Download Analytic Support to Intelligence in Counterinsurgencies by Walter L. Perry, John Gordon PDF
By Walter L. Perry, John Gordon
Operations in Iraq and Afghanistan have proven that U.S. forces desire more-effective ideas and techniques to behavior counterinsurgency. they're going to probably face related, abnormal war strategies from destiny enemies. This monograph examines the character of the modern rebel risk and gives insights on utilizing operational research thoughts to help intelligence operations in counterinsurgencies.
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Sensor assets such as satellites, unmanned aerial vehicles (UAVs), and other forms of surveillance and reconnaissance are used to detect enemy formations and other pertinent features that enhance the IPB. Once operations begin, the most important piece of information needed to support operations is enemy intent. Whether planning defensive or offensive operations, the commander studies the enemy’s possible courses of action and charges the intelligence community to gather evidence to support the most likely of these.
5 It is also possible to employ a kernel to obtain a smooth estimate of the class density. In this case, we sum over the kernel of the distance. 6 In the data, “found caches” are clearly identified as such. Caches not found are recorded in two ways: (1) if a mission to find a cache failed to produce one, and (2) all other entries in the database. Intelligence Analysis 31 recent data so that when candidate factor values for a given observation are classified, the latest enemy tactic is accounted for.
The predictions are therefore based solely on what the enemy forces have done in the past—not on any interaction between friendly and enemy forces. Most assume an underlying randomness associated with enemy behavior. For example, an examination of past enemy attacks might reveal that the interarrival time of the attacks is exponentially distributed, leading to a Poisson distribution of the number of attacks per time interval. This is also true of the location of the attack. 7 7 The SCAN statistic, for example, is used to predict the spread of diseases.