Аpplication of fuzzy logic algorithms for energy сonsumption forecasting

Abstract

Fuzzy logic is a form of multi-valued logic in which the truth values of the variables can be any real number between 0 and 1, inclusive. It is used to deal with the concept of partial truth, where the truth value can vary between completely true and completely false. This contrasts with traditional Boolean logic, where truth values are binary - either true or false. Fuzzy logic provides a more flexible way to reason and make decisions under uncertainty and imprecision, making it particularly useful in artificial intelligence and machine learning for applications that mimic human decision making. The ability of fuzzy logic to deal with imprecise and uncertain information makes it valuable in a variety of applications: 1. Control systems. Fuzzy logic controllers are widely used in industrial control systems, home appliances like washing machines, and automotive systems. For example, in a washing machine, fuzzy logic can control the wash cycle based on the type and amount of laundry, optimizing water and energy consumption. 2. Image processing and computer vision. In computer vision, fuzzy logic can improve image segmentation and object recognition by dealing with the ambiguity and fuzziness inherent in visual data. For example, in medical image analysis, fuzzy logic can help determine the boundaries of tumors or lesions where the edges may not be clearly defined.