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Predictive Econometrics and Big Data
This book presents recent research on predictive econometrics and big data. Gathering edited papers presented at the 11th International Conference of the Thailand Econometric Society (TES2018), held in Chiang Mai, Thailand, on January 10-12, 2018, its main focus is on predictive techniques – which directly aim at predicting economic phenomena; and big data techniques – which enable us to handle the enormous amounts of data generated by modern computers in a reasonable time. The book also discusses the applications of more traditional statistical techniques to econometric problems. Econometrics is a branch of economics that employs mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. It is therefore important to develop data processing techniques that explicitly focus on prediction. The more data we have, the better our predictions will be. As such, these techniques are essential to our ability to process huge amounts of available data.
The Genus Arisaema
None
Gay Rights at the Ballot Box
From Boulder in 1974 to Maine Question 1 in 2009, the first comprehensive history of the LGBT movement's fight against anti-gay ballot measures
Integrated Uncertainty in Knowledge Modelling and Decision Making
This book constitutes the refereed proceedings of the 7th International Symposium on Integrated Uncertainty in Knowledge Modelling and Decision Making, IUKM 2019, held in Nara, Japan, in March 2019. The 37 revised full papers presented were carefully reviewed and selected from 93 submissions. The papers deal with all aspects of uncertainty modelling and management and are organized in topical sections on uncertainty management and decision support; econometrics; machine learning; machine learning applications; and statistical methods.
Behind Deep Blue
The riveting quest to construct the machine that would take on the world’s greatest human chess player—told by the man who built it On May 11, 1997, millions worldwide heard news of a stunning victory, as a machine defeated the defending world chess champion, Garry Kasparov. Behind Deep Blue tells the inside story of the quest to create the mother of all chess machines and what happened at the two historic Deep Blue vs. Kasparov matches. Feng-hsiung Hsu, the system architect of Deep Blue, reveals how a modest student project started at Carnegie Mellon in 1985 led to the production of a multimillion-dollar supercomputer. Hsu discusses the setbacks, tensions, and rivalries in the race to develop the ultimate chess machine, and the wild controversies that culminated in the final triumph over the world's greatest human player. With a new foreword by Jon Kleinberg and a new preface from the author, Behind Deep Blue offers a remarkable look at one of the most famous advances in artificial intelligence, and the brilliant toolmaker who invented it.
Intelligent Computing, Smart Communication and Network Technologies
This book constitutes the refereed proceedings of the First International Conference on Intelligent Computing, Smart Communication and Network Technologies, ICICSCNT 2023, held in Chennai, India, during April 26-27, 2023. The 36 full papers included in this book were carefully reviewed and selected from 782 submissions. The main aim of ICICSCNT 2023 is to present the state-of-the-art research innovations and results in the area of intelligent systems and advanced control technologies and real-world applications in ICT research, particularly covering autonomous systems, artificial intelligence, sensing, hardware and software implementation, soft computing, optimization, intelligent control design, intelligent system integration and control applications, and other relevant research areas.
