A HYBRID MACHINE LEARNING USING MAMDANI TYPE FUZZY INFERENCE SYSTEM (FIS) FOR SOLAR POWER PREDICTION
Explore this paper's citation graph
Summary
It is demonstrated that a hybrid or aggregated machine learning using Mamdani type fuzzy inference system (FIS) for solar power prediction can deliver improved prediction accuracy that outperforms those of single machine learning technique.
- Type
- article
- Published
- 2013-07-01
- Cited by
- 3
- References
- 65
- Access
- Open access
- OpenAlex
- https://openalex.org/W33755662
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:107895720
Keywords
Machine learning, Artificial intelligence, Support vector machine, Computer science, Multilayer perceptron
References
- Pattern recognition using generalized portrait method
- Benchmarking of different approaches to forecast solar irradiance
- Synoptic Scale Forecast Skill and Systematic Errors in the MASS 2.0 Model
- Fuzzy Logic with Engineering Applications: Ross/Fuzzy Logic with Engineering Applications
- Selection of Relevant Features and Examples in Machine Learning
- Artificial neural networks for the prediction of the energy consumption of a passive solar building
- Design of Transparent Mamdani Fuzzy Inference Systems
- A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection
- A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning
- Validation of short and medium term operational solar radiation forecasts in the US
- A new correlation between clearness index and relative sunshine
- Prediction of daily global solar radiation using fuzzy systems
- Artificial neural networks used for the performance prediction of a thermosiphon solar water heater
- Time series analysis of daily horizontal solar radiation
- The 15‐km version of the Canadian regional forecast system
- An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller
- Time series analysis of hourly global horizontal solar radiation
- Uncertainty analysis for the forecast of lake level fluctuations using ensembles of ANN and ANFIS models
- Obtaining interpretable fuzzy classification rules from medical data
- Predicting solar generation from weather forecasts using machine learning
Cited by
Related papers
- Comparison of different models for wind speed prediction
- A soft computing approach for modeling of severity of faults in software systems
- Multi-Step Ahead Wind Power Generation Prediction Based on Hybrid Machine Learning Techniques
- Structure identification and IO space partitioning in a nonlinear fuzzy system for prediction of patient survival after surgery
- A Clustering based Genetic Fuzzy expert system for electrical energy demand prediction
- The Effectiveness of Hybrid Backpropagation Neural Network Model and TSK Fuzzy Inference System for Inflation Forecasting
- Software reliability prediction using machine learning techniques