MLR,GMDH and ANNtechniques accurately performed with values of correlation coefficient (R) being obtained as 0.90552, 0.95542 and 0.97617 respectively. Comparative study of all models reveals that out of these three techniques, ANNperforms the best. In the ANNmodel, the values of RMSE, MAE and ...
Answer to: Compare and contrast two forecasting techniques, including the different circumstances in which these might be used. By signing up,...
Wind speed forecasting using statistical and AI techniques is conducted in the first stage. Following this, uncertainty analysis is carried out. The performance of the models in terms of confidence intervals and coverages is evaluated using a comprehensive evaluation index. The work underlines that al...
Examples for general forecasting techniques are the exponential smoothing method (McNeil et al., 2015) or the SARIMA model. A more advanced approach is to use the wavelet transform as e.g. discussed by Schlüter and Deuschle (2014), who generate point forecasts by splitting up a time series ...
A deep learning objective forecasting solution for severe convective weather (SCW) including short-duration heavy rain (HR), hail, convective gusts (CG), a
CLI 4.2 (mg kg-1), CFI 4.6 (mg kg-1), and CNI 5.3 (mg kg-1) were the satisfactory values of the root mean square error of estimation for the forecasting algorithms. The calculated excess standard deviation of the reproducibility was approximately 8%. These findings demonstrate the prospect...
For example, a CNN and an RNN could be used together in a video captioning application, with the CNN extracting features from video frames and the RNN using those features to write captions. Similarly, in weather forecasting, a CNN could identify patterns in maps of meteorological data, which...
Clustering refers to multiple techniques for grouping data together, which can assist people in understanding the data, explaining the data to executives, or performing further analyses on the data.Answer and Explanation: Different clustering techniques include hierarchical techniques, which produce tree-...
This paper aims to compare the performance of different Artificial Neural Networks techniques for tourist demand forecasting. We test the forecasting accuracy of three different types of architectures: a multi-layer perceptron, a radial basis function and an Elman network. We also evaluate the effect...
The 1983 and 2010 landslide inventory maps used in this work were based on different landslide mapping approaches that combined different techniques: detailed field mapping; high resolution aerial photo and orthophotomap interpretation; and analysis of shadow relief models. The landslide type was defined...