Model Algorithm Research Articles

Generation of daily amounts of precipitation from standard climatic data: a case study for Argentina

We propose a two-part model type for generating daily precipitation from standard climatic data. The objective was to cover the needs of Argentina, excluding its southernmost tip, although the model may also be used for other regions with similar available data. The input for the model was conditioned by the climatic data edited by the National Meteorological Service of Argentina (mean weather variables over 10 years). The model's performance was tested for three cases. In Case 1, the mean monthly amount and occurrence of precipitation were both available. In Case 2, the mean monthly amount of precipitation was available, but the mean monthly occurrence of precipitation was available for a nearby weather station. In Case 3, only the monthly amount of precipitation was available. Calibration and validation of the model's algorithms was carried out using a wide range of climatic data from sites throughout the world and from all the available sites in Argentina with at least two decades of data covering the period 1950–1990. Use of the model was not recommended at sites near the Andes, beyond latitude 45°S and in Jujuy province. The excluded area represents less than 20% of Argentina's total surface area. Due to data availability, the full performance of the model was mainly evaluated in the province of Buenos Aires (the one with most engineering activity). At Bahı́a Blanca (in Buenos Aires province, 38°44′S, 62°10′W, Fig. 1) the model reliably reproduced the main features of precipitation required for agricultural, forestry and civil planning uses. In conclusion, the proposed model was very simple and fulfilled the objective of this work; furthermore, some of the results obtained could be extrapolated and applied for other regions.

Simulation of Human Visual Search in Cluttered Backgrounds

Work in progress at Georgia Tech to develop a model of human pattern perception, visual search, and detection is reviewed. The model's algorithms are based on research on low-level visual processes. Recent advances in that field have led to the development of computational models of the image processing performed by the visual system from the cornea to the striate cortex. The model also incorporates recent advances from research on visual search. The organization of the model is described, and the results of some preliminary tests are presented.

A model of shared DASD and multipathing

This paper presents a model of an I/O subsystem in which devices can be accessed from multiple CPUs and/or via alternative channel and control unit paths. The model estimates access response times, given access rates for all CPU-device combinations. Central to the model's algorithm is the estimation of the rotational position sensing (RPS) miss probabilities by means of the maximum entropy principle. Performance differences strongly favored the English-based editor.