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  • Open Access

    ARTICLE

    Seasonal Short-Term Load Forecasting for Power Systems Based on Modal Decomposition and Feature-Fusion Multi-Algorithm Hybrid Neural Network Model

    Jiachang Liu1,*, Zhengwei Huang2, Junfeng Xiang1, Lu Liu1, Manlin Hu1

    Energy Engineering, Vol.121, No.11, pp. 3461-3486, 2024, DOI:10.32604/ee.2024.054514 - 21 October 2024

    Abstract To enhance the refinement of load decomposition in power systems and fully leverage seasonal change information to further improve prediction performance, this paper proposes a seasonal short-term load combination prediction model based on modal decomposition and a feature-fusion multi-algorithm hybrid neural network model. Specifically, the characteristics of load components are analyzed for different seasons, and the corresponding models are established. First, the improved complete ensemble empirical modal decomposition with adaptive noise (ICEEMDAN) method is employed to decompose the system load for all four seasons, and the new sequence is obtained through reconstruction based on the… More >

  • Open Access

    ARTICLE

    Changes in Leaf Stomatal Properties in Rice with the Growing Season

    Jiana Chen1,2, Fangbo Cao1,2, Min Huang1,2,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.4, pp. 807-817, 2024, DOI:10.32604/phyton.2024.048299 - 29 April 2024

    Abstract Transplanting rice varieties grown in different seasons can lead to different yields due to different dry matter production. Early-season rice varieties transplanted in the late season can obtain high yields with short-growth duration and higher yields driven by higher dry matter production. To make clear the variations in dry matter production across seasons, four early-season rice varieties were chosen for late-season transplantation. The grain yield, dry matter accumulation, leaf photosynthetic, and leaf stomatal properties were studied. It was observed that the average yields of these four varieties in the late season were 33% greater, despite… More >

  • Open Access

    ARTICLE

    Research on Scheduling Strategy of Flexible Interconnection Distribution Network Considering Distributed Photovoltaic and Hydrogen Energy Storage

    Yang Li1,2, Jianjun Zhao2, Xiaolong Yang2, He Wang1,*, Yuyan Wang1

    Energy Engineering, Vol.121, No.5, pp. 1263-1289, 2024, DOI:10.32604/ee.2024.046784 - 30 April 2024

    Abstract Distributed photovoltaic (PV) is one of the important power sources for building a new power system with new energy as the main body. The rapid development of distributed PV has brought new challenges to the operation of distribution networks. In order to improve the absorption ability of large-scale distributed PV access to the distribution network, the AC/DC hybrid distribution network is constructed based on flexible interconnection technology, and a coordinated scheduling strategy model of hydrogen energy storage (HS) and distributed PV is established. Firstly, the mathematical model of distributed PV and HS system is established,… More >

  • Open Access

    ARTICLE

    Responses of Wheat Production, Quality, and Soil Profile Properties to Biochar Applied at Different Seasons in a Rice-Wheat Rotation

    Lipei Chen, Rilie Deng, Xuewen Li, Min Yu, Hongdong Xiao*

    Phyton-International Journal of Experimental Botany, Vol.92, No.12, pp. 3359-3370, 2023, DOI:10.32604/phyton.2023.046877 - 28 December 2023

    Abstract

    In the rice-wheat rotation system, biochar (BC) can be applied at the initiation of the rice or wheat season. Here, we compared the effects of BC that were applied at two different crop seasons on wheat production, quality, and soil profile properties in a rice-wheat rotation system with nitrogen (N) fertilizer applied at 280 kg/ha rate. Results showed that both wheat grain production and N recovery use efficiency were influenced by BC applied at two crop seasons. Biochar application did not affect the total non-essential amino-acid, but when applied during wheat season, BC significantly (p

    More >

  • Open Access

    ARTICLE

    Inversion of Water Quality TN-TP Values Based on Hyperspectral Features and Model Validation

    Yaping Luo1, Na Guo1,*, Dong Liu2, Shuming Peng3, Xinchen Wang4, Jie Wu3

    Revue Internationale de Géomatique, Vol.32, pp. 39-52, 2023, DOI:10.32604/RIG.2023.046014 - 20 December 2023

    Abstract Using hyperspectral data collected in January and June 2022 from the Sha River, the concentrations of total nitrogen (TN) and total phosphorus (TP) were estimated using the differential method. The results indicate that the optimal bands for estimation vary monthly due to temperature fluctuations. In the TN model, the power function model at 586 nm in January exhibited the strongest fit, yielding a fit coefficient (R2) of 0.95 and F-value of 164.57 at a significance level (p) of less than 0.01. Conversely, the exponential model at 477 nm in June provided the best fit, with R2 = More > Graphic Abstract

