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  • Open Access


    Learning Vector Quantization-Based Fuzzy Rules Oversampling Method

    Jiqiang Chen, Ranran Han, Dongqing Zhang, Litao Ma*

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 5067-5082, 2024, DOI:10.32604/cmc.2024.051494

    Abstract Imbalanced datasets are common in practical applications, and oversampling methods using fuzzy rules have been shown to enhance the classification performance of imbalanced data by taking into account the relationship between data attributes. However, the creation of fuzzy rules typically depends on expert knowledge, which may not fully leverage the label information in training data and may be subjective. To address this issue, a novel fuzzy rule oversampling approach is developed based on the learning vector quantization (LVQ) algorithm. In this method, the label information of the training data is utilized to determine the antecedent… More >

  • Open Access


    Fuzzy-HLSTM (Hierarchical Long Short-Term Memory) for Agricultural Based Information Mining

    Ahmed Abdu Alattab1,*, Mohammed Eid Ibrahim1, Reyazur Rashid Irshad1, Anwar Ali Yahya2, Amin A. Al-Awady3

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2397-2413, 2023, DOI:10.32604/cmc.2023.030924

    Abstract This research proposes a machine learning approach using fuzzy logic to build an information retrieval system for the next crop rotation. In case-based reasoning systems, case representation is critical, and thus, researchers have thoroughly investigated textual, attribute-value pair, and ontological representations. As big databases result in slow case retrieval, this research suggests a fast case retrieval strategy based on an associated representation, so that, cases are interrelated in both either similar or dissimilar cases. As soon as a new case is recorded, it is compared to prior data to find a relative match. The proposed More >

  • Open Access


    An Intelligent Medical Expert System Using Temporal Fuzzy Rules and Neural Classifier

    Praveen Talari1,*, A. Suresh2, M. G. Kavitha3

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 1053-1067, 2023, DOI:10.32604/iasc.2023.027024

    Abstract As per World Health Organization report which was released in the year of 2019, Diabetes claimed the lives of approximately 1.5 million individuals globally in 2019 and around 450 million people are affected by diabetes all over the world. Hence it is inferred that diabetes is rampant across the world with the majority of the world population being affected by it. Among the diabetics, it can be observed that a large number of people had failed to identify their disease in the initial stage itself and hence the disease level moved from Type-1 to Type-2.… More >

  • Open Access


    CNN and Fuzzy Rules Based Text Detection and Recognition from Natural Scenes

    T. Mithila1,*, R. Arunprakash2, A. Ramachandran3

    Computer Systems Science and Engineering, Vol.42, No.3, pp. 1165-1179, 2022, DOI:10.32604/csse.2022.023308

    Abstract In today’s real world, an important research part in image processing is scene text detection and recognition. Scene text can be in different languages, fonts, sizes, colours, orientations and structures. Moreover, the aspect ratios and layouts of a scene text may differ significantly. All these variations appear assignificant challenges for the detection and recognition algorithms that are considered for the text in natural scenes. In this paper, a new intelligent text detection and recognition method for detectingthe text from natural scenes and forrecognizing the text by applying the newly proposed Conditional Random Field-based fuzzy rules… More >

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