{"title":"伏特拉积分微分方程的维塔-卢卡斯多项式计算技术","authors":"T. Oyedepo, A. Ayinde, Edith Didigwu","doi":"10.21608/ejmaa.2023.232998.1064","DOIUrl":null,"url":null,"abstract":". In this study, we introduce a computational technique for tack-ling Volterra Integro-Differential Equations (VIDEs) using shifted Vieta-Lucas polynomials as the foundational basis functions. The approach involves adopting an approximative solution strategy through the utilization of Vieta-Lucas polynomials. These polynomials are then integrated into the pertinent VIDEs. Subsequently, the resulting equation is subjected to collocation at evenly spaced intervals, generating a system of linear algebraic equations with unspecified Vieta-Lucas coefficients. To solve this system, we employ a matrix inversion method to deduce the unknown constants. Once these constants are determined, they are incorporated into the earlier assumed approximate solution, thus yielding the sought-after approximated solution. To validate the accuracy and efficiency of this technique, we conducted numerical experiments. The obtained results underscore the outstanding performance of our method in comparison to outcomes found in existing literature. The precision and effectiveness of the approach are further illustrated through the utilization of tables.","PeriodicalId":91074,"journal":{"name":"Electronic journal of mathematical analysis and applications","volume":"8 11","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"VIETA-LUCAS POLYNOMIAL COMPUTATIONAL TECNIQUE FOR VOLTERRA INTEGRO-DIFFERENTIAL EQUATIONS\",\"authors\":\"T. Oyedepo, A. Ayinde, Edith Didigwu\",\"doi\":\"10.21608/ejmaa.2023.232998.1064\",\"DOIUrl\":null,\"url\":null,\"abstract\":\". In this study, we introduce a computational technique for tack-ling Volterra Integro-Differential Equations (VIDEs) using shifted Vieta-Lucas polynomials as the foundational basis functions. The approach involves adopting an approximative solution strategy through the utilization of Vieta-Lucas polynomials. These polynomials are then integrated into the pertinent VIDEs. Subsequently, the resulting equation is subjected to collocation at evenly spaced intervals, generating a system of linear algebraic equations with unspecified Vieta-Lucas coefficients. To solve this system, we employ a matrix inversion method to deduce the unknown constants. Once these constants are determined, they are incorporated into the earlier assumed approximate solution, thus yielding the sought-after approximated solution. To validate the accuracy and efficiency of this technique, we conducted numerical experiments. The obtained results underscore the outstanding performance of our method in comparison to outcomes found in existing literature. The precision and effectiveness of the approach are further illustrated through the utilization of tables.\",\"PeriodicalId\":91074,\"journal\":{\"name\":\"Electronic journal of mathematical analysis and applications\",\"volume\":\"8 11\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Electronic journal of mathematical analysis and applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21608/ejmaa.2023.232998.1064\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electronic journal of mathematical analysis and applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21608/ejmaa.2023.232998.1064","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
.在本研究中,我们介绍了一种使用移位维特拉-卢卡斯多项式作为基础基函数来粘合伏特拉积分微分方程(VIDE)的计算技术。该方法通过利用 Vieta-Lucas 多项式采用近似解法。然后将这些多项式整合到相关的 VIDE 中。随后,在均匀分布的间隔内对所得到的方程进行配位,从而生成一个具有未指定的 Vieta-Lucas 系数的线性代数方程组。为了求解这个系统,我们采用矩阵反演法推导出未知常数。一旦确定了这些常量,就将其纳入先前假定的近似解中,从而得到所需的近似解。为了验证这一技术的准确性和效率,我们进行了数值实验。实验结果表明,与现有文献中的结果相比,我们的方法性能卓越。我们还利用表格进一步说明了该方法的精确性和有效性。
VIETA-LUCAS POLYNOMIAL COMPUTATIONAL TECNIQUE FOR VOLTERRA INTEGRO-DIFFERENTIAL EQUATIONS
. In this study, we introduce a computational technique for tack-ling Volterra Integro-Differential Equations (VIDEs) using shifted Vieta-Lucas polynomials as the foundational basis functions. The approach involves adopting an approximative solution strategy through the utilization of Vieta-Lucas polynomials. These polynomials are then integrated into the pertinent VIDEs. Subsequently, the resulting equation is subjected to collocation at evenly spaced intervals, generating a system of linear algebraic equations with unspecified Vieta-Lucas coefficients. To solve this system, we employ a matrix inversion method to deduce the unknown constants. Once these constants are determined, they are incorporated into the earlier assumed approximate solution, thus yielding the sought-after approximated solution. To validate the accuracy and efficiency of this technique, we conducted numerical experiments. The obtained results underscore the outstanding performance of our method in comparison to outcomes found in existing literature. The precision and effectiveness of the approach are further illustrated through the utilization of tables.