Titlebook: Recent Trends in Applied Artificial Intelligence; 26th International C Moonis Ali,Tibor Bosse,Jan Treur Conference proceedings 2013 Springe

ureter

Predicting Human Behavior in Crowds: Cognitive Modeling versus Neural Networks effective measures might be crucial to avoid severe consequences in case the crowd goes out of control. Recently, a number of simulation models have been developed for crowd behavior and the descriptive capabilities of these models have been shown. In this paper the aim is to judge the predictive c

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curettage

彩色的蜡笔

Computing the Consensus Permutation in Mallows Distribution by Using Genetic Algorithmsons) of . objects, finding the ranking which best . such dataset. Though different probabilistic models have been proposed to tackle this problem (see e.g. [12]), the so called . is the one that has more attentions [1]. Exact computation of the parameters of this model is an NP-hard problem [19], ju

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坦白

Approximately Recurring Motif Discovery Using Shift Density Estimationer, we propose a novel algorithm for solving this problem that can achieve performance comparable with the most accurate algorithms to solve this problem with a speed comparable to the fastest ones. The main idea behind the proposed algorithm is to convert the problem of ARM discovery into a density

slow-wave-sleep

An Online Anomalous Time Series Detection Algorithm for Univariate Data Streamscontrol charts, makes it easy to determine when a series begins to differ from other series. Empirical evidence shows that this novel online anomalous time series detection algorithm performs very well, while being efficient in terms of time complexity, when compared to approaches previously discuss

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