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Search Results (24)
  • Open Access


    Fusing Supervised and Unsupervised Measures for Attribute Reduction

    Tianshun Xing, Jianjun Chen*, Taihua Xu, Yan Fan

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 561-581, 2023, DOI:10.32604/iasc.2023.037874

    Abstract It is well-known that attribute reduction is a crucial action of rough set. The significant characteristic of attribute reduction is that it can reduce the dimensions of data with clear semantic explanations. Normally, the learning performance of attributes in derived reduct is much more crucial. Since related measures of rough set dominate the whole process of identifying qualified attributes and deriving reduct, those measures may have a direct impact on the performance of selected attributes in reduct. However, most previous researches about attribute reduction take measures related to either supervised perspective or unsupervised perspective, which are insufficient to identify attributes… More >

  • Open Access


    Approximations by Ideal Minimal Structure with Chemical Application

    Rodyna A. Hosny1, Radwan Abu-Gdairi2, Mostafa K. El-Bably3,*

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3073-3085, 2023, DOI:10.32604/iasc.2023.034234

    Abstract The theory of rough set represents a non-statistical methodology for analyzing ambiguity and imprecise information. It can be characterized by two crisp sets, named the upper and lower approximations that are used to determine the boundary region and accurate measure of any subset. This article endeavors to achieve the best approximation and the highest accuracy degree by using the minimal structure approximation space via ideal . The novel approach (indicated by ) modifies the approximation space to diminish the boundary region and enhance the measure of accuracy. The suggested method is more accurate than Pawlak’s and EL-Sharkasy techniques. Via illustrated… More >

  • Open Access


    Mathematical Morphology View of Topological Rough Sets and Its Applications

    Ibrahim Noaman1, Abd El Fattah El Atik2, Tamer Medhat3,*, Manal E. Ali4

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6893-6908, 2023, DOI:10.32604/cmc.2023.033539

    Abstract This article focuses on the relationship between mathematical morphology operations and rough sets, mainly based on the context of image retrieval and the basic image correspondence problem. Mathematical morphological procedures and set approximations in rough set theory have some clear parallels. Numerous initiatives have been made to connect rough sets with mathematical morphology. Numerous significant publications have been written in this field. Others attempt to show a direct connection between mathematical morphology and rough sets through relations, a pair of dual operations, and neighborhood systems. Rough sets are used to suggest a strategy to approximate mathematical morphology within the general… More >

  • Open Access


    Attribute Reduction for Information Systems via Strength of Rules and Similarity Matrix

    Mohsen Eid1, Tamer Medhat2,*, Manal E. Ali3

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1531-1544, 2023, DOI:10.32604/csse.2023.031745

    Abstract An information system is a type of knowledge representation, and attribute reduction is crucial in big data, machine learning, data mining, and intelligent systems. There are several ways for solving attribute reduction problems, but they all require a common categorization. The selection of features in most scientific studies is a challenge for the researcher. When working with huge datasets, selecting all available attributes is not an option because it frequently complicates the study and decreases performance. On the other side, neglecting some attributes might jeopardize data accuracy. In this case, rough set theory provides a useful approach for identifying superfluous… More >

  • Open Access


    Game Theory-Based Dynamic Weighted Ensemble for Retinal Disease Classification

    Kanupriya Mittal*, V. Mary Anita Rajam

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1907-1921, 2023, DOI:10.32604/iasc.2023.029037

    Abstract An automated retinal disease detection system has long been in existence and it provides a safe, no-contact and cost-effective solution for detecting this disease. This paper presents a game theory-based dynamic weighted ensemble of a feature extraction-based machine learning model and a deep transfer learning model for automatic retinal disease detection. The feature extraction-based machine learning model uses Gaussian kernel-based fuzzy rough sets for reduction of features, and XGBoost classifier for the classification. The transfer learning model uses VGG16 or ResNet50 or Inception-ResNet-v2. A novel ensemble classifier based on the game theory approach is proposed for the fusion of the… More >

  • Open Access


    On Soft Pre-Rough Approximation Space with Applications in Decision Making

    M. El Sayed1,*, Wadia Faid Hassan Al-shameri1, M. A. El Safty2

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 865-879, 2022, DOI:10.32604/cmes.2022.020066

    Abstract A soft, rough set model is a distinctive mathematical model that can be used to relate a variety of real-life data. In the present work, we introduce new concepts of rough set based on soft pre-lower and soft pre-upper approximation space. These concepts are soft pre-rough equality, soft pre-rough inclusion, soft pre-rough belonging, soft predefinability, soft pre-internal lower, and soft pre-external lower. We study the properties of these concepts. Finally, we use the soft pre-rough approximation to illustrate the importance of our method in decision-making for Chikungunya medical illnesses. In reality, the impact factors of Chikungunya’s medical infection were determined.… More >

  • Open Access


    Rough Sets Hybridization with Mayfly Optimization for Dimensionality Reduction

    Ahmad Taher Azar1,2,*, Mustafa Samy Elgendy1, Mustafa Abdul Salam1,3, Khaled M. Fouad1,4

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1087-1108, 2022, DOI:10.32604/cmc.2022.028184

    Abstract Big data is a vast amount of structured and unstructured data that must be dealt with on a regular basis. Dimensionality reduction is the process of converting a huge set of data into data with tiny dimensions so that equal information may be expressed easily. These tactics are frequently utilized to improve classification or regression challenges while dealing with machine learning issues. To achieve dimensionality reduction for huge data sets, this paper offers a hybrid particle swarm optimization-rough set PSO-RS and Mayfly algorithm-rough set MA-RS. A novel hybrid strategy based on the Mayfly algorithm (MA) and the rough set (RS)… More >

  • Open Access


    Binary Representation of Polar Bear Algorithm for Feature Selection

    Amer Mirkhan1, Numan Çelebi2,*

    Computer Systems Science and Engineering, Vol.43, No.2, pp. 767-783, 2022, DOI:10.32604/csse.2022.023249

    Abstract In most of the scientific research feature selection is a challenge for researcher. Selecting all available features is not an option as it usually complicates the research and leads to performance drop when dealing with large datasets. On the other hand, ignoring some features can compromise the data accuracy. Here the rough set theory presents a good technique to identify the redundant features which can be dismissed without losing any valuable information, however, exploring all possible combinations of features will end with NP-hard problem. In this research we propose adopting a heuristic algorithm to solve this problem, Polar Bear Optimization… More >

  • Open Access


    Power Quality Assessment Based on Rough AHP and Extension Analysis

    Guofeng Liu*, Can Zhang, Zhengyi Zhu, Xuyan Wang

    Energy Engineering, Vol.119, No.3, pp. 929-946, 2022, DOI:10.32604/ee.2022.014816

    Abstract Due to the increasing power consumption of whole society and widely using of new non-linear and asymmetric electrical equipment, power quality assessment problem in the new period has attracted more and more attention. The mathematical essence of comprehensive assessment of power quality is a multi-attribute optimal decision-making problem. In order to solve the key problem of determining the indicator weight in the process of power quality assessment, a rough analytic hierarchy process (AHP) is proposed to aggregate the judgment opinions of multiple experts and eliminate the subjective effects of single expert judgment. Based on the advantage of extension analysis for… More >

  • Open Access


    Soft -Rough Set and Its Applications in Decision Making of Coronavirus

    M. A. El Safty1,*, Samirah Al Zahrani1, M. K. El-Bably2, M. El Sayed3

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 267-285, 2022, DOI:10.32604/cmc.2022.019345

    Abstract In this paper, we present a proposed method for generating a soft rough approximation as a modification and generalization of Zhaowen et al. approach. Comparisons were obtained between our approach and the previous study and also. Eventually, an application on Coronavirus (COVID-19) has been presented, illustrated using our proposed concept, and some influencing results for symptoms of Coronavirus patients have been deduced. Moreover, following these concepts, we construct an algorithm and apply it to a decision-making problem to demonstrate the applicability of our proposed approach. Finally, a proposed approach that competes with others has been obtained, as well as realistic… More >

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