To compare two Bayesian methods (Fuzzy and Naïve) for classifying injury narratives in large administrative databases into event cause groups, a dataset of 14 000 narratives was randomly extracted from claims filed with a worker's compensation insurance provider. Two expert coders assigned one-digit and two-digit Bureau of Labor Statistics (BLS) Occupational Injury and Illness Classification ev...

Article history: Received 25 October 2011 Received in revised form November, 2, 2011 Accepted December, 1 2011 Available online 4 December 2011 The complexity of large-scale projects has led to numerous risks in their life cycle. This paper presents a new risk evaluation approach in order to rank the high risks in large-scale projects and improve the performance of these projects. It is based o...

Feature coding is an fundamental step in bag-of-words based model for image classification and have drawn increasing attention in recent works. However, there still exits ambiguity problem, and it is also sensitiveness to unusual features. To improve the stability and robustness, we introduce saliency detection and fuzzy reasoning rules to propose an novel coding scheme. In detail, saliency map...

In risk analysis, the treatment of the epistemic uncertainty associated to the probability of occurrence of an event is fundamental. Traditionally, probabilistic distributions have been used to characterize the epistemic uncertainty due to imprecise knowledge of the parameters in risk models. On the other hand, it has been argued that in certain instances such uncertainty may be best accounted ...

In the classical approach to probability theory, an event, A, is defined as a member of a o-field,,d, of subsets of a sample space ft. Thus, ifP is a normed measure over a measurable space (a,_~#), the probabibty of A is defined as P(A), the measure of.4, and is a number in the interval [0, I]. There are many real-world problems in which one or more of the basic assumptions which are implicit i...

This article introduces a method for objectively separating and validating forecast scenarios within a large multimodel ensemble for the medium-range (3–7 day) forecasts of extratropical cyclones impacting the U.S. East Coast. The method applies fuzzy clustering to the principal components (PCs) of empirical orthogonal function (EOF) analysis on mean sea level pressure (MSLP) from a 90-member c...

In a Wireless Sensor Network when an event is detected, the network traffic increases. It in turn increases the flow of data packets and congestion. Congestion in Wireless Sensor Network plays a vital role in degrading the performance of the network. Hence it necessitates, developing a novel technique to control congestion. In this paper, soft computing based congestion control technique is pro...

Focusing on the diversity, complexity and uncertainty of the third-party damage accident, the failure probability of third-party damage to urban gas pipeline was evaluated on the theory of analytic hierarchy process and fuzzy mathematics. The fault tree of third-party damage containing 56 basic events was built by hazard identification of third-party damage. The fuzzy evaluation of basic event ...

Most information retrieval systems make indirect use of human knowledge in their retrieval process. The new method we present here aims to efficiently use human knowledge directly in combination with support vector machines for clustering. As illustrated in this paper, this approach is particularly applicable to concept retrieval from soccer-related videos. The first phase consists of extractin...

The objective of this is to develop a Fuzzy aided Application layer Semantic Intrusion Detection System (FASIDS) which works in the application layer of the network stack. FASIDS consist of semantic IDS and Fuzzy based IDS. Rule based IDS looks for the specific pattern which is defined as malicious. A non-intrusive regular pattern can be malicious if it occurs several times with a short time in...