Hongwei Mo

Hongwei Mo was born in 1973. He receiced his BS and PhD degrees from Automation College of Harbin Engineering University in 2002 and 2005. He is presently a professor of Automation College of Harbin Engineering University. He was a visiting Scholar of UCDavis (California, USA) from 2003-2004. His main research interests include, natural computing, artificial immune systems, data mining, intelligent systems, and artificial intelligence. He has published 30 papers and two books on AIS. He is a director at the Biomedicine Engineering Academy of Heilongjiang Province, commissioner of the China Neural Network Committee, and a senior member of the Computer Academy of China. He is secretary-general chairman and associate chairman of the organization committee of the 16th China Neural Network Conference and 1st Conference of Special Topic on Artificial Immune Systems, a member of the program committee of the 2nd International Conference on Natural Computing, Fuzzy Systems, and Knowledge Discovery (ICNC-FSKD2006), 1st International Conference on Rough Sets and Knowledge Discovery, 6th International Conference on Simulation Learning and Evolution, 13th IEEE International Conference on Mechanics and Automation(ICMA2007), Biology Inspired Computing 2008, and numerous other conferences. He served as a member of the editorial board for the International Journal on Information Technology Research.

Publications

Magnetotactic Bacteria Optimization Algorithm (MBOA) for Function Optimization: MBOA Based on Four Best-Rand Pairwise Schemes
Lili Liu, Hongwei Mo. © 2018. 22 pages.
Magnetotactic bacteria is a kind of prokaryotes with the characteristics of magnetotaxis. Magnetotactic bacteria optimization algorithm (MBOA) is an optimization algorithm based...
Image Segmentation Based on Bio-Inspired Optimization Algorithms
Hongwei Mo, Lifang Xu, Mengjiao Geng. © 2015. 26 pages.
This chapter addresses the issue of image segmentation by clustering in the domain of image processing. Fuzzy C-Means is a widely adopted clustering algorithm. Bio-inspired...
Magnetotactic Bacteria Optimization Algorithm Based On Four Best-Rand Pairwise Schemes
Hongwei Mo, Lifang Xu, Lili Liu, Yanyan Zhao. © 2014. 19 pages.
Magnetotactic bacteria optimization algorithm (MBOA) is an optimization algorithm based on the characteristics of magnetotactic bacteria, which is a kind of polyphyletic group of...
Image Segmentation Based on Bacterial Foraging and FCM Algorithm
Hongwei Mo, Yujing Yin. © 2013. 14 pages.
This paper addresses the issue of image segmentation by clustering in the domain of image processing. The clustering algorithm taken account here is the Fuzzy C-Means which is...
Research of Biogeography-Based Multi-Objective Evolutionary Algorithm
Hongwei Mo, Zhidan Xu. © 2013. 11 pages.
Biogeography-based optimization algorithm (BBO) is an optimization algorithm inspired by the migration of animals in nature. A new multi-objective evolutionary algorithm is...
Research of Biogeography-Based Multi-Objective Evolutionary Algorithm
Hongwei Mo, Zhidan Xu. © 2011. 11 pages.
Biogeography-based optimization algorithm (BBO) is an optimization algorithm inspired by the migration of animals in nature. A new multi-objective evolutionary algorithm is...
Image Segmentation Based on Bacterial Foraging and FCM Algorithm
Hongwei Mo, Yujing Yin. © 2011. 13 pages.
This paper addresses the issue of image segmentation by clustering in the domain of image processing. The clustering algorithm taken account here is the Fuzzy C-Means which is...
Handbook of Research on Artificial Immune Systems and Natural Computing: Applying Complex Adaptive Technologies
Hongwei Mo. © 2009. 634 pages.
Today, nature is used as a source of inspiration for the development of new techniques for solving complex problems in various domains, from engineering to biology, with...
Journal of Information Technology Research (JITR)
Wen-Chen Hu. Est. 2008.
The Journal of Information Technology Research (JITR) presents comprehensive interdisciplinary and refereed research on the most emerging and breakthrough areas of information...