Neural Network Weather Forecasting Modeling Theoretical Methods and Applications

Author: Jinlong
Publisher:
Publish Date: 2004-12-01
Features: This book provides a detailed introduction to the main research achievements of the author in the field of artificial neural network meteorological forecasting modeling theory and application over the past 10 years. The main contents include: the basic theories and methods of major neural network models, various short-term climate prediction models based on neural networks, neural network modeling for time series forecasting, hybrid forecasting models using neural networks, application research on neural network forecasting models such as the interpretation of numerical weather prediction products and visibility forecasting, as well as solutions to key issues like the construction of learning matrices, generalization performance, and overfitting in neural network forecasting models. The book also presents numerous computational examples of meteorological forecasting application research, demonstrating strong practicality and facilitating application and promotion. This book is suitable for researchers engaged in meteorological forecasting research, operational forecasting, as well as those in hydrology, oceanography, environment, seismology, economics, and market prediction fields, as well as undergraduate and graduate students from relevant universities and institutions.