Shallow and Deep Learning Principles

This book discusses Artificial Neural Networks (ANN) and their ability to predict outcomes using deep and shallow learning principles. The author first describes ANN implementation, consisting of at least three layers that must be established together with cells, one of which is input, the other is output, and the third is a hidden (intermediate) layer. For this, the author states, it is necessary to develop an architecture that will not model mathematical rules but only the action and response variables that control the event and the reactions that may occur within it. The book explains the reasons and necessity of each ANN model, considering the similarity to the previous methods and the philosophical - logical rules.

Discusses Artificial Neural Networks (ANN), their features aligning with goals of parallel processing modeling methods Describes implementation of ANNs using three layers: input, output, and the hidden (intermediate) layer Presents methods for modeling, simulating, optimizing and predicting future behavior in various subjects

Auteur
Zekâi en obtained B. Sc. and M. Sc Degrees from Technical University of stanbul, Civil Engineering Faculty, Department of Reinforced Concrete in 1971. His further post-graduate studies were carried out at the University of London, Imperial College of Science and Technology. He was granted Diploma of Imperial College (D.I.C) and M. Sc. in Engineering Hydrology in 1972 and Ph. D. in stochastic hydrology in 1974. He worked in different countries such as England, Norway, Saudi Arabia and Turkey. He worked in different faculties as the head of department such as the Faculty of Earth Sciences, Hydrogeology Department; Faculty of Astronautics and Aeronautics, Meteorology Department. His main interests are hydrology, water resources, hydrogeology, hydrometeorology, hydraulics, science philosophy and history. He has published numerous (Science Citation Indexed) SCI scientific papers in different internationally top journals on various topics. He supervised many national and international students for M. Sc. and Ph. D. degrees. He holds several national (Encouragement Science Price for Young Scientist in 1978, Science Price in 1993 both from the Scientific and Technological Research Council of Turkey, etc.) and international scientific prizes and the most recent one is given as a team work due to his contribution to "Nobel Peace Prize" through his works in IPCC form 2002-2007 concerning Climate Change. He also holds Science Encouragement Prize (1978) and Science Prize (1993) from Science and Technology Center of Turkey in addition to administration and Science Prize from the King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia. He also had a chair as consultant at Prince Sultan Research Center, King Saud University, and Riyadh. He worked as consultant with the Saudi Geological Survey for three years on various water, climate change and groundwater issues. He worked also with the ARAMCO as a consultant for hydrogeology and groundwater training program development. He made numerous other national and international consulting works on water resources, climate change, renewable energy alternatives, earthquake engineering, earth sciences and similar projects. He is currently working at the Technical University of Istanbul, Civil Engineering Faculty. He is also the president of Turkish Water Foundation. He holds several national and international scientific prizes and one of the recent one is the "Nobel Peace Prize", which is given as a result of team work during his actual contributions in IPCC form 2002-2007 concerning Climate Change Impact on Fresh Water Resources.

Contenu
Introduction.- Philosophical and Logical Principles in Science.- Uncertainty and Modeling Principles.- Mathematical Modeling Principles.- Genetic Algorithm.- Artificial Neural Networks.- Artfcal Intellgence.- Machne Learnng.- Deep Learning.- Conclusion. <p