Dynamic Cellular Automata Based Epidemic Spread Model for Population in Patches with Movement

Epidemiology is the study of spread of diseases among the group of population. If not controlled properly, the epidemic would cause an enormous number of problems and lead to pandemic situation. Here in this paper we consider the situation of populated areas where people live in patches. A dynamic cellular automata model for population in patches is being proposed in this paper. This work not only explores the computing power of cellular automata in modeling the epidemic spread but also provides the pathway in reduction of computing time when using the dynamic cellular automata model for the patchy population when compared to the static cellular automata which is used for a nonpatchy homogeneous population. The variation of the model with movement of population among the patches is also explored which provides an efficient way for evacuation planning and vaccination of infected areas.

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Epidemic Spread Modeling with Time Variant Infective Population Using Pushdown Cellular Automata

Journal of Computational Environmental Sciences ◽

10.1155/2014/769064 ◽

2014 ◽

Vol 2014 ◽

pp. 1-10

Author(s):

Senthil Athithan ◽

Vidya Prasad Shukla ◽

Sangappa Ramachandra Biradar

Keyword(s):

Cellular Automata ◽

Real Time ◽

Disease Spread ◽

Abu Dhabi ◽

Epidemic Spread ◽

Time Data ◽

Cellular Automata Model ◽

Spread Model ◽

The World ◽

Real Time Data

The world without a disease is a dream of any human being. The disease spread if not controlled could cause an epidemic situation to spread and lead to pandemic. To control an epidemic we need to understand the nature of its spread and the epidemic spread model helps us in achieving this. Here we propose an epidemic spread model which considers not only the current infective population around the population but also the infective population which remain from the previous generations for computing the next generation infected individuals. A pushdown cellular automata model which is an enhanced version of cellular automata by adding a stack component is being used to model the epidemic spread and the model is validated by the real time data of H1N1 epidemic in Abu Dhabi.

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Voting Rule Based Cellular Automata Epidemic Spread Model for Leptospirosis

Indian Journal of Science and Technology ◽

10.17485/ijst/2015/v8i4/60441 ◽

2015 ◽

Vol 8 (4) ◽

pp. 337

Author(s):

Senthil Athithan ◽

Vidya Prasad Shukla ◽

Sangappa Ramachandra Biradar

Keyword(s):

Cellular Automata ◽

Epidemic Spread ◽

Rule Based ◽

Voting Rule ◽

Spread Model

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A symmetry based anomaly detection in brain using cellular automata for computer aided diagnosis

Indonesian Journal of Electrical Engineering and Computer Science ◽

10.11591/ijeecs.v14.i1.pp471-477 ◽

2018 ◽

Vol 14 (1) ◽

pp. 471

Author(s):

Nisha V M ◽

L Jeganathan

Keyword(s):

Cellular Automata ◽

Early Stage ◽

Computer Aided Diagnosis ◽

Brain Images ◽

Cellular Automata Model ◽

Computing Power ◽

Diagnosis System ◽

Proposed Model ◽

Computer Aided ◽

Aided Diagnosis

Computer aided diagnosis (CAD) is an advancing technology in medical imaging. CAD acts as an additional computing power for doctors to interpret the medical images which leads to a more accurate diagnosis of the disease.CAD system increases the chances of detection of brain lesions by assisting the physicians in decreasing the observational oversight in the early stage of diseases.This paper focuses on the development of a cellular automata based model to find the anomaly prone areas in human brains.Because of the bilateral symmetric nature of human brain, a symmetry based cellular automata model is proposed.An algorithm is designed based on the proposed model to detect the anomaly prone areas in brain images. The proposed model can be a standalone model or it can be incorporated to a sophisticated computer aided diagnosis system. By incorporating asymmetry information into a computer aided diagnosis system, enhances its performance in identifying the anomalies exists in bilaterally symmetrical brain images.

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Comparative Analysis of Different Driving Rules in Freeways Based on Cellular Automata Model and Analytic Hierarchy Process

CICTP 2017 ◽

10.1061/9780784480915.399 ◽

2018 ◽

Author(s):

Guizheng Zhang ◽

Jianhong Ye ◽

Yizhe Wang ◽

Weiwei Jing

Keyword(s):

Comparative Analysis ◽

Cellular Automata ◽

Analytic Hierarchy Process ◽

Analytic Hierarchy ◽

Cellular Automata Model ◽

Hierarchy Process

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Synergistic cellular automata model for dissemination of Internet public opinion

Journal of Computer Applications ◽

10.3724/sp.j.1087.2012.00399 ◽

2013 ◽

Vol 32 (2) ◽

pp. 399-402

Author(s):

Wei FANG ◽

Liu-jin HE ◽

Liang-tu SONG

Keyword(s):

Public Opinion ◽

Cellular Automata ◽

Cellular Automata Model

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A GIS-Based Irregular Cellular Automata Model of Land-Use Change

Environment and Planning B Planning and Design ◽

10.1068/b32098 ◽

2007 ◽

Vol 34 (4) ◽

pp. 708-724 ◽

Cited By ~ 87

Author(s):

Daniel Stevens ◽

Suzana Dragićević

Keyword(s):

Land Use ◽

Cellular Automata ◽

Land Use Change ◽

Spatial Data ◽

Cellular Automata Model ◽

Population Growth Rates ◽

Asynchronous Development ◽

Canadian City ◽

Ca Model ◽

Developing Area

This study proposes an alternative cellular automata (CA) model, which relaxes the traditional CA regular square grid and synchronous growth, and is designed for representations of land-use change in rural-urban fringe settings. The model uses high-resolution spatial data in the form of irregularly sized and shaped land parcels, and incorporates synchronous and asynchronous development in order to model more realistically land-use change at the land parcel scale. The model allows urban planners and other stakeholders to evaluate how different subdivision designs will influence development under varying population growth rates and buyer preferences. A model prototype has been developed in a common desktop GIS and applied to a rapidly developing area of a midsized Canadian city.

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