Name
Abstract | ||
|---|---|---|
Climate changes on Iraq characterized by increasing droughts and desertification cause many environmental problems especially in the last decade. In this study, a model was designed to forecast selected weather variables in Nineveh province which is located in northwestern of Iraq based on artificial neural networks consisting radial basis function, Fuzzy C-Means, and Nonlinear Autoregressive Network with Exogenous inputs. The performance accuracy of this developed model gives very close predicted results with very small statistic errors for predicted period years from 2015 till the year 2050 then the model begins to collapse and its results are irrational. An interface window was designed to be an easy facility to work on this model without any difficulty or complexity. This model is a very useful tool for decision-makers for developing future plans to address the rapid climate changes in the study area. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1080/08839514.2018.1530858 | APPLIED ARTIFICIAL INTELLIGENCE |
Field | DocType | Volume |
Autoregressive model,Data mining,Radial basis function,Climate change,Computational intelligence,Statistic,Computer science,Fuzzy logic,Artificial intelligence,Artificial neural network,Weather forecasting,Machine learning | Journal | 33.0 |
Issue | ISSN | Citations |
2 | 0883-9514 | 0 |
PageRank | References | Authors |
0.34 | 5 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bashar Muneer Yahya | 1 | 0 | 0.34 |
| Dursun Zafer Seker | 2 | 4 | 2.42 |