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Mathematical Optimization in Mobile Apps Business Essay

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Updated: Jul 4th, 2021

The Problem

Mobile application development is the term used to refer to an act or process by which a software application is developed for mobile devices such as personal digital assistants, corporate digital assistants, or mobile phones. These applications can be pre-installed on devices during production, downloaded by the user through various platforms for installing mobile apps or delivered in a web application that is processed on the client-side or server.

Currently, there is a rapid growth in sales of mobile devices, replacing a personal computer. The number of users of mobile devices is increasing, so it needs quantity and quality software. This leads to the constant rapid growth of application development technologies for mobile devices. Therefore, the selected application business involves statistical data-gathering programs, such as dating applications or apps where people search for jobs. The problem is the lack of proper mathematical optimization, where, for example, a potential employee gets recommendations based on unimportant parameters.

Data Analysis

Based on the statistical data for all points, it is essential to identify and analyze the transfer functions’ parameters and make an integral dynamic mathematical model, written in the form of a system of linear finite-difference equations with discretization by critical features. Within the framework of the integrated model in the environment of statistical analysis, it is essential to carry out optimization modeling for the local region. The methodology for identifying model coefficients for optimal control synthesis, taking into account restrictions, has been developed.

Data Assimilation

Procedure for modeling and forecasting professional employment needs allows simulating these processes in the main groups of specialties for all subjects. The developed technique is based on a formalized technological approach, representing a group of specialists with higher education as one of the elements of the technological chain in the production of goods and services. The methodology for predicting the future needs of the labor market in individuals with professional skills is based on the analysis of such an inertial parameter as the structure of the forecasted market needs. Forecasting the current and future needs of a particular labor market in personnel with different professional skills uses a strict sequence for each subject.

The primary way to estimate and analyze the mathematical expectation is to take the most common value of the variable of interest to us as its value. This value is called the distribution mode, and it plays a significant role in performing mathematical remodeling. Model estimation is mainly used when the experimenter is dealing with variables that take discrete values ​​given on a non-metric scale. It is clear that the mode, like the arithmetic mean, may or may not coincide with the actual cost of the mathematical expectation. However, just like the arithmetic means, the model is an unbiased estimate of the mathematical expectation.

In addition, if two values ​​in the sample are found equally often, then this distribution is called bimodal. If three or more values ​​in a model are usually found equally, then they say that such an example has no mode. Such cases with a sufficiently large number of observations, as a rule, indicate that the data are extracted from the general population, the nature of the distribution which differs from average.

Impact of the Optimization Process

The program of optimization modeling of the distribution of parametric data flows allows predicting the distribution of units taking into account demographic and professional factors. At the initial choice of the modeling environment, a prognostic approach was used, specially developed for the study of dynamic systems and having a number of timely diagnostics. At the same time, it should be noted that this approach has a good set of functions for working with range variables for defining features and solving systems of finite difference equations in vector form. In the study and formulation of the deterministic part of the problem, both of these methods can be used.

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IvyPanda. (2021, July 4). Mathematical Optimization in Mobile Apps Business. Retrieved from https://ivypanda.com/essays/mathematical-optimization-in-mobile-apps-business/

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"Mathematical Optimization in Mobile Apps Business." IvyPanda, 4 July 2021, ivypanda.com/essays/mathematical-optimization-in-mobile-apps-business/.

1. IvyPanda. "Mathematical Optimization in Mobile Apps Business." July 4, 2021. https://ivypanda.com/essays/mathematical-optimization-in-mobile-apps-business/.


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IvyPanda. "Mathematical Optimization in Mobile Apps Business." July 4, 2021. https://ivypanda.com/essays/mathematical-optimization-in-mobile-apps-business/.

References

IvyPanda. 2021. "Mathematical Optimization in Mobile Apps Business." July 4, 2021. https://ivypanda.com/essays/mathematical-optimization-in-mobile-apps-business/.

References

IvyPanda. (2021) 'Mathematical Optimization in Mobile Apps Business'. 4 July.

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