An Integration of Cloud Transform and Rough Set Theory to Induction of Decision Trees
Fundamenta Informaticae - Fundamentals of Knowledge Technology
IEEE Transactions on Circuits and Systems II: Express Briefs
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Cloud score for feature selection
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 3
Cloud model-based control strategy on cluster communication coverage for wireless sensor networks
CAR'10 Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 1
An uncertain control framework of cloud model
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
A qualitative requirement and quantitative data transform model
RSKT'10 Proceedings of the 5th international conference on Rough set and knowledge technology
Piecewise cloud approximation for time series mining
Knowledge-Based Systems
A method for trust management in cloud computing: Data coloring by cloud watermarking
International Journal of Automation and Computing
Image data field for homogeneous region based segmentation
Computers and Electrical Engineering
PRIMA'10 Proceedings of the 13th international conference on Principles and Practice of Multi-Agent Systems
Feature selection in text categorization based on cloud model
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
An Integration of Cloud Transform and Rough Set Theory to Induction of Decision Trees
Fundamenta Informaticae - Fundamentals of Knowledge Technology
How to handle uncertainties in AHP: The Cloud Delphi hierarchical analysis
Information Sciences: an International Journal
P-order normal cloud model: walking on the way between gaussian and power law distributions
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part II
Mining for geographically disperse communities in social networks by leveraging distance modularity
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Topology-aware virtual network embedding based on closeness centrality
Frontiers of Computer Science: Selected Publications from Chinese Universities
Granular Computing Based on Gaussian Cloud Transformation
Fundamenta Informaticae - To Andrzej Skowron on His 70th Birthday
A computational intelligence optimization algorithm: Cloud drops algorithm
Integrated Computer-Aided Engineering
A multi-risks group evaluation method for the informatization project under linguistic environment
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
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The information deluge currently assaulting us in the 21st century is having a profound impact on our lifestyles and how we work. We must constantly separate trustworthy and required information from the massive amount of data we encounter each day. Through mathematical theories, models, and experimental computations, Artificial Intelligence with Uncertainty explores the uncertainties of knowledge and intelligence that occur during the cognitive processes of human beings. The authors focus on the importance of natural language-the carrier of knowledge and intelligence-for artificial intelligence (AI) study. This book develops a framework that shows how uncertainty in AI expands and generalizes traditional AI. It describes the cloud model, its uncertainties of randomness and fuzziness, and the correlation between them. The book also centers on other physical methods for data mining, such as the data field and knowledge discovery state space. In addition, it presents an inverted pendulum example to discuss reasoning and control with uncertain knowledge as well as provides a cognitive physics model to visualize human thinking with hierarchy. With in-depth discussions on the fundamentals, methodologies, and uncertainties in AI, this book explains and simulates human thinking, leading to a better understanding of cognitive processes.