Predicting Behavioural Evolution on a Graph-Based Model
Advances in Networks
Volume 3, Issue 2, September 2015, Pages: 8-21
Received: Jul. 11, 2015; Accepted: Jul. 23, 2015; Published: Aug. 5, 2015
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Authors
Arnold Adimabua Ojugo, Dept. of Math/Computer, Federal University of Petroleum Resources Effurun, Delta State, Nigeria
Rume Elizabeth Yoro, Dept. of Computer Science, Delta State Polytechnic, Ogwashi-Uku, Delta State, Nigeria
Andrew Okonji Eboka, Dept. of Computer Sci. Education, Federal College of Education (Technical), Asaba, Delta State, Nigeria
Mary Oluwatoyin Yerokun, Dept. of Computer Sci. Education, Federal College of Education (Technical), Asaba, Delta State, Nigeria
Christiana Nneamaka Anujeonye, Dept. of Computer Sci. Education, Federal College of Education (Technical), Asaba, Delta State, Nigeria
Fidelia Ngozi Efozia, Prototype Engineering Development Institute, Fed. Ministry of Science Technology, Osun State, Nigeria
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Abstract
Corruption is the bane of any economy. Its malady cuts across religious, socio-economic and political system of Nigeria. With a fast and contagious spread through the nation’s socio-economic and political strata, its adverse malignant effect is today, difficult to treat. This study models its contagion via an agent-based graph-diffusion model. Graphs are now quickly becoming the dominant life-form of most activities in a society, with human actors as nodes. Actors have ties that bind them to others via interaction as they form a social graph that analyzes the agent’s local feats via interaction to impact on the society as a global structure. Study explores the graph’s rich connective patterns and personal-networks as actors influence each other, so that graph’s behaviour evolves to orchestrate a relationship in probabilities of observed data and recognize patterns that aid decision making via its convergence to predict the expected number of final adopters as its optimal solution in a multi-peak function.
Keywords
Stochastic, Immunize, Network, Vertices, SIS, SIR, Function, Search Space, Solution, Models
To cite this article
Arnold Adimabua Ojugo, Rume Elizabeth Yoro, Andrew Okonji Eboka, Mary Oluwatoyin Yerokun, Christiana Nneamaka Anujeonye, Fidelia Ngozi Efozia, Predicting Behavioural Evolution on a Graph-Based Model, Advances in Networks. Vol. 3, No. 2, 2015, pp. 8-21. doi: 10.11648/j.net.20150302.11
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