Description: Heuristic methods are techniques that employ practical approaches and general rules to solve complex problems, particularly in various domains such as optimization, artificial intelligence, and anomaly detection. These methods are based on experience and prior knowledge, enabling systems to identify patterns and unusual behaviors in large volumes of data. Unlike traditional algorithmic approaches, which require precise mathematical models, heuristic methods are more flexible and adaptive, making them ideal for situations where data is noisy or incomplete. Their relevance lies in their ability to enhance the efficiency and effectiveness of various detection systems, enabling organizations to identify potential issues before they escalate into crises. These methods may include techniques such as clustering analysis, outlier detection, and the use of neural networks, among others. In summary, heuristic methods are valuable tools in problem-solving scenarios, as they combine human intuition with the power of computational tools to tackle complex challenges more effectively.
