主题：果蝇优化算法的思维起因、理论应用与目前发展状况
报告人：潘文超博士（台湾华夏科技大学）
报告时间：2015年3月31号下午15:00
报告地点：机械大楼东楼叠240
学术报告摘要：
Up to now, the core of evolution began to be diverted to animal foraging behavior and group behavior, such as the Particle Swarm Optimization (PSO) of Prof. Eberhart and the Artificial Fish Swarm Algorithm (AFSA) proposed by Prof. Li of Chinese Mainland. The two algorithms are developed from the foraging behaviors of animal populations, thus, they are called swarm intelligence algorithms by some scholars.
The Fruit Fly Optimization Algorithm was invented by Prof. Pan, a scholar of Taiwan. It is a new method for deducing global optimization based on the foraging behavior of the fruit fly. The sensory perception of the fruit fly is better than that of other species, especially the sense of smell and vision. The olfactory organ of a fruit fly can gather various smells from the air, and even a food source 40km away. Afterwards, the fruit fly flies to the food, uses its acute vision to find the food and where its fellows gather, and then it flies in that direction,
个人介绍：
Wen-Tsao Pan works at department of Business Administration, Hwa Hsia University of Technology, Taiwan China. He's got the international Scopus Young Academic Research Award and current research interests include machine learning, data mining, financial prediction and computational intelligence. He is the international journal referee of Economic Modelling, Knowledge-Based Systems, etc. His papers have been appeared in Expert Systems with Applications, Neural Computing and Applications, etc.
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