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  1. Article ; Online: Author Correction: Divorce prediction using machine learning algorithms in Ha'il region, KSA.

    Moumen, Abdelkader / Shafqat, Ayesha / Alraqad, Tariq / Alshawarbeh, Etaf Saleh / Saber, Hicham / Shafqat, Ramsha

    Scientific reports

    2024  Volume 14, Issue 1, Page(s) 5452

    Language English
    Publishing date 2024-03-05
    Publishing country England
    Document type Published Erratum
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-024-53928-x
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Divorce prediction using machine learning algorithms in Ha'il region, KSA.

    Moumen, Abdelkader / Shafqat, Ayesha / Alraqad, Tariq / Alshawarbeh, Etaf Saleh / Saber, Hicham / Shafqat, Ramsha

    Scientific reports

    2024  Volume 14, Issue 1, Page(s) 502

    Abstract: The application of artificial intelligence (AI) in predictive analytics is growing in popularity. It has the power to offer ground-breaking solutions for a range of social problems and real world societal difficulties. It is helpful in addressing some of ...

    Abstract The application of artificial intelligence (AI) in predictive analytics is growing in popularity. It has the power to offer ground-breaking solutions for a range of social problems and real world societal difficulties. It is helpful in addressing some of the social issues that today's world seems incapable of solving. One of the most significant phenomena affecting people's lives is divorce. The goal of this paper is to study the use of machine learning algorithms to determine the effectiveness of divorce predictor scale (DPS) and identify the reasons that usually lead to divorce in the scenario of Hail region, KSA. For this purpose, in this study, the DPS, based on Gottman couples therapy, was used to predict divorce by applying different machine learning algorithms. There were 54 items of the DPS used as features or attributes for data collection. In addition to the DPS, a personal information form was utilized to gather participants' personal data in order to conduct this study in a more structured and traditional manner. Out of 148 participants 116 participants were married whereas 32 were divorced. With the use of algorithms artificial neural network (ANN), naïve bayes (NB), and random forest (RF), the effectiveness of DPS was examined in this study. The correlation based feature selection method was used to identify the top six features from the same dataset and the highest accuracy rate was 91.66% with RF. The results show that DPS can predict divorce. This scale can help family counselors and therapists in case formulation and intervention plan development process. Additionally, it may be argued that the Hail region, KSA sampling confirmed the Gottman couples treatment predictors.
    MeSH term(s) Humans ; Artificial Intelligence ; Divorce ; Bayes Theorem ; Algorithms ; Machine Learning
    Language English
    Publishing date 2024-01-04
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-023-50839-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: Explicit scheme for solving variable-order time-fractional initial boundary value problems.

    Kanwal, Asia / Boulaaras, Salah / Shafqat, Ramsha / Taufeeq, Bilal / Ur Rahman, Mati

    Scientific reports

    2024  Volume 14, Issue 1, Page(s) 5396

    Abstract: The creation of an explicit finite difference scheme with the express purpose of resolving initial boundary value issues with linear and semi-linear variable-order temporal fractional properties is presented in this study. The rationale behind the ... ...

    Abstract The creation of an explicit finite difference scheme with the express purpose of resolving initial boundary value issues with linear and semi-linear variable-order temporal fractional properties is presented in this study. The rationale behind the utilization of the Caputo derivative in this scheme stems from its known importance in fractional calculus, an area of study that has attracted significant interest in the mathematical sciences and physics. Because of its special capacity to accurately represent physical memory and inheritance, the Caputo derivative is a relevant and appropriate option for representing the fractional features present in the issues this study attempts to address. Moreover, a detailed Fourier analysis of the explicit finite difference scheme's stability is shown, demonstrating its conditional stability. Finally, certain numerical example solutions are reviewed and MATLAB-based graphic presentations are made.
    Language English
    Publishing date 2024-03-05
    Publishing country England
    Document type Journal Article
    ZDB-ID 2615211-3
    ISSN 2045-2322 ; 2045-2322
    ISSN (online) 2045-2322
    ISSN 2045-2322
    DOI 10.1038/s41598-024-55943-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Analysis of food chain mathematical model under fractal fractional Caputo derivative.

    Sami, Adnan / Ali, Amir / Shafqat, Ramsha / Pakkaranang, Nuttapol / Rahmamn, Mati Ur

    Mathematical biosciences and engineering : MBE

    2022  Volume 20, Issue 2, Page(s) 2094–2109

    Abstract: In this article, the dynamical behavior of a complex food chain model under a fractal fractional Caputo (FFC) derivative is investigated. The dynamical population of the proposed model is categorized as prey populations, intermediate predators, and top ... ...

    Abstract In this article, the dynamical behavior of a complex food chain model under a fractal fractional Caputo (FFC) derivative is investigated. The dynamical population of the proposed model is categorized as prey populations, intermediate predators, and top predators. The top predators are subdivided into mature predators and immature predators. Using fixed point theory, we calculate the existence, uniqueness, and stability of the solution. We examined the possibility of obtaining new dynamical results with fractal-fractional derivatives in the Caputo sense and present the results for several non-integer orders. The fractional Adams-Bashforth iterative technique is used for an approximate solution of the proposed model. It is observed that the effects of the applied scheme are more valuable and can be implemented to study the dynamical behavior of many nonlinear mathematical models with a variety of fractional orders and fractal dimensions.
    MeSH term(s) Fractals ; Food Chain
    Language English
    Publishing date 2022-11-14
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2265126-3
    ISSN 1551-0018 ; 1551-0018
    ISSN (online) 1551-0018
    ISSN 1551-0018
    DOI 10.3934/mbe.2023097
    Database MEDical Literature Analysis and Retrieval System OnLINE

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