Distance Prediction for Commercial Serial Crime Cases Using Time Delay Neural Networks
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2015, Vol 6, Issue 11
Abstract
The prediction of the next serial criminal time is important in the field of criminology for preventing the recurring actions of serial criminals. In the associated dynamic systems, one of the main sources of instability and poor performances is the time delay, which is commonly predicted based on nonlinear methods. The aim of this study is to introduce a dynamic neural network model by using nonlinear autoregressive time series with exogenous (external) input (NARX) and Back Propagation Through Time (BPTT), which is verified intensively with MATLAB to predict and model the crime times for the next distance of serial cases. Recurrent neural networks have been extensively used for modeling of nonlinear dynamic systems. There are different types of recurrent neural networks such as Time Delay Neural Networks (TDNN), layer recurrent networks, NARX, and BPTT. The NARX model for the two cases of input- output modeling of dynamic systems and time series prediction draw more attention. In this study, a comparison of two models of NARX and BPTT used for the prediction of the next serial criminal time illustrates that the NARX model exhibits better performance for the prediction of serial cases than the BPTT model. Our future work aims to improve the NARX model by combining objective functions.
Authors and Affiliations
Anahita Ghazvini, Siti Abdullah, Mohammed Abdullah, Md Junoh, Zainal Kasim
Keywords
Related Articles
- EP ID EP106583
- DOI 10.14569/IJACSA.2015.061101
- Views 92
- Downloads 0
Corporate Responsibility in Combating Online Misinformation
In the age of mass information and misinformation, the corporate duty of developers of browsers, social media, and search engines are falling short of the minimum standards of responsibility. The tools and technologies a...
Tracking Items Through Rfid and Solving Heterogeneity Problems During a Collaboration Between Port Companies
In this article, we are proposing an architecture that enables improvements in various steps of the collaboration process between different port companies, based on the use of ontologies, multi-agent systems and RFIDs. T...
Applying Machine Learning Techniques for Classifying Cyclin-Dependent Kinase Inhibitors
The importance of protein kinases made them a target for many drug design studies. They play an essential role in cell cycle development and many other biological processes. Kinases are divided into different subfamilies...
Spectral Efficiency of Massive MIMO Communication Systems with Zero Forcing and Maximum Ratio Beamforming
The massive multiple-input-multiple-output (MIMO) is a key enabling technology for the 5G cellular communication systems. In massive MIMO (M-MIMO) systems few hundred numbers of antennas are deployed at each base station...
Detection of SQL Injection Using a Genetic Fuzzy Classifier System
SQL Injection (SQLI) is one of the most popular vulnerabilities of web applications. The consequences of SQL injection attack include the possibility of stealing sensitive information or bypassing authentication procedur...