multipath Routing model for Multimedia Networks (QIBMRMN) is able to reduce communication delay by 2.6%, reduce energy consumed during these communications by 14.0%, while improving throughput by 19.6% & packet delivery performance by 8.3% when compared with standard multimedia routing techniques.
    Źródło:
    International Journal of Electronics and Telecommunications; 2023, 69, 4; 776--784
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    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:
    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:
    Novel Hybrid Model Investing in 5G Network Optimization Under Suzuki Fading Channel
    Autorzy:
    Abed, Muntadher Suhail
    Powiązania:
    https://bibliotekanauki.pl/articles/27311908.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    5G
    Suzuki Fading Channel
    polar code
    quality of service (QoS)
    rate matching
    Opis:
    Nowadays, the advancement and increased use of fifth-generation (5G) and sixth-generation (6G) systems have created a demand for more efficient and rapid transmission of information over wireless communication media. However, developing wireless communication systems that can meet these modern-day criteria for fast, reliable, and secure information exchange is a challenging task. To address this issue, this paper proposes a novel model for enhancing the 5G system. The proposed model utilizes polar code with rate matching and constitutional interleaving over the Suzuki fading channel. The combination of polar codes with rate matching and interleaving enables the communication system to achieve a lower error rate and better reliability over a Suzuki fading channel. Specifically, the polar code can correct a larger number of errors, while rate matching and interleaving can mitigate the effects of channel variations and reduce the probability of error bursts. These enhancements can lead to more robust and reliable communication in wireless networks.
    Źródło:
    International Journal of Electronics and Telecommunications; 2023, 69, 3; 553--558
    2300-1933
    Pojawia się w:
    International Journal of Electronics and Telecommunications
    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:
    Development of a Sound Quality Evaluation Model Based on an Optimal Analytic Wavelet Transform and an Artificial Neural Network
    Autorzy:
    Pourseiedrezaei, Mehdi
    Loghmani, Ali
    Keshmiri, Mehdi
    Powiązania:
    https://bibliotekanauki.pl/articles/1953511.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    analytic wavelet transform
    AWT
    sound quality evaluation
    SQE
    psychoacoustic metrics
    back propagation neural network
    BPNN
    Opis:
    The purpose of this study was to develop a sound quality model for real time active sound quality control systems. The model is based on an optimal analytic wavelet transform (OAWT) used along with a back propagation neural network (BPNN) in which the initial weights and thresholds are determined by particle swarm optimisation (PSO). In the model the input signal is decomposed into 24 critical bands to extract a feature matrix, based on energy, mean, and standard deviation indices of the sub signal scalogram obtained by OAWT. The feature matrix is fed into the neural network input to determine the psychoacoustic parameters used for sound quality evaluation. The results of the study show that the present model is in good agreement with psychoacoustic models of sound quality metrics and enables evaluation of the quality of sound at a lower computational cost than the existing models.
    Źródło:
    Archives of Acoustics; 2021, 46, 1; 55-65
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    VMD and CNN-Based Classification Model for Infrasound Signal
    Autorzy:
    Lu, Quanbo
    Li, Mei
    Powiązania:
    https://bibliotekanauki.pl/articles/31339812.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    infrasound signal
    variational mode decomposition
    convolutional neural network
    Fast Fourier Transform
    Opis:
    Infrasound signal classification is vital in geological hazard monitoring systems. The traditional classification approach extracts the features and classifies the infrasound events. However, due to the manual feature extraction, its classification performance is not satisfactory. To deal with this problem, this paper presents a classification model based on variational mode decomposition (VMD) and convolutional neural network (CNN). Firstly, the infrasound signal is processed by VMD to eliminate the noise. Then fast Fourier transform (FFT) is applied to convert the reconstructed signal into a frequency domain image. Finally, a CNN model is established to automatically extract the features and classify the infrasound signals. The experimental results show that the classification accuracy of the proposed classification model is higher than the other model by nearly 5%. Therefore, the proposed approach has excellent robustness under noisy environments and huge potential in geophysical monitoring.
    Źródło:
    Archives of Acoustics; 2023, 48, 3; 403-412
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A Study on the Impact of Lombard Effect on Recognition of Hindi Syllabic Units Using CNN Based Multimodal ASR Systems
    Autorzy:
    Uma Maheswari, Sadasivam
    Shahina, A.
    Rishickesh, Ramesh
    Nayeemulla Khan, A.
    Powiązania:
    https://bibliotekanauki.pl/articles/176415.pdf
    Data publikacji:
    2020
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    Lombard speech
    multimodal ASR
    throat microphone
    visual speech
    Convolutional Neural Network
    Hidden Markov Model
    late fusion
    intermediate fusion
    Opis:
    Research work on the design of robust multimodal speech recognition systems making use of acoustic, and visual cues, extracted using the relatively noise robust alternate speech sensors is gaining interest in recent times among the speech processing research fraternity. The primary objective of this work is to study the exclusive influence of Lombard effect on the automatic recognition of the confusable syllabic consonant-vowel units of Hindi language, as a step towards building robust multimodal ASR systems in adverse environments in the context of Indian languages which are syllabic in nature. The dataset for this work comprises the confusable 145 consonant-vowel (CV) syllabic units of Hindi language recorded simultaneously using three modalities that capture the acoustic and visual speech cues, namely normal acoustic microphone (NM), throat microphone (TM) and a camera that captures the associated lip movements. The Lombard effect is induced by feeding crowd noise into the speaker’s headphone while recording. Convolutional Neural Network (CNN) models are built to categorise the CV units based on their place of articulation (POA), manner of articulation (MOA), and vowels (under clean and Lombard conditions). For validation purpose, corresponding Hidden Markov Models (HMM) are also built and tested. Unimodal Automatic Speech Recognition (ASR) systems built using each of the three speech cues from Lombard speech show a loss in recognition of MOA and vowels while POA gets a boost in all the systems due to Lombard effect. Combining the three complimentary speech cues to build bimodal and trimodal ASR systems shows that the recognition loss due to Lombard effect for MOA and vowels reduces compared to the unimodal systems, while the POA recognition is still better due to Lombard effect. A bimodal system is proposed using only alternate acoustic and visual cues which gives a better discrimination of the place and manner of articulation than even standard ASR system. Among the multimodal ASR systems studied, the proposed trimodal system based on Lombard speech gives the best recognition accuracy of 98%, 95%, and 76% for the vowels, MOA and POA, respectively, with an average improvement of 36% over the unimodal ASR systems and 9% improvement over the bimodal ASR systems.
    Źródło:
    Archives of Acoustics; 2020, 45, 3; 419-431
    0137-5075
    Pojawia się w:
    Archives of Acoustics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-10 z 10

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