    Inversion of Water Quality TN-TP Values Based on Hyperspectral Features and Model Validation

  • Open Access

    ARTICLE

    Short-Term Wind Power Prediction Based on ICEEMDAN-SE-LSTM Neural Network Model with Classifying Seasonal

    Shumin Sun1, Peng Yu1, Jiawei Xing1, Yan Cheng1, Song Yang1, Qian Ai2,*

    Energy Engineering, Vol.120, No.12, pp. 2761-2782, 2023, DOI:10.32604/ee.2023.042635 - 29 November 2023

    Abstract Wind power prediction is very important for the economic dispatching of power systems containing wind power. In this work, a novel short-term wind power prediction method based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and (long short-term memory) LSTM neural network is proposed and studied. First, the original data is prepossessed including removing outliers and filling in the gaps. Then, the random forest algorithm is used to sort the importance of each meteorological factor and determine the input climate characteristics of the forecast model. In addition, this study conducts seasonal classification… More >

  • Open Access

    ARTICLE

    Investigation of Particle Breakdown in the Production of Composite Magnesium Chloride and Zeolite Based Thermochemical Energy Storage Materials

    Louis F. Marie*, Karina Sałek, Tadhg S. O’Donovan

    Energy Engineering, Vol.120, No.10, pp. 2193-2209, 2023, DOI:10.32604/ee.2023.043075 - 28 September 2023

    Abstract Composite thermochemical energy storage (TCES) represents an exciting field of thermal energy storage which could address the issue of seasonal variance in renewable energy supply. However, there are open questions about their performance and the root cause of some observed phenomena. Some researchers have observed the breakdown of particles in their production phase, and in their use. This study seeks to investigate the underlying cause of this breakdown. SEM and EDX analysis have been conducted on MgCl2 impregnated 13X zeolite composites of differing diameters, as well as LiX zeolite. This was done in order to study… More > Graphic Abstract

    Investigation of Particle Breakdown in the Production of Composite Magnesium Chloride and Zeolite Based Thermochemical Energy Storage Materials

  • Open Access

    ARTICLE

    Price Prediction of Seasonal Items Using Time Series Analysis

    Ahmed Salah1,2, Mahmoud Bekhit3, Esraa Eldesouky4,5, Ahmed Ali4,6,*, Ahmed Fathalla7

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 445-460, 2023, DOI:10.32604/csse.2023.035254 - 20 January 2023

    Abstract The price prediction task is a well-studied problem due to its impact on the business domain. There are several research studies that have been conducted to predict the future price of items by capturing the patterns of price change, but there is very limited work to study the price prediction of seasonal goods (e.g., Christmas gifts). Seasonal items’ prices have different patterns than normal items; this can be linked to the offers and discounted prices of seasonal items. This lack of research studies motivates the current work to investigate the problem of seasonal items’ prices… More >

  • Open Access

    ARTICLE

    Holt-Winters Algorithm to Predict the Stock Value Using Recurrent Neural Network

    M. Mohan1,*, P. C. Kishore Raja2, P. Velmurugan3, A. Kulothungan4

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1151-1163, 2023, DOI:10.32604/iasc.2023.026255 - 06 June 2022

    Abstract Prediction of stock market value is highly risky because it is based on the concept of Time Series forecasting system that can be used for investments in a safe environment with minimized chances of loss. The proposed model uses a real time dataset of fifteen Stocks as input into the system and based on the data, predicts or forecast future stock prices of different companies belonging to different sectors. The dataset includes approximately fifteen companies from different sectors and forecasts their results based on which the user can decide whether to invest in the particular… More >

  • Open Access

    ARTICLE

    Sources of Nitrogen in Combination with Systems of Irrigation Influence the Productivity of Modern Rice (Oryza sativa L.) Cultivars during Dry Season in Sub-Tropical Environment

    Uttam Kumer Sarker1, Md. Romij Uddin1,*, Ahmed Khairul Hasan1, Md. Abdur Rahman Sarkar1, Md. Abdus Salam1, Md. Alamgir Hossain2, Eldessoky S. Dessoky3, Ismail A. Ismail3

    Phyton-International Journal of Experimental Botany, Vol.91, No.8, pp. 1687-1708, 2022, DOI:10.32604/phyton.2022.020645 - 14 April 2022

    Abstract In irrigated agricultural systems, nitrogen (N) and water are the vital resources for sustainability of the crop production in the modern era of climate change. The current study aimed to assess the impact of water and N management on the productivity of irrigated rice cultivars. In the context, a field observation was done at the research farm of Bangladesh Agricultural University, Mymensingh, during dry seasons in consecutive two years (2018–2019 and 2019–2020). The experiments were set up following split-plot design assigning water management in the main plots, nitrogen management in the sub-plots, and the cultivars… More >

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