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  • Open Access

    ARTICLE

    Application of Deep Learning to Production Forecasting in Intelligent Agricultural Product Supply Chain

    Xiao Ya Ma1,2,*, Jin Tong1,2, Fei Jiang3, Min Xu4, Li Mei Sun1, Qiu Yan Chen1

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6145-6159, 2023, DOI:10.32604/cmc.2023.034833

    Abstract Production prediction is an important factor influencing the realization of an intelligent agricultural supply chain. In an Internet of Things (IoT) environment, accurate yield prediction is one of the prerequisites for achieving an efficient response in an intelligent agricultural supply chain. As an example, this study applied a conventional prediction method and deep learning prediction model to predict the yield of a characteristic regional fruit (the Shatian pomelo) in a comparative study. The root means square error (RMSE) values of regression analysis, exponential smoothing, grey prediction, grey neural network, support vector regression (SVR), and long short-term memory (LSTM) neural network… More >

  • Open Access

    ARTICLE

    Fuzzy MCDM for Improving the Performance of Agricultural Supply Chain

    Le Thi Diem My1, Chia-Nan Wang1, Nguyen Van Thanh2,*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4003-4015, 2022, DOI:10.32604/cmc.2022.030209

    Abstract Fertilizer industry in Vietnam and globally have entered the saturation phase. With the growth rate slowing down, this poses challenges for the development impetus of the fertilizer industry in the next period. In fact, over the past few decades, Vietnam’s crop industry has abused excessive investment in chemical fertilizers, with organic fertilizers are rarely used or not at all, limiting crop productivity, increasing pests and diseases. To develop sustainable agriculture, Vietnam’s crop industry must limit the use of chemical fertilizers, increase the use of environmentally friendly organic and natural mineral fertilizers to produce clean agricultural products which is safe. Therefore,… More >

  • Open Access

    ARTICLE

    Agricultural Supply Chain Risks Evaluation with Spherical Fuzzy Analytic Hierarchy Process

    Phi-Hung Nguyen*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4211-4229, 2022, DOI:10.32604/cmc.2022.030115

    Abstract The outbreak of the COVID-19 pandemic has impacted the development of the global economy. As most developing and third world countries are heavily dependent on agriculture and agricultural imports, the agricultural supply chains (ASC) in all these countries are exposed to unprecedented risks following COVID-19. Therefore, it is vital to investigate the impact of risks and create resilient ASC organizations. In this study, critical risks associated with ASC were assessed using a novel Analytical Hierarchy Process based on spherical fuzzy sets (SF-AHP). The findings indicated that depending on the scope and scale of the organization, supply risks, demand risks, financial… More >

  • Open Access

    ARTICLE

    Optimization Agricultural Supply Chain: A Case Study of Fertilizer Supplier Selection

    Nguyen Van Thanh1, Nguyen Thi Kim Lan2,*, Syed Tam Husain1, Nguyen Hoang Hai1, Nguyen Viet Tinh1

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 4057-4068, 2022, DOI:10.32604/cmc.2022.026587

    Abstract The 21st century is associated with the Industrial Revolution 4.0 and the organic agriculture trend, making the utilization of high-quality fertilizers, abundant nutritional content, economical, and no affect to environment pollution. According to the new concept, clean agricultural production and organic agricultural products are not allowed to excessively use synthetic chemicals such as chemical fertilizers, and plant protection drugs, but priority is to use manure, organic fertilizers, and natural mineral fertilizers. Fertilizer must meet the balanced nutritional requirements of crops, maintain, and improve the fertility of the ground, protect the surrounding ecosystem, and leave harmful effects in agricultural products, products… More >

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