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    Wyświetlanie 1-4 z 4
    Tytuł:
    Load regulation application of university campus based on solar power generation forecasting
    Autorzy:
    Han, Guozheng
    Tan, Shujuan
    Zhang, Zihan
    Powiązania:
    https://bibliotekanauki.pl/articles/24202744.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    load regulation
    solar power generation forecast
    photovoltaic generation
    Opis:
    For a solar photovoltaic power system on a university campus, the electricity generated by the system meets the campus load, and the extra electricity is delivered to the grid. Generally, the price of the photovoltaic system is cheaper than that of the utility power system. The full use of solar electricity can reduce the electricity cost of the school. The deep belief network is used to predict solar photovoltaic generation and electricity load, and the gap is found. According to the gap, the power loads on the campus are adjusted to improve the utilization rate of solar power generation. Through the practical application of Changqing Campus of Qilu University of Technology in China, it is found that the utilization rate of solar photovoltaic power generation effectively improved from 91.24% in 2017 to 98.16% in 2019, and the annual electricity is saved by 68 610 yuan (in 2019).
    Źródło:
    Archives of Electrical Engineering; 2023, 72, 2; 429--441
    1427-4221
    2300-2506
    Pojawia się w:
    Archives of Electrical Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Research on path optimization for multimodal transportation of hazardous materials under uncertain demand
    Autorzy:
    Han, Wei
    Chai, Huo
    Zhang, Jianpeng
    Li, Yuanping
    Powiązania:
    https://bibliotekanauki.pl/articles/27311810.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    hazardous materials
    multimodal transport
    routing optimization
    fuzzy random numbers
    NSGA-II
    materiały niebezpieczne
    transport multimodalny
    optymalizacja tras
    Opis:
    In the process of long-distance and large-volume transportation of hazardous materials (HAZMAT), multimodal transportation plays a crucial role with its unique advantages. In order to effectively reduce the transportation risk and improve the reliability of transportation, it is particularly important to choose a suitable transportation plan for multimodal transport of HAZMAT. In this paper, we study the transportation of HAZMAT in multimodal transport networks. Considering the fluctuation in demand for HAZMAT during the actual transportation process, it is difficult for decision makers to obtain the accurate demand for HAZMAT orders in advance, leading to uncertainty in the final transportation plan. Therefore, in this paper, the uncertain demand of HAZMAT is set as a triangular fuzzy random number, and a multi-objective mixed integer linear programming model is established with the objective of minimizing the total risk exposure population and the total cost in the transportation process of HAZMAT. In order to facilitate the solution of the model, we combined the fuzzy random expected value method with the fuzzy random chance constraint method based on credibility measures to reconstruct the uncertain model clearly and equivalently, and designed a non-dominated sorting genetic algorithm (NSGA-Ⅱ) to obtain the Pareto boundary of the multi-objective optimization problem. Finally, we conducted a numerical example experiment to verify the rationality of the model proposed in this paper. The experimental results indicate that uncertain demand can affect the path decision-making of multimodal transportation of HAZMAT. In addition, the confidence level of fuzzy random opportunity constraints will have an impact on the risk and economic objectives of optimizing the multimodal transportation path of HAZMAT. When the confidence level is higher than 0.7, it will lead to a significant increase in transportation risks and costs. Through sensitivity analysis, it can provide useful decision-making references for relevant departments to formulate HAZMAT transportation plans.
    Źródło:
    Archives of Transport; 2023, 67, 3; 91--104
    0866-9546
    2300-8830
    Pojawia się w:
    Archives of Transport
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Anonymous traffic classification based on three-dimensional Markov image and deep learning
    Autorzy:
    Tang, Xin
    Li, Huanzhou
    Zhang, Jian
    Tang, Zhangguo
    Wang, Han
    Cai, Cheng
    Powiązania:
    https://bibliotekanauki.pl/articles/27311448.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    anonymous network
    traffic classification
    three-dimensional Markov image
    output self-attention
    deep learning
    sieć anonimowa
    klasyfikacja ruchu
    trójwymiarowy obraz Markowa
    samouwaga wyjściowa
    uczenie głębokie
    Opis:
    Illegal elements use the characteristics of an anonymous network hidden service mechanism to build a dark network and conduct various illegal activities, which brings a serious challenge to network security. The existing anonymous traffic classification methods suffer from cumbersome feature selection and difficult feature information extraction, resulting in low accuracy of classification. To solve this problem, a classification method based on three-dimensional Markov images and output self-attention convolutional neural network is proposed. This method first divides and cleans anonymous traffic data packets according to sessions, then converts the cleaned traffic data into three-dimensional Markov images according to the transition probability matrix of bytes, and finally inputs the images to the output self-attention convolution neural network to train the model and perform classification. The experimental results show that the classification accuracy and F1-score of the proposed method for Tor, I2P, Freenet, and ZeroNet can exceed 98.5%, and the average classification accuracy and F1-score for 8 kinds of user behaviors of each type of anonymous traffic can reach 93.7%. The proposed method significantly improves the classification effect of anonymous traffic compared with the existing methods.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 4; art. no. e145676
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Identification of a linear epitope in the capsid protein of goose astrovirus with monoclonal antibody
    Autorzy:
    Dai, G.
    Huang, X.
    Liu, Q.
    Li, Y.
    Zhang, L.
    Han, K.
    Yang, J.
    Liu, Y.
    Xue, F.
    Zhao, D.
    Powiązania:
    https://bibliotekanauki.pl/articles/16647377.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    epitope
    goose astrovirus
    capsid protein
    monoclonal antibody
    Opis:
    Goose astrovirus (GoAstV) is a novel avastrovirus that typically causes gosling gout and results in 2 to 20% mortality. GoAstV capsid protein is the sole structural protein, which is responsible for viral attachment, assembly, maturation as well as eliciting host antibodies. However, the epitopes within capsid protein have not been well studied. In this study, a monoclonal antibody, named 1D7, was generated against GoAstV capsid protein by hybridoma technology. Western blot results showed that this MAb could react with recombinant capsid protein expressed in E. coli. Also, it recognized the precursor of capsid protein, VP90 and VP70, in GoAstV-infected cells. Besides, excellent specificity of MAb 1D7 was further demonstrated in indirect immunofluorescence assay and immunohistochemical analysis. Epitope mapping results revealed that MAb 1D7 recognized the epitope 33QKVY 36 within Cap protein. Sequence alignment indicated that 33QKVY 36 is a conserved epitope among the isolates of goose astrovirus type 2 (GoAstV-2), suggesting the potential for its use in GoAstV-2 specific diagnostic assay. These findings may provide some insight into a function of the GoAstV capsid protein and further contribute to the development of diagnostic methods for GoAstV infection.
    Źródło:
    Polish Journal of Veterinary Sciences; 2022, 25, 4; 579-587
    1505-1773
    Pojawia się w:
    Polish Journal of Veterinary Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
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