Introduction, availability and role of simulation in surgical education and training: Review of current evidence and recommendations from the association of surgeons in training
Rcts, Cohort, Case Control and Interrupted Time Series
NEW EVIDENCE ON THE IMPACT OF FINANCIAL LEVERAGE ON BETA RISK: A TIME SERIES APPROACH
ROCKETS An Educator's Guide with Activities in Science, Mathematics, and Technology
Spiking Neural Networks As Continuous-Time Dynamical Systems: Fundamentals, Elementary Structures And Simple Applications
Modeling sequential context effects in judgment analysis: A time series approach
Apparent and real time in studies of linguistic change and variation
A Back Propagation Neural Networks for Grading Jatropha curcas ...
Applications of Artificial Neural Networks
What is Artificial Neural Networks
Increasingly, neural networks are used and implemented in a wide range of fields and have become useful tools in probabilistic analysis and prediction theory. This book—unique in the literature—studies the application of neural networks to the analysis of time series of sea data, namely significant wave heights and sea levels. The particular problem examined as a starting point is the reconstruction of missing data, a general problem that appears in many cases of data analysis.
Specific topics covered include:
* Presentation of general information on the phenomenology of waves and tides, as well as related technical details of various measuring processes used in the study
* Description of the model of wind waves (WAM) used to determine the spectral function of waves and predict the behavior of SWH (significant wave heights); a comparison is made of the reconstruction of SWH time series obtained by means of neural network algorithms versus SWH computed by WAM
* Principles of artificial neural networks, approximation theory, and extreme-value theory necessary to understand the main applications of the book.
* Application of artificial neural networks (ANN) to reconstruct SWH and sea levels (SL)
* Comparison of the ANN approach and the approximation operator approach, displaying the advantages of ANN
* Examination of extreme-event analysis applied to the time series of sea data in specific locations
* Generalizations of ANN to treat analogous problems for other types of phenomena and data
This book, a careful blend of theory and applications, is an excellent introduction to the use of ANN, which may encourage readers to try analogous approaches in other important application areas. Researchers, practitioners, and advanced graduate students in neural networks, hydraulic and marine engineering, prediction theory, and data analysis will benefit from the results and novel ideas presented in this useful resource.
Use coupon below to get discount at eCampus.com!
$3 off textbook orders over $75
$4 off textbook orders over $90
$5 off textbook orders over $100
Copy the coupon code before clicking the button!
|Amazon US||Paperback||$53.34 - $104.00|
Neural networks are one of the fast-growing paradigms for learning systems with a wide variety of potential applications in industry. In particular there are general results which prove the universal ...
This is a unique undergraduate level textbook on Cellular Nonlinear/neural Networks (CNN) technology. The many examples and excercises, including a simulator accessible via the Internet, make this ...
The book shows a very original organization addressing in a non traditional way, but with a systematic approach, to who has an interest in using mathematics in the social sciences.The book is divided ...
This volume is concerned with the analysis and interpretation of multivariate measurements commonly found in the mineral and metallurgical industries, with the emphasis on the use of neural networks. ...
Reviews theoretical, historical and clinical issues, including the contribution of neural network models to diagnosis, pharmacotherapy and psychotherapy. It will interest clinicians and researchers ...
Cellular Nonlinear/Neural Network (CNN) technology is both a revolutionary concept and an experimentally proven new computing paradigm. Analogic cellular computers based on CNNs are set to change the ...
This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform ...
Looks at financial prediction from a broad range of perspectives. All of the techniques are demonstrated with real examples using actual market data, and show that it is possible to extract ...
Compensatory Genetic Fuzzy Neural Networks and Their Applications
Trading Using Artificial Intelligence: Expert Systems, Neural Networks and Hybrid Systems (Wiley Finance)