|
Special Session Special sessions and organizers:
Organiser: Kang Li, Queen's University Belfast Energy conservation and pollution reduction have been receiving increased attention over recent years. More efficient use of energy in the energy-intensive processes can reduce the cost for the enterprises, as well as protect our climate and environment. This special session will focus on the latest development and applications of intelligent computing techniques for energy conservation, pollution reduction and related topics. Topics of interest include, but are not limited to:
Chair: Dr Marion McAfee, Queen's University Belfast and Sligo IT. Process industries such as petrochemical and chemical, refining, water and sewage treatment and food processing are vitally important to our quality of life but currently account for the majority of industrial energy demand. It is important that these industries initiate and sustain actions to reduce energy consumption, which in turn achieves capital and operational cost savings and maximizes profits. This special session will include recent advances and applications on the following areas:
Organisers: Weidong Chen, Shanghai Jiaotong University Service robots covers a variety of applications. This special session will select papers on various advanced intelligent computing techniques in service robots, including path planning, data fusion, intelligent control, mechatronics, etc.
Organisers: Prof Guangzhou Zhao, Zhejiang University Support Vector Machine (SVM) and related kernel methods are currently very active research areas within neural computation and machine learning. It has been successfully applied to numerous applications ranging from face identification, text categorization to engine knock detection bioinformatics and database marketing. The aim of this special session is to present new perspectives and new directions in SVM and the applications in signal process and pattern recognition.
Organisers: Prof Guangzhao Zhao, Zhejiang University A great number of mechatronic applications require advanced motion control techniques, realized by integrating smart control strategies, high precision sensing, and innovative actuators. In the past decade, several trends have been at work to drive the use of complex motor control techniques. The most important trend is the desire for lower energy consumption and the need for higher performance. This special session will provide a great opportunity for researchers active in the field of advanced motion control to discuss current developments and future perspectives on motion control technology. The topics include, but are not limited to:
Organisers: Prof Minrui Fei, Shanghai University In recent years, a great deal of research has focused on Networked Control System (NCS). NCS is now used in many fields such as homeland security, agriculture, energy management, intelligent transportation and traffic engineering, logistics, warehouse management, disaster management, healthcare delivery, military, smart buildings, and manufacturing. It is widely recognized that NCS is a very challenging and promising research field. The session is intended to provide a forum for academic researchers and industrial engineering to present their recent research, and development in NCS. It is hoped that the special session will attract high quality contributions from, but not limited to, the following topics:
Organisers: Prof T. C. Yang, Unirersity of Sussex Over the past several decades, significant changes in computing technology, along with widespread deregulation of electricity industries, have impacted on power plant operations while affording academics and engineers the opportunity to introduce monitoring and plant-wide control schemes which were previously unfeasible. This session aims to present recent approaches to intelligent modeling, simulation and control in power generation and power networks. Researchers from both computational intelligence as well as power generation fields are invited to submit papers. Areas of interest include, but are not limited to:
|
|
|