Distributed Evolutionary Programming Formulation of Support Vector Machines (SVMS) for Detecting and Classifying Organophosphate Nerve Agents
This paper extends the research described in Land et al. (2002) to include the following: (1) establishing SVM classification performance in the detection of organophosphates nerve agents using four separate model stimulant compounds, and (2) upgrading the architecture of EP SVMs to run on multiple machines simultaneously by using a client-server architecture (Distributed EP). Due to the increased threats of chemical and biological weapons of mass destruction (WMD) by international terrorist organizations, a significant effort is underway to develop tools that can be used to detect and effectively combat biochemical warfare. Furthermore, recent events have highlighted awareness that chemical and biological agents (CBAs) may become the preferred, cheap alternative WMD, because these agents can effectively attack large populations while leaving infrastructures intact. Despite the availability of numerous sensing devices, intelligent hybrid sensors that can detect and degrade CBAs are virtually nonexistent.
Land, W. H., M. J. Embrechts, A. Wanekaya, O. Sadik, L. Wong, M. Uematsu. "Distributed Evolutionary Programming Formulation of Support Vector Machines (SVMS) for Detecting and Classifying Organophosphate Nerve Agents." In Intelligent Engineering Systems Through Artificial Neural Networks 13 (2003): 175-180.
Intelligent Engineering Systems Through Artificial Neural Networks