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Hybrid Support Vector Regression and Autoregressive Integrated Moving Average Models Improved by Particle Swarm Optimization for Property Crime Rates Forecasting with Economic Indicators
المؤلفون المشاركون
Shamsuddin, Siti Mariyam
Alwee, Razana
Sallehuddin, Roselina
المصدر
العدد
المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2013-05-23
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الطب البشري
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
Crimes forecasting is an important area in the field of criminology.
Linear models, such as regression and econometric models, are commonly applied in crime forecasting.
However, in real crimes data, it is common that the data consists of both linear and nonlinear components.
A single model may not be sufficient to identify all the characteristics of the data.
The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR) and autoregressive integrated moving average (ARIMA) to be applied in crime rates forecasting.
SVR is very robust with small training data and high-dimensional problem.
Meanwhile, ARIMA has the ability to model several types of time series.
However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets.
Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models.
The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators.
The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Alwee, Razana& Shamsuddin, Siti Mariyam& Sallehuddin, Roselina. 2013. Hybrid Support Vector Regression and Autoregressive Integrated Moving Average Models Improved by Particle Swarm Optimization for Property Crime Rates Forecasting with Economic Indicators. The Scientific World Journal،Vol. 2013, no. 2013, pp.1-11.
https://search.emarefa.net/detail/BIM-1033482
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Alwee, Razana…[et al.]. Hybrid Support Vector Regression and Autoregressive Integrated Moving Average Models Improved by Particle Swarm Optimization for Property Crime Rates Forecasting with Economic Indicators. The Scientific World Journal No. 2013 (2013), pp.1-11.
https://search.emarefa.net/detail/BIM-1033482
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Alwee, Razana& Shamsuddin, Siti Mariyam& Sallehuddin, Roselina. Hybrid Support Vector Regression and Autoregressive Integrated Moving Average Models Improved by Particle Swarm Optimization for Property Crime Rates Forecasting with Economic Indicators. The Scientific World Journal. 2013. Vol. 2013, no. 2013, pp.1-11.
https://search.emarefa.net/detail/BIM-1033482
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1033482
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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