This book mainly focuses on the multi-media energy prediction technology and optimization methods of iron and steel enterprises. The technical methods adopted include swarm intelligence algorithm, neural network, reinforcement learning, and so on. Energy saving and consumption reduction in iron and steel enterprises have always been a research hotspot in the field of process control. This book considers the multi-media energy balance problem from the perspective of system, studies the energy flow and material flow in iron and steel enterprises, and provides energy optimization methods that can be used for planning, prediction, and scheduling under different production scenes. The main audience of this book is scholars and graduate students in the fields of control theory, applied mathematics, energy optimization, etc.

This book focuses on the implementation, evaluation and application of DNA/RNA-based genetic algorithms in connection with neural network modeling, fuzzy control, the Q-learning algorithm and CNN deep learning classifier. It presents several DNA/RNA-based genetic algorithms and their modifications, which are tested using benchmarks, as well as detailed information on the implementation steps and program code. In addition to single-objective optimization, here genetic algorithms are also used to solve multi-objective optimization for neural network modeling, fuzzy control, model predictive control and PID control. In closing, new topics such as Q-learning and CNN are introduced. The book offers a valuable reference guide for researchers and designers in system modeling and control, and for senior undergraduate and graduate students at colleges and universities.

This book focuses on the implementation, evaluation and application of DNA/RNA-based genetic algorithms in connection with neural network modeling, fuzzy control, the Q-learning algorithm and CNN deep learning classifier. It presents several DNA/RNA-based genetic algorithms and their modifications, which are tested using benchmarks, as well as detailed information on the implementation steps and program code. In addition to single-objective optimization, here genetic algorithms are also used to solve multi-objective optimization for neural network modeling, fuzzy control, model predictive control and PID control. In closing, new topics such as Q-learning and CNN are introduced. The book offers a valuable reference guide for researchers and designers in system modeling and control, and for senior undergraduate and graduate students at colleges and universities.

This book reviews advances in cutting-edge micro-/nano-electrometers, and discusses the technological challenges involved in their practical implementation. The detection of electrostatic charge has a wide range of applications in ionization chambers, bio-analyte and aerosol particle instruments, mass spectrometers, scanning tunneling microscopes, and even quantum computers. Designing micro-/nano-electrometers (also known as charge sensors) for electrometry is considered vital because of the charge sensitivity and resolution issues at micro-/nano-scales. The remarkably dynamic microelectromechanical systems (MEMSs)/nanoelectromechanical systems (NEMSs), and advances in solid-state electronics, hold considerable potential for the design and fabrication of extremely sensitive charge sensors.

Mechanics of Composite, Hybrid, and Multifunctional Materials, Volume 7 of the Proceedings of the 2016 SEM Annual Conference & Exposition on Experimental and Applied Mechanics, the seventh volume of ten from the Conference, brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on a wide range of areas, including: Recycled-Constituent Composites Nano and Particulate Composites Damage Detection and Non-Destructive Evaluation of Composites Fracture and Fatigue Novel Developments in Composites Additive Manufacturing of Composites Mechanics of Graphene & Graphene Oxide Smart Materials Novel Developments in Composites Manufacturing and Joining of Composites

Experimental and Applied Mechanics, Volume 4 of the Proceedings of the 2016 SEM Annual Conference & Exposition on Experimental and Applied Mechanics, the fourth volume of ten from the Conference, brings together contributions to important areas of research and engineering. The collection presents early findings and case studies on a wide range of topics, including: Hybrid Experimental & Computational Techniques Advanced Experimental Mechanics Methods Integration of Models & Experiments Soft Materials Education & Research in Progress Applications