Complex-valued neuro-fuzzy inference system for wind prediction
Open Access
- 1 June 2012
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE) in The 2012 International Joint Conference on Neural Networks (IJCNN)
Abstract
In this paper, we present a complex-valued neuro-fuzzy inference system (CNFIS) and its gradient descent based learning algorithm developed employing Wirtinger calculus. The proposed CNFIS is a four layered network which realizes zero-order Takagi-Sugeno-Kang based fuzzy inference mechanism. CNFIS is used to predict the speed and direction of wind. Here, the speed and direction are considered as statistically independent variables and are represented as a complex-valued signal (with speed as magnitude and direction as phase). Performance of CNFIS is compared with other algorithms available in the literature and results indicate improved performance of CNFIS. The major contribution of this paper is as follows: (1) Propose a complex-valued neuro-fuzzy inference system (2) Employ Wirtinger calculus for complex-valued gradient descent algorithm (3) Solve wind speed and direction prediction problem in complex domain.Keywords
This publication has 33 references indexed in Scilit:
- Fast learning Circular Complex-valued Extreme Learning Machine (CC-ELM) for real-valued classification problemsInformation Sciences, 2012
- A Sequential Learning Algorithm for Complex-Valued Self-Regulating Resource Allocation Network-CSRANIEEE Transactions on Neural Networks, 2011
- Fast Learning Fully Complex-Valued Classifiers for Real-Valued Classification ProblemsLecture Notes in Computer Science, 2011
- Single-layered complex-valued neural network for real-valued classification problemsNeurocomputing, 2009
- Multilayer Feedforward Neural Network Based on Multi-valued Neurons (MLMVN) and a Backpropagation Learning AlgorithmSoft Computing, 2006
- A MODIFIED ERROR BACKPROPAGATION ALGORITHM FOR COMPLEX-VALUE NEURAL NETWORKSInternational Journal of Neural Systems, 2005
- An Approach to Online Identification of Takagi-Sugeno Fuzzy ModelsIEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2004
- Orthogonality of Decision Boundaries in Complex-Valued Neural NetworksNeural Computation, 2004
- Approximation by Fully Complex Multilayer PerceptronsNeural Computation, 2003
- Complex-valued radial basic function network, Part I: Network architecture and learning algorithmsSignal Processing, 1994