Four types of mathematical modeling techniques [multiple linear regression (MLR), multilayer perception (MLP) network, radial basis function (RBF) network, and support vector machine (SVM)] and six combinations of predictor variables were used to develop a total of 24 predictive mathematical models ...
Later, mathematical model was formed for particular cases of the gap of electromagnetic levitation and many composite non-contact mechanisms. This analysis mechanics creates effective contactless mechanisms which help us many aspects of energy and material saving.Matmurodov, F. M....
Recently, many countries have been commissioning large numbers of wind power plants (WPP) with wind turbines (WT) The development of power output diagrams for WPPs is associated with problems of the mathematical modeling of WTs for the calculation of short-circuit (SC) currents. This is required...
The final type of 3D modeling we are going to explore is Non-Uniform Rational Basis Spline or NURBS for short. This is a very popular method of 3D modeling due to its elegance, as it functions via a mathematical model that can be applied in a variety of scenarios to create realistic cur...
Using mathematical modeling and computer science, financial engineers are able to test and issue new tools such as new methods of investment analysis, new debt offerings, new investments, new trading strategies, new financial models, etc.
Financial Models are mathematical representations of financial operations or investments. They are used to evaluate and predict financial performance, determine the possible outcomes of various decisions, and produce accurate financial projections. The goal of Financial Modeling is to provide a framework ...
Predictive modeling is a statistical technique used to predict the outcome of future events based on historical data. It involves building a mathematical model that takes relevant input variables and generates a predicted output variable. Machine learning algorithms are used to train and improve these ...
A model can be defined as a description of a real-world system or process using mathematical concepts. It is usually represented as a mapping between input and output variables. In this regard, neural networks are used to discover relationships, recognize patterns, predict trends, and recognize ...
A mathematical model is often fitted to the data set while estimation of epidemiological parameter is done from disease outbreak data. The probable estimates of parameters are uncertain that may arise due to sum data errors. The estimates are dependent on structure models used in fitting process ...
We first generate new features based on mathematical transformations of the existing numerical features. AutoFE (automatically feature engineering) applied operations such as logarithms, square roots, and exponentials to the original features. Next, we created new categorical features by grouping the origi...