Nonlinear Curve Fitting
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In this article, we explore the concept and applications of nonlinear curve fitting. Nonlinear curve fitting refers to data fitting curves that do not conform to linear equation forms, commonly used to describe the behavior of nonlinear systems. In practical applications, these fitting methods are employed to solve various problems such as predicting future trends, analyzing data variations, and forecasting sales volumes. Understanding how to implement nonlinear curve fitting is therefore essential. Below, we provide detailed explanations of relevant concepts and practical applications, along with code implementation insights using optimization algorithms like the Levenberg-Marquardt method. Key functions such as MATLAB's lsqcurvefit or Python's scipy.optimize.curve_fit will be discussed to help readers effectively apply these techniques in real-world scenarios.
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