Kernel Probability Density Estimation in Solving the Problem of Classification of the Technical Condition of Complex Systems

To improve the versatility of modeling for recognizing the technical condition of a complex system, a solution to the problem of its statistical classification is proposed. The fact that the current condition belongs to a specific class is evaluated by confirming the hypothesis using a decision function based on the inductive behavior concept. The confirmation is made by estimating the probability of the object’s current parameters falling within a 2D parallelepiped of the joint density function determined using the kernel probability density estimation method.