13.0 Types of Knowledge | Neural Networks And Fuzzy Logic

Описание: This lecture is part of a lecture series on Artificial Neural Network (ANN) by Ms Pooja Sharma for B.Tech students at Binary Institute.
Description
Types of knowledge in neural networks and fuzzy logic refer to the different forms of information that these systems can represent and process to solve problems. Common types include:

procedural knowledge, which defines how tasks are performed or actions are taken. In neural networks, this is captured in the form of learned weights and connections.

declarative knowledge, which describes facts or relationships about the world. In fuzzy logic, this is represented using fuzzy rules and membership functions.

heuristic knowledge, which consists of rules of thumb or expert insights used for making decisions under uncertainty.

These types of knowledge help neural networks and fuzzy logic systems handle tasks like classification, prediction, reasoning, and control.

#ArtificialNeuralNetwork #ANN #NeuralNetworks #FuzzyLogic #KnowledgeTypes #MachineLearning #AI #SoftComputing #IntelligentSystems #FuzzySystems #DeepLearning #PatternRecognition #DecisionMaking