Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering

Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering

Dookie Kim (Kunsan National University, South Korea), Sanjiban Sekhar Roy (VIT University, India), Tim Länsivaara (Tampere University of Technology, Finland), Ravinesh Deo (University of Southern Queensland, Australia) and Pijush Samui (National Institute of Technology Patna, India)
Projected Release Date: June, 2018|Copyright: © 2018 |Pages: 576
ISBN13: 9781522547662|ISBN10: 1522547665|EISBN13: 9781522547679|DOI: 10.4018/978-1-5225-4766-2

Description

The disciplines of science and engineering rely heavily on the forecasting of prospective constraints for concepts that have not yet been proven to exist, especially in areas such as artificial intelligence. Obtaining quality solutions to the problems presented becomes increasingly difficult due to the number of steps required to sift through the possible solutions, and the ability to solve such problems relies on the recognition of patterns and the categorization of data into specific sets. Predictive modeling and optimization methods allow unknown events to be categorized based on statistics and classifiers input by researchers.

The Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering is a critical reference source that provides comprehensive information on the use of optimization techniques and predictive models to solve real-life engineering and science problems. Through discussions on techniques such as robust design optimization, water level prediction, and the prediction of human actions, this publication identifies solutions to developing problems and new solutions for existing problems, making this publication a valuable resource for engineers, researchers, graduate students, and other professionals.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Artificial Neural Network Use
  • Degradation-Based Modeling
  • Hybrid Models
  • Multiscale Modeling
  • Particle Swarm Optimization
  • Robust Design Optimization
  • Slope Stability Analysis
  • Water Level Prediction

Table of Contents and List of Contributors

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Author(s)/Editor(s) Biography

Dookie Kim received his Bachelor degree in Civil and Environmental Engineering from Korea University in 1993, and he earned his Master and Ph.D. degrees in Civil Engineering from Korea Advanced Institute of Science and Technology (KAIST) in 1995 and 1999 respectively. He is as a post-doctoral researcher and at Korea Atomic Energy Research Institute (KAERI), University of California, and Irvine (UCI) and as a senior researcher at UNISON Co. Ltd in September 1999 - February 2003. Since March 2003, Dr. Kim has been teaching, researching, and consulting at the Department of Civil Engineering, Kunsan National University (KNU), Jeonbuk, Korea.
Pijush Samui is working as an associate professor in civil engineering department at NIT Patna, India. He graduated in 2000, with a B.Tech. in Civil Engineering from Indian Institute of Engineering Science and Technology, Shibpur, India. He received his M.Sc. in Geotechnical Earthquake Engineering from Indian Institute of Science, Bangalore, India (2004). He holds a Ph.D. in Geotechnical Earthquake Engineering (2008) from Indian Institute of Science, Bangalore, India. He was a postdoctoral fellow at University of Pittsburgh (USA) (2008-2009) and Tampere University of Technology (Finland) (2009- 2010). At University of Pittsburgh, he worked on design of efficient tool for rock cutting and application of Support Vector Machine (SVM) in designing of geostructure. At Tampere University of Technology, he worked on design of railway embankment, slope reliability and site characterization. In 2010, Dr. Pijush joined in the Center for Disaster Mitigation and Management at VIT University as an Associate Professor. He was promoted to a Professor in 2012. Dr. Pijush’s research focuses on the application of Artificial Intelligence for designing civil engineering structure, design of foundation, stability of railway embankment, reliability analysis, site characterization, and earthquake engineering. Dr. Pijush is the recipient of the prestigious CIMO fellowship (2009) from Finland, for his integrated research on the design of railway embankment. He was awarded Shamsher Prakash Research Award (2011) by IIT Roorkee for his innovative research on the application of Artificial Intelligence in designing civil engineering structure. He wasselected asthe recipient of IGS Sardar Resham Singh Memorial Award – 2013 for his innovative research on infrastructure project. He was elected Fellow of International Congress of Disaster Management in 2010. He served as a guest in disaster advance journal. He also serves as an editorial board member in several international journals. Dr. Pijush is active in a variety of professional organizations including the Indian Geotechnical Society, Indian Science Congress, Institution of Engineers, World federation of Soft Computing, and Geotechnical Engineering for Disaster Mitigation and Rehabilitation. He has organized numerous workshops and conferences on the applications of artificial intelligence in civil engineering design.