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  • Open Access


    Automatic Crop Expert System Using Improved LSTM with Attention Block

    Shahbaz Sikandar1, Rabbia Mahum1, Suliman Aladhadh2,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2007-2025, 2023, DOI:10.32604/csse.2023.037723

    Abstract Agriculture plays an important role in the economy of any country. Approximately half of the population of developing countries is directly or indirectly connected to the agriculture field. Many farmers do not choose the right crop for cultivation depending on their soil type, crop type, and climatic requirements like rainfall. This wrong decision of crop selection directly affects the production of the crops which leads to yield and economic loss in the country. Many parameters should be observed such as soil characteristics, type of crop, and environmental factors for the cultivation of the right crop.… More >

  • Open Access


    Multimodal Machine Learning Based Crop Recommendation and Yield Prediction Model

    P. S. S. Gopi*, M. Karthikeyan

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 313-326, 2023, DOI:10.32604/iasc.2023.029756

    Abstract Agriculture plays a vital role in the Indian economy. Crop recommendation for a specific region is a tedious process as it can be affected by various variables such as soil type and climatic parameters. At the same time, crop yield prediction was based on several features like area, irrigation type, temperature, etc. The recent advancements of artificial intelligence (AI) and machine learning (ML) models pave the way to design effective crop recommendation and crop prediction models. In this view, this paper presents a novel Multimodal Machine Learning Based Crop Recommendation and Yield Prediction (MMML-CRYP) technique. More >

  • Open Access


    Prediction of Suitable Crops Using Stacked Scaling Conjugant Neural Classifier

    P. Nithya*, A. M. Kalpana

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3743-3755, 2023, DOI:10.32604/iasc.2023.030394

    Abstract Agriculture plays a vital role in economic development. The major problem faced by the farmers are the selection of suitable crops based on environmental conditions such as weather, soil nutrients, etc. The farmers were following ancestral patterns, which could sometimes lead to the wrong selection of crops. In this research work, the feature selection method is adopted to improve the performance of the classification. The most relevant features from the dataset are obtained using a Probabilistic Feature Selection (PFS) approach, and classification is done using a Neural Fuzzy Classifier (NFC). Scaling Conjugate Gradient (SCG) optimization More >

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