The current study relates to designing a swarming computational paradigm to solve the influenza disease system (IDS). The nonlinear system’s mathematical form depends upon four classes: susceptible ndividuals, infected people, recovered individuals and cross-immune people. The solutions of the IDS are provided by using the artificial neural networks (ANNs) together with the swarming computational paradigm-based particle swarm optimization (PSO) and interior-point scheme (IPA) that are the global and local search approaches. The ANNs-PSO-IPA has never been applied to solve the IDS. Instead a merit function in the sense of mean square error is constructed using the differential form of each class of the IDS and then optimized by the PSOIPA. The correctness and accuracy of the scheme are observed to perform the comparative analysis of the obtained IDS results with the Adams solutions (ref...

La extensión universitaria, en el contexto de la revolución científico tecnológica, se debe gestionar bajo la orientación de modelos integradores, que interrelacióneme con el trabajo formativo de la universidad con las exigencias del mundo institucional y laboral. En este orden de ideas, el problema que se abordó en el estudio fue la gestión asistémica-tradicional de la extensión universitaria, que se realiza en la Facultad de Ciencias Físicas y Matemáticas de la Universidad Nacional Pedro Ruiz gallo. El propósito o finalidad del estudio, fue configurar la logicidad sistémica del Modelo de Gestión por Procesos de la Extensión Universitaria de La FACFYM-UNPRG, para insertarlo en el Contexto Socioeconómico; propuesta fundamentada en las perspectivas teóricas de los modelos de extensión universitaria y la gestión por procesos. Las conclusiones centrales del estudio fuero...

In this paper, we generalize He’s frequency approach for solving the damped Duffing equation by introducing a time varying amplitude. We also solve this equation by means of the homotopy method and the Lindstedt–Poincaré method. High accurate formulas for approximating the Jacobi elliptic function cn are formally derived using Chebyshev and Pade approximation techniques.

In this communication, a fractional order design and numerical form of the solutions are presented for numerical simulations of heterogeneous mosquito model. The use of the fractional order derivatives is exploited to observe more accurate and exhaustive performances of the numerical simulation of the model. The novel design of the fractional order heterogeneous mosquito differential system is analyzed with stochastic solver based on the internet of things (IoT) technologies, represented with four categories i.e., normal individuals, people with reflex behavior, panic behavior and controlled behavior based differential system. The solutions of the novel design of the fractional order system are presented by using the stochastic paradigm of artificial neural network (ANN) procedures along with the Scaled Conjugate Gradient (SCG), i.e., ANN-SCG, for learning of weights. In ANN-SCG implemen...