Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (5)
  • Open Access


    Multi-Attribute Couplings-Based Euclidean and Nominal Distances for Unlabeled Nominal Data

    Lei Gu*, Furong Zhang, Li Ma

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5911-5928, 2023, DOI:10.32604/cmc.2023.038127

    Abstract Learning unlabeled data is a significant challenge that needs to handle complicated relationships between nominal values and attributes. Increasingly, recent research on learning value relations within and between attributes has shown significant improvement in clustering and outlier detection, etc. However, typical existing work relies on learning pairwise value relations but weakens or overlooks the direct couplings between multiple attributes. This paper thus proposes two novel and flexible multi-attribute couplings-based distance (MCD) metrics, which learn the multi-attribute couplings and their strengths in nominal data based on information theories: self-information, entropy, and mutual information, for measuring both numerical and nominal distances. MCD… More >

  • Open Access


    A Spacecraft Equipment Layout Optimization Method for Diverse and Competitive Design

    Wei Cong, Yong Zhao*, Bingxiao Du*, Senlin Huo, Xianqi Chen

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 621-654, 2023, DOI:10.32604/cmes.2023.025143

    Abstract The spacecraft equipment layout optimization design (SELOD) problems with complicated performance constraints and diversity are studied in this paper. The previous literature uses the gradient-based algorithm to obtain optimized non-overlap layout schemes from randomly initialized cases effectively. However, these local optimal solutions are too difficult to jump out of their current relative geometry relationships, significantly limiting their further improvement in performance indicators. Therefore, considering the geometric diversity of layout schemes is put forward to alleviate this limitation. First, similarity measures, including modified cosine similarity and gaussian kernel function similarity, are introduced into the layout optimization process. Then the optimization produces… More >

  • Open Access


    Sentiment Analytics: Extraction of Challenging Influencing Factors from COVID-19 Pandemics

    Mahmoud Oglah Al Hasan Baniata*, Sohail Asghar

    Intelligent Automation & Soft Computing, Vol.30, No.3, pp. 821-836, 2021, DOI:10.32604/iasc.2021.018612

    Abstract The advancement in electronic devices and communication technologies in social media have introduced major changes in today’s communication and people have accepted such communicational habits at a rapid pace. The changes involve the way people started interacting with each other, and modern mean of discovering new groups of people, and individuals with similar mindsets, mutual interests, and ideas to share with. As far as the communities are concerned, there are so many social drives (such as “Say No to Plastic”) that need to be discussed on a certain platform for their promotion. Although, it’s quit is challenging, but with the… More >

  • Open Access


    P-Indeterminate Vector Similarity Measures of Orthopair Neutrosophic Number Sets and Their Decision-Making Method with Indeterminate Degrees

    Mailing Zhao1, Jun Ye1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1219-1230, 2021, DOI:10.32604/cmes.2021.016871

    Abstract In the complexity and indeterminacy of decision making (DM) environments, orthopair neutrosophic number set (ONNS) presented by Ye et al. can be described by the truth and falsity indeterminacy degrees. Then, ONNS demonstrates its advantages in the indeterminate information expression, aggregations, and DM problems with some indeterminate ranges. However, the existing research lacks some similarity measures between ONNSs. They are indispensable mathematical tools and play a crucial role in DM, pattern recognition, and clustering analysis. Thus, it is necessary to propose some similarity measures between ONNSs to supplement the gap. To solve the issue, this study firstly proposes the p-indeterminate… More >

  • Open Access


    Power Aggregation Operators and Similarity Measures Based on Improved Intuitionistic Hesitant Fuzzy Sets and their Applications to Multiple Attribute Decision Making

    Tahir Mahmood1, Wajid Ali1, Zeeshan Ali1, Ronnason Chinram2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1165-1187, 2021, DOI:10.32604/cmes.2021.014393

    Abstract Intuitionistic hesitant fuzzy set (IHFS) is a mixture of two separated notions called intuitionistic fuzzy set (IFS) and hesitant fuzzy set (HFS), as an important technique to cope with uncertain and awkward information in realistic decision issues. IHFS contains the grades of truth and falsity in the form of the subset of the unit interval. The notion of IHFS was defined by many scholars with different conditions, which contain several weaknesses. Here, keeping in view the problems of already defined IHFSs, we will define IHFS in another way so that it becomes compatible with other existing notions. To examine the… More >

Displaying 1-10 on page 1 of 5. Per Page  

Share Link