Please use this identifier to cite or link to this item:
https://elibrary.tucl.edu.np/handle/123456789/7479
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Neupane, Krishna Prasad | - |
dc.date.accessioned | 2022-01-18T05:55:05Z | - |
dc.date.available | 2022-01-18T05:55:05Z | - |
dc.date.issued | 2015-06 | - |
dc.identifier.citation | MASTER OF SCIENCE IN COMPUTER SYSTEM AND KNOWLEDGE ENGINEERING | en_US |
dc.identifier.uri | https://elibrary.tucl.edu.np/handle/123456789/7479 | - |
dc.description | Crime is an illegal act deviating from normal violation of the norms giving losses and harms for people. | en_US |
dc.description.abstract | Crime is an illegal act deviating from normal violation of the norms giving losses and harms for people. Social, psychological, economical and environmental factors are to be considered in crime issue. All these concepts affect occurrence of crime in different ways. Peoples who have role in crime prediction are police, local governments, law enforcement agencies and people exposed to crime and offenders. The spatio and temporal model is generated by using crime data for the year 2070 in Kathmandu police Headquarters. Methodology starts with obtaining clusters with K-mean, Nearest and Neighborhood(Nnh) and Spatial and Temporal Analysis clustering(STAC) algorithms. Above discussed clustering methods are compared in terms of number of crimes andland-use to select the most appropriate clustering algorithm. Crime data is divided into daily epoch, to observe spatio and temporal distribution of crime over the Kathmandu valley.To predict crime in time dimension a time series model (ARIMA) is fitted for each week day. Thespatial and temporal model of this thesis can give crime prediction in both space and time. Keywords:Spatial, temporal, ellipse, clustering, Spatial and Temporal Analysis of Crime (STAC),Euclidean distance, Geographical Information System (GIS), Autoregressive and Integrated Moving Average (ARIMA). | en_US |
dc.language.iso | en | en_US |
dc.publisher | Pulchowk Campus | en_US |
dc.subject | Spatial, Temporal, Ellipse, | en_US |
dc.subject | Euclidean Distance | en_US |
dc.title | Spatio-Temporal Crime Prediction Model in Kathmandu valley using GIS | en_US |
dc.type | Thesis | en_US |
local.institute.title | Institute of Engineering | - |
local.academic.level | Masters | en_US |
local.affiliatedinstitute.title | Pulchowk Campus | en_US |
Appears in Collections: | Electronics and Computer Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Final Thesis Report on Crime Prediction_657(069-MSCSKE-657).pdf | 1.52 MB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.