History tells that every human being desire to foresee, comprehend
and ultimately explore the future. Multi-step ahead forecasting is
a challenging research area due to propagation of forecasting
errors with the increase of forecasting steps. Two interesting
architectures based on nearest neighbor method are proposed.
Importance of selection criteria in nearest neighbor search plays
an important role in multi-step ahead forecasting. Effect of
up-sampling of time series and change of effective embedding
dimension on the forecasting errors is studied in detail. Effect of
five interpolation schemes for up-sampling and comparison of three
distance metrics for nearest neighbor search on forecasting
performance is also included. A hybrid selection criterion of
nearest neighbor with avoidance of biasing is found to be very
effective in multi-step ahead forecasting. In the end,
predictability analysis of proposed algorithms on ten benchmark
time series highlight the effectiveness of the forecasting
algorithms in the scenarios of series collected from different
kinds of dynamic systems. This book is based on the PhD work of Mr.
Rahat Abbas.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!
Welcome to Loot.co.za!
Sign in / Register |Wishlists & Gift Vouchers |Help | Advanced search
