Shahlaa Mashhadani^1,*, Wisal Hashim Abdulsalam¹, Oday Ali Hassen², Saad M. Darwish³

Intelligent Automation & Soft Computing, Vol.39, No.5, pp. 805-828, 2024, DOI:10.32604/iasc.2024.054611 - 31 October 2024

Abstract Signature verification involves vague situations in which a signature could resemble many reference samples or might differ because of handwriting variances. By presenting the features and similarity score of signatures from the matching algorithm as fuzzy sets and capturing the degrees of membership, non-membership, and indeterminacy, a neutrosophic engine can significantly contribute to signature verification by addressing the inherent uncertainties and ambiguities present in signatures. But type-1 neutrosophic logic gives these membership functions fixed values, which could not adequately capture the various degrees of uncertainty in the characteristics of signatures. Type-1 neutrosophic representation is also… More >

Ali Ahmed^1,*, Alaa Omran Almagrabi², Omar M. Barukab³

Intelligent Automation & Soft Computing, Vol.37, No.2, pp. 2355-2370, 2023, DOI:10.32604/iasc.2023.039847 - 21 June 2023

Abstract Content-based medical image retrieval (CBMIR) is a technique for retrieving medical images based on automatically derived image features. There are many applications of CBMIR, such as teaching, research, diagnosis and electronic patient records. Several methods are applied to enhance the retrieval performance of CBMIR systems. Developing new and effective similarity measure and features fusion methods are two of the most powerful and effective strategies for improving these systems. This study proposes the relative difference-based similarity measure (RDBSM) for CBMIR. The new measure was first used in the similarity calculation stage for the CBMIR using an More >

Lei Gu^*, Furong Zhang, Li Ma

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5911-5928, 2023, DOI:10.32604/cmc.2023.038127 - 29 April 2023

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 More >

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 - 05 January 2023

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 More >

Angyan Tu^1,2, Jiancheng Chen³, Bing Wang^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.2, pp. 377-387, 2022, DOI:10.32604/cmes.2022.021299 - 21 July 2022

Abstract A neutrosophic multi-valued set (NMVS) is a crucial representation for true, false, and indeterminate multi-valued information. Then, a consistent single-valued neutrosophic set (CSVNS) can effectively reflect the mean and consistency degree of true, false, and indeterminate multi-valued sequences and solve the operational issues between different multi-valued sequence lengths in NMVS. However, there has been no research on consistent single-valued neutrosophic similarity measures in the existing literature. This paper proposes cotangent similarity measures and weighted cotangent similarity measures between CSVNSs based on cotangent function in the neutrosophic multi-valued setting. The cosine similarity measures show the cosine… More >

Jayavarthini Chockalingam^*, Malathy Chidambaranathan

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 697-710, 2022, DOI:10.32604/iasc.2022.024142 - 08 February 2022

Abstract Presently, Person Re-IDentification (PRe-ID) acts as a vital part of real time video surveillance to ensure the rising need for public safety. Resolving the PRe-ID problem includes the process of matching observations of persons among distinct camera views. Earlier models consider PRe-ID as a unique object retrieval issue and determine the retrieval results mainly based on the unidirectional matching among the probe and gallery images. But the accurate matching might not be present in the top-k ranking results owing to the appearance modifications caused by the difference in illumination, pose, viewpoint, and occlusion. For addressing… More >

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 - 20 August 2021

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… More >

Mailing Zhao¹, Jun Ye^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.3, pp. 1219-1230, 2021, DOI:10.32604/cmes.2021.016871 - 11 August 2021

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… More >

Tahir Mahmood¹, Wajid Ali¹, Zeeshan Ali¹, Ronnason Chinram^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1165-1187, 2021, DOI:10.32604/cmes.2021.014393 - 19 February 2021

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… More >

Shiru Zhang¹, Zhiyao Liang^{1, *}, Jian Lin²

CMC-Computers, Materials & Continua, Vol.63, No.2, pp. 943-957, 2020, DOI:10.32604/cmc.2020.08800 - 01 May 2020

Abstract Calculating the semantic similarity of two sentences is an extremely challenging problem. We propose a solution based on convolutional neural networks (CNN) using semantic and syntactic features of sentences. The similarity score between two sentences is computed as follows. First, given a sentence, two matrices are constructed accordingly, which are called the syntax model input matrix and the semantic model input matrix; one records some syntax features, and the other records some semantic features. By experimenting with different arrangements of representing the syntactic and semantic features of the sentences in the matrices, we adopt the… More >