Clustering of Sedimentary Basins Using Associative Neural memories (ART2)
Journal Title: International Journal on Computer Science and Engineering - Year 2011, Vol 3, Issue 8
Abstract
Associative Memory (AM) research covers technologies enabling implementation of associative memory which enables thought process and links previous experience to novel situations. Each neural network system requires a memory for storing and retrieval of associated concepts, based on a combination of the base concept and the context. Adaptive Resonance Theory is a kind of associative neural memory model as unsupervised neural network model. The aim of this article is to present identification and recognition of Magneto-telluric data for sedimentary basins using associative neural memory with Adaptive Resonance Theory (ART2).The ART2 is an unsupervised learning algorithm where the network is provided with inputs but not with desired outputs. The system itself to decide what features it will use to group the input data. Several sets of data consisting of 17 phases and 17 apparent resistivity values and their respective tag values are given. These sets of data are used for training the network, and other sets of data are used to test the network for clustering. The testing will result in the approximate identification of the data patterns with tag value of 1 where there is sediment of hydrocarbon and a tag value of 0 where there is no sediment of hydrocarbon in the given data set. The recognition rate in the proposed system lies between 90% and 100%.
Authors and Affiliations
LAKSHMIPRASAD BOPPANA , B. POORNA SATYANARAYANA
Keywords
Related Articles
- EP ID EP113732
- DOI -
- Views 104
- Downloads 0
CBIR Using Kekre’s Transform over Row column Mean and Variance Vectors
We see the advancement in image acquisition technologies and storage systems which always encourages us to design a sophisticated system to retrieve the images effectively. In this paper, we describe the novel approach f...
Cost Effective Cloud Environment Setup to Secure Corporate Data
In recent years ad-hoc parallel processing has emerged to be one among the killer applications for Infrastructure-as-a-Service (IaaS) clouds. Major Cloud computing firms have began to integrate frameworks for parallel pr...
Automatic Recommendation of Web Pages in Web Usage Mining
With the rising growth of Web users, Web-based organizations are keen to analyze the on-line browsing behavior of the users in their web site and learn (identify) their interest instantly in a session. The analysis of th...
Non-Linear Segmentation of Touched Roman Characters Based on Genetic Algorithm
The segmentation accuracy of Roman cursive characters, especially touched characters, is essential for the high performance of Optical Character Recognition Systems. This paper presents a new approach for non-linear seg...
SIMULATION BASED DESIGN OF RETENTION TANK OF MODULAR CONTROLLER DISCHARGE SYSTEM (MCDS) FOR TRAIN COACHES
As increasingly more complex embedded systems are being considered for design, their design and validation is proving a Herculean task. Innovative applications demand stringent requirements, necessitating improvements in...