Repository logo
  • English
  • Yкраї́нська
Log In
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Матеріали конференцій
  3. Наукова весна
  4. «Наукова весна» 2025 : матеріали XV Міжнародної науково-технічної конференції аспірантів та молодих вчених, Дніпро, 26-28 березня 2025 року
  5. Секція «Інформаційні технології та телекомунікації»
  6. Аpplication of fuzzy logic algorithms for energy сonsumption forecasting
 
  • Details

Аpplication of fuzzy logic algorithms for energy сonsumption forecasting

Date Issued
2025
Author(s)
Titov M.G.
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.
Subjects

нечітка логіка

алгоритм

прогнозування

споживання енергії

File(s)
Loading...
Thumbnail Image
Name

Scientific_Spring_2025-210-211.pdf

Size

319.05 KB

Format

Adobe PDF

Checksum

(MD5):6002fc283a41ba83838eaf994db1bb6f

.

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • End User Agreement
  • Send Feedback
Repository logo COAR Notify