Adaptive Neuro Fuzzy Inference System

Adaptive Neuro-Fuzzy Inference Systems (ANFIS) combine the strengths of neural networks and fuzzy logic to create adaptable models for complex, often nonlinear, systems. Current research focuses on applying ANFIS, often coupled with optimization algorithms like Rain Optimization or hybrid training methods (e.g., backpropagation and least squares), to diverse prediction and control problems, including cryptocurrency forecasting, power generation optimization, and medical diagnostics (e.g., potassium level estimation from ECG data). This approach offers improved accuracy and adaptability compared to traditional methods in various fields, leading to more efficient systems and potentially better decision-making in areas like energy management and healthcare.