Data Information integrated Neural Network (DINN) algorithm for modelling and interpretation performance analysis for energy systems
Developing a well-predictive machine learning model that also offers improved interpretability is a key challenge to widen the application of artificial intelligence in various application domains. In this work, we present a Data Information integrated Neural Network (DINN) algorithm that incorporat...
Main Authors: | Waqar Muhammad Ashraf, Vivek Dua |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2024-05-01
|
Series: | Energy and AI |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2666546824000296 |
Similar Items
-
Partial derivative-based dynamic sensitivity analysis expression for non-linear auto regressive with exogenous (NARX) modelcase studies on distillation columns and model's interpretation investigation
by: Waqar Muhammad Ashraf, et al.
Published: (2024-05-01) -
Exploring Evaluation Methods for Interpretable Machine Learning: A Survey
by: Nourah Alangari, et al.
Published: (2023-08-01) -
Feature-Based Interpretation of the Deep Neural Network
by: Eun-Hun Lee, et al.
Published: (2021-11-01) -
Making Sense of Machine Learning: A Review of Interpretation Techniques and Their Applications
by: Ainura Tursunalieva, et al.
Published: (2024-01-01) -
Explainable AI: A Neurally-Inspired Decision Stack Framework
by: Muhammad Salar Khan, et al.
Published: (2022-09-01)