Self-organizing information fusion and hierarchical knowledge discovery: a new framework using ARTMAP neural networks
نویسندگان
چکیده
منابع مشابه
Self-organizing information fusion and hierarchical knowledge discovery: a new framework using ARTMAP neural networks
Classifying novel terrain or objects from sparse, complex data may require the resolution of conflicting information from sensors working at different times, locations, and scales, and from sources with different goals and situations. Information fusion methods can help resolve inconsistencies, as when evidence variously suggests that an object’s class is car, truck, or airplane. The methods de...
متن کاملSelf-organizing Hierarchical Knowledge Discovery by an ARTMAP Image Fusion System
Classifying novel terrain or objects from sparse, complex data may require the resolution of conflicting information from sensors working at different times, locations, and scales, and from sources with different goals and situations. Information fusion methods can help resolve inconsistencies, as when evidence variously suggests that an object’s class is car, truck, or airplane. The methods de...
متن کاملDistributed Prediction and Hierarchical Knowledge Discovery by ARTMAP Neural Networks
Adaptive Resonance Theory (ART) neural networks model real-time prediction, search, learning, and recognition. ART networks function both as models of human cognitive information processing [1,2,3] and as neural systems for technology transfer [4]. A neural computation central to both the scientific and the technological analyses is the ART matching rule [5], which models the interaction betwee...
متن کاملParallel, Probabilistic, Self-organizing, Hierarchical Neural Networks
Valafar, Fararnarz. Ph.D., Purdue University, August 1993. PARALLEL PROBABILISTIC SELF-ORGANIZING HIERARCHICAL NEURAL NETWORKS. Major Professor: Okan K. Ersoy. A new neural network architecture called the Parallel Probabilistic Self-organizing Hierarchical Neural Network (PPSHNN) is introduced. The PPSHNN is designed to solve complex classification problems, by dividing the input vector space i...
متن کاملKnowledge Extraction from Web Documents Using Self- Organizing Neural Networks
Knowledge discovery is defined as non-trivial extraction of implicit, previously unknown and potentially useful information from given data [1]. Knowledge extraction from web documents deals with unstructured, free-format documents whosenumberisenormousandrapidlygrowing.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Neural Networks
سال: 2005
ISSN: 0893-6080
DOI: 10.1016/j.neunet.2004.12.003