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Fast flow analysis to compute fuzzy estimates of risk levels

E. Merlo, G. Antoniol, P.-L. Brunelle
Seventh European Conference onSoftware Maintenance and Reengineering, 2003. Proceedings.  
The definite analysis computes the minimum blocking risk levels that statements may encounter on every path, while the possible analysis computes the highest blocking risk levels encountered by statements  ...  This paper presents original flow equations to compute the definite and possible blocking risk levels for statements in source code.  ...  The authors wish to thank Jean-François Patenaude and Bruno Malenfant for their contribution to the results of this paper in terms of software and experiments.  ... 
doi:10.1109/csmr.2003.1192443 dblp:conf/csmr/MerloAB03 fatcat:rdqtd25hbnfg3en33bcabta4oe

Risk analysis and crisis response

Cengiz Kahraman
2008 Stochastic environmental research and risk assessment (Print)  
However, there is a growing acceptance that risk analysis involves the development of the probability distribution for the measure of effectiveness.  ...  The term risk analysis has different interpretations among various environments.  ...  The ninth paper proposes the application of an Artificial Neural Network (ANN) approach as a fast alternative to computational fluid dynamics models to simulate the behavior of a compartment fire.  ... 
doi:10.1007/s00477-008-0230-x fatcat:eepyezzimvapzgfez5r37wccrm

Time-based critical infrastructure dependency analysis for large-scale and cross-sectoral failures

George Stergiopoulos, Panayiotis Kotzanikolaou, Marianthi Theocharidou, Georgia Lykou, Dimitris Gritzalis
2016 International Journal of Critical Infrastructure Protection  
We employ different growth models to capture slow, linear and fast evolving effects, but instead of using static projections, the evolution of each dependency is "objectified" by a fuzzy control system  ...  These tools 55 are very useful for low-level analysis of small-scale scenarios; for example to identify the critical components within a power transmission network.  ...  level of analysis.  ... 
doi:10.1016/j.ijcip.2015.12.002 fatcat:tlzrus2zbjeqbayfdt7dki2wey

A Novel Method of Emergency Situation Evaluation for Deep-sea Based on Bayesian Network

Kun Lang, Dongsen Si, Zhihong Ma
2020 IEEE Access  
of the domain knowledge, which can reduce the computational complexity greatly. 4) Considering the fuzziness of the boundary between any two evaluation levels and the fuzziness of the corresponding relationship  ...  In order to realize the quantitative analysis of the overall emergency situation, it is necessary to combine the above reasoning results to obtain a global situation probability risk level.  ... 
doi:10.1109/access.2020.3039171 fatcat:vgy34pxjrvfz5n3igele7doxc4

A Survey On Heart Disease Prediction Using Soft Computing

Agrawal*, Pallavi A., Prof. Nitin R. Chopde
2016 Zenodo  
Especially in medical sector there is no such adequate research focus on effective analysis tool to discover and trends in data.  ...  This project intends to design and develop, diagnosis and prediction system for heart disease based on soft computing technique that is ANFIS.  ...  As work is rule based, the easy estimation of the interrelated variables can be identified to understand the approach followed by the fuzzy analysis.  ... 
doi:10.5281/zenodo.48318 fatcat:g2ymgfbxlvbyffbdnkkmu76xya

Execution Path Classification for Vulnerability Analysis and Detection [chapter]

George Stergiopoulos, Panagiotis Katsaros, Dimitris Gritzalis
2016 Communications in Computer and Information Science  
The Risk of each IB is the combination of its computed Severity and Vulnerability measurements through an aggregation operation over two fuzzy sets using a Fuzzy Logic system.  ...  Severity quantifies the danger level of an IB using static analysis and a variation of the Information Gain algorithm.  ...  and, finally, the fuzzy logic system to compute the Risk (grey and yellow colors).  Static Analysis: Static code analysis uses the Java compiler to create Abstract Syntax Trees for the AUT.  ... 
doi:10.1007/978-3-319-30222-5_14 fatcat:2eiuzug5b5gmlisudgrldjffnm

Project Management Efficiency using Soft Computing and Risk Analysis

Vinay KumarNassa, Sri Krishan Yadav
2012 International Journal of Computer Applications  
This paper quantify the project management efficiency (PME) using a Soft computing tool based fuzzy logic system (SFLS) employing risk analysis.  ...  The basic objective of the paper shall revolve around the concepts on project management, soft computing and risk analysis techniques.  ...  complex analysis like cash flow or even ROI (Return on Investment).The algorithm developed in this thesis is based upon fuzzy logic, giving it the ability to solve complex problems plagued with uncertainty  ... 
doi:10.5120/7854-1111 fatcat:lnlngt6pb5fjdnrnvg36w2rzrq

Evaluating Operational Risk Exposure Using Fuzzy umber Approach to Scenario Analysis

Antonina Durfee, Alexey Tselykh
2011 Proceedings of the 7th conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011)  
The methodology is based on the use of fuzzy numbers to express subjective probability of expert estimates.  ...  Risks and losses arising from system failure, unauthorized activity, fraud and other operational errors are postulated to be one of the primary banking risks.  ...  The paper on "Fuzzy Capital Budgeting" by Kuchta [12] that evaluated fuzzy cash flows was an inspiration of the applicability of fuzzy numbers to scenario description in operational risk.  ... 
doi:10.2991/eusflat.2011.55 dblp:conf/eusflