{"title":"A new probabilistic model with properties and Monte Carlo simulation: Its explorations in dance education and music engineering","authors":"Hualong Zhong , Yuanjun Xue , Tmader Alballa , Wafa F. Alfwzan , Somayah Abdualziz Alhabeeb , Hamiden Abd El-Wahed Khalifa","doi":"10.1016/j.aej.2024.10.095","DOIUrl":null,"url":null,"abstract":"<div><div>In the examination of real-life situations, the application of probability distributions is often crucial for statistical analysis of the real-life scenarios. Many models based on probability have been utilized in disciplines such as music education, music engineering, and other music-related areas. Hence, acknowledging the significance of probability-based approaches, this article introduces an innovative probability model known as a new generalized Rayleigh distribution. The suggested model is established on merging the generalized Rayleigh distribution with a prominent weighted probabilistic method. The mathematical properties, specifically the quartile-based features of the novel generalized Rayleigh distribution, are investigated. Moreover, we outline the derivation of the point estimators for the unknown parameters of the new model. A thorough simulation study is also conducted to examine the performances of these point estimators. Within the music industry, specifically in music education and music engineering, we examine the practical implications of the new generalized Rayleigh distribution. We observe that it offers a superior fit when contrasted with other distributions. Our findings demonstrate that the new distribution is a inclusion to the group of probability distributions that can be applied in music engineering and other closely connected engineering fields for the statistical analysis of real-life events.</div></div>","PeriodicalId":7484,"journal":{"name":"alexandria engineering journal","volume":"112 ","pages":"Pages 461-473"},"PeriodicalIF":6.2000,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"alexandria engineering journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1110016824012614","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
In the examination of real-life situations, the application of probability distributions is often crucial for statistical analysis of the real-life scenarios. Many models based on probability have been utilized in disciplines such as music education, music engineering, and other music-related areas. Hence, acknowledging the significance of probability-based approaches, this article introduces an innovative probability model known as a new generalized Rayleigh distribution. The suggested model is established on merging the generalized Rayleigh distribution with a prominent weighted probabilistic method. The mathematical properties, specifically the quartile-based features of the novel generalized Rayleigh distribution, are investigated. Moreover, we outline the derivation of the point estimators for the unknown parameters of the new model. A thorough simulation study is also conducted to examine the performances of these point estimators. Within the music industry, specifically in music education and music engineering, we examine the practical implications of the new generalized Rayleigh distribution. We observe that it offers a superior fit when contrasted with other distributions. Our findings demonstrate that the new distribution is a inclusion to the group of probability distributions that can be applied in music engineering and other closely connected engineering fields for the statistical analysis of real-life events.
期刊介绍:
Alexandria Engineering Journal is an international journal devoted to publishing high quality papers in the field of engineering and applied science. Alexandria Engineering Journal is cited in the Engineering Information Services (EIS) and the Chemical Abstracts (CA). The papers published in Alexandria Engineering Journal are grouped into five sections, according to the following classification:
• Mechanical, Production, Marine and Textile Engineering
• Electrical Engineering, Computer Science and Nuclear Engineering
• Civil and Architecture Engineering
• Chemical Engineering and Applied Sciences
• Environmental Engineering