Complex-valued neuro-fuzzy inference system for wind prediction
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 i...
| Main Authors: | , , |
|---|---|
| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2013
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/97939 http://hdl.handle.net/10220/12380 |
| _version_ | 1826125985448198144 |
|---|---|
| author | Suresh, Sundaram Subramanian, K. Savitha, R. |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Suresh, Sundaram Subramanian, K. Savitha, R. |
| author_sort | Suresh, Sundaram |
| collection | NTU |
| description | 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. |
| first_indexed | 2024-10-01T06:45:21Z |
| format | Conference Paper |
| id | ntu-10356/97939 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:45:21Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/979392020-05-28T07:17:23Z Complex-valued neuro-fuzzy inference system for wind prediction Suresh, Sundaram Subramanian, K. Savitha, R. School of Computer Engineering International Joint Conference on Neural Networks (2012 : Brisbane, Australia) DRNTU::Engineering::Computer science and engineering 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. 2013-07-26T06:13:30Z 2019-12-06T19:48:33Z 2013-07-26T06:13:30Z 2019-12-06T19:48:33Z 2012 2012 Conference Paper Subramanian, K., Savitha, R., & Suresh, S. (2012). Complex-valued neuro-fuzzy inference system for wind prediction. The 2012 International Joint Conference on Neural Networks (IJCNN). https://hdl.handle.net/10356/97939 http://hdl.handle.net/10220/12380 10.1109/IJCNN.2012.6252812 en © 2012 IEEE. |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Suresh, Sundaram Subramanian, K. Savitha, R. Complex-valued neuro-fuzzy inference system for wind prediction |
| title | Complex-valued neuro-fuzzy inference system for wind prediction |
| title_full | Complex-valued neuro-fuzzy inference system for wind prediction |
| title_fullStr | Complex-valued neuro-fuzzy inference system for wind prediction |
| title_full_unstemmed | Complex-valued neuro-fuzzy inference system for wind prediction |
| title_short | Complex-valued neuro-fuzzy inference system for wind prediction |
| title_sort | complex valued neuro fuzzy inference system for wind prediction |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/97939 http://hdl.handle.net/10220/12380 |
| work_keys_str_mv | AT sureshsundaram complexvaluedneurofuzzyinferencesystemforwindprediction AT subramaniank complexvaluedneurofuzzyinferencesystemforwindprediction AT savithar complexvaluedneurofuzzyinferencesystemforwindprediction |