Coupled behaviors

NANO SCIENTIFIC RESEARCH CENTRE PVT.LTD.,  AMEERPET, HYD

WWW.NSRCNANO.COM, 09640648777, 09652926926

DOT NET PROJECTS LIST--2013

DOT NET 2013 IEEE PAPERS

Coupled behaviors

Abstract

Coupled behaviors refer to the activities of one too many actors who are associated with each other in terms of certain relationships. With increasing network and community-based events and applications, such as group-based crime and social network interactions, behavior coupling contributes to the causes of eventual business problems. Effective approaches for analyzing coupled behaviors are not available, since existing methods mainly focus on individual behavior analysis. This paper discusses the problem of Coupled Behavior Analysis (CBA) and its challenges. A Coupled Hidden Markov Model (CHMM)-based approach is illustrated to model and detect abnormal group-based trading behaviors. The CHMM models cater for: 1) multiple behaviors from a group of people,2) behavioral properties, 3) interactions among behaviors, customers, and behavioral properties, and 4) significant changes between coupled behaviors. We demonstrate and evaluate the models on order-book-level stock tick data from a major Asian exchange and demonstrate that the proposed CHMMs outperforms HMM-only for modeling a single sequence or combining multiple single sequences, without considering coupling relationships to detect anomalies. Finally, we discuss interaction relationships and modes between coupled behaviors, which are worthy of substantial study.

Existing System

Coupled behaviors refer to the activities of one too many actors who are associated with each other in terms of certain relationships. With increasing network and community-based events and applications, such as group-based crime and social network interactions, behavior coupling contributes to the causes of eventual business problems. Effective approaches for analyzing coupled behaviors are not available, since existing methods mainly focus on individual behavior analysis.

Proposed System

This paper discusses the problem of Coupled Behavior Analysis (CBA) and its challenges. A Coupled Hidden Markov Model (CHMM)-based approach is illustrated to model and detect abnormal group-based trading behaviors. The CHMM models cater for: 1) multiple behaviors from a group of people,2) behavioral properties, 3) interactions among behaviors, customers, and behavioral properties, and 4) significant changes between coupled behaviors. We demonstrate and evaluate the models on order-book-level stock tick data from a major Asian exchange and demonstrate that the proposed CHMMs outperforms HMM-only for modeling a single sequence or combining multiple single sequences, without considering coupling relationships to detect anomalies. Finally, we discuss interaction relationships and modes between coupled behaviors, which are worthy of substantial study.

Soft ware and hard ware requirements

Hardware Required:                            

System                        :           Pentium IV

Hard Disk                   :           80 GB

RAM                           :           512 MB

Software Required:

O/S                              :           Windows XP.

Language                    :           Asp.Net, c#.

Data Base                    :           Sql Server 2005.