Papers are grouped in sections on logic knowledge-based systems, natural language processing, hybrid intelligent systems, robotics, computer vision and image processing, pattern recognition and data mining for decision making, and bioinformatics and medical applications.
What does HIS stand for?
HIS stands for Hybrid Intelligent Systems (International Conference)
This definition appears very frequently and is found in the following Acronym Finder categories:
- Information technology (IT) and computers
- Organizations, NGOs, schools, universities, etc.
See other definitions of HIS
We have 232 other meanings of HIS in our Acronym Attic
- Host Integration Server (Microsoft)
- Hostile Intelligence Service
- House Information System
- Houses of the Inner Sphere (MechWarrior)
- Hrvatska Izvještajna Služba (Croatian Informing Service)
- HST Instrument Servicing
- Hue, Intensity, Saturation (transformation)
- Hughes Information System
- Human Systems Integration
- Humanities and International Studies (various locations)
- Hydraulic Institute Standards
- Hypermedia Indexing Schema
- Hyperspectral Imaging Spectroscopy
- Hyperwave Information Server
- Head Injury Society of New Zealand
- Health Insurance Study-General Well-Being Schedule (Rand)
- Health Information Strategy for New Zealand
- Headquarters & Installation Support Activity
- Health Informatics Society of Australia
- Health Information Systems Architecture
Samples in periodicals archive:
9 The 310 papers of this 3-volume proceedings were first presented at the Ninth International Conference on Hybrid Intelligent Systems, held in August 2009 in Shenyang, China.
Since 2001, he is actively involved in the Hybrid Intelligent Systems (HIS); Intelligent Systems Design and Applications (ISDA) and Information Assurance and Security (IAS) series of International conferences.
The keynote and invited papers explore such topics as probabilistic graphical models in complex industrial applications, hybrid intelligent systems and cognitive robotics, natural language processing, and the application of data mining techniques as a complement to natural inflow uni-variable stochastic forecasting.