Applications of Wavelet Neural Networks in Time Series Forecasting
In this extensive manuscript, Mohd Yasin Pir embarks on a meticulously organized and in-depth investigation of wavelet networks as they pertain to the forecasting of time series data. This volume emerges as an indispensable asset for scholars and students immersed in the realms of mathematical modeling, artificial neural networks, wavelet analysis, and the discipline of economics, seamlessly merging theoretical insights with practical implementations. The text is thoughtfully segmented into three coherent sections. Initially, it lays down the key principles underpinning wavelet neural networks, offering an introduction to time series scrutiny, the realm of artificial neural networks, and wavelet analysis itself, while underscoring the unique advantages each possesses in the art of forecasting. The author adeptly contrasts these innovative methods with established statistical techniques, shining a spotlight on the enhanced efficacy presented by hybrid models that synergize wavelets with neural frameworks. Moving into the second segment, the narrative dives into tangible applications, illustrating how wavelet networks find utility in finance and classification through various empirical outcomes and thoughtful discussions. The concluding section succinctly articulates prospective pathways and insights, equipping readers with a lucid perspective on forthcoming advancements within this domain. Pir's endeavor crafts a meticulously arranged and reader-friendly exploration of this intricate subject matter, rendering it a must-read for anyone eager to grasp sophisticated methodologies in the forecasting of time series data.
- Author: Mohd Yasin Pir
- Publisher: White Falcon Publishing
- Genre: Business Strategy
- ISBN: 9781636404424
- Pages: 152