Computing probabilistic solutions of the Bernoulli random differential equation

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• 作者：M.-C. Casabá ; n ^{macabar@imm.upv.es" class="auth_mail" title="E-mail the corresponding author} ; J.-C. Corté ; s ^{jccortes@imm.upv.es" class="auth_mail" title="E-mail the corresponding author} ; A. Navarro-Quiles ^{annaqui@doctor.upv.es" class="auth_mail" title="E-mail the corresponding author} ; J.-V. Romero ; ^{jvromero@imm.upv.es" class="auth_mail" title="E-mail the corresponding author} ; M.-D. Roselló ; ^{drosello@imm.upv.es" class="auth_mail" title="E-mail the corresponding author} ; R.-J. Villanueva ^{rjvillan@imm.upv.es" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Bernoulli random differential equation ; First probability density function ; Probabilistic solution ; Random variable transformation technique
• 刊名：Journal of Computational and Applied Mathematics
• 出版年：2017
• 出版时间：1 January 2017
• 年：2017
• 卷：309
• 期：Complete
• 页码：396-407
• 全文大小：1131 K

文摘

The random variable transformation technique is a powerful method to determine the probabilistic solution for random differential equations represented by the first probability density function of the solution stochastic process. In this paper, that technique is applied to construct a closed form expression of the solution for the Bernoulli random differential equation. In order to account for the general scenario, all the input parameters (coefficients and initial condition) are assumed to be absolutely continuous random variables with an arbitrary joint probability density function. The analysis is split into two cases for which an illustrative example is provided. Finally, a fish weight growth model is considered to illustrate the usefulness of the theoretical results previously established using real data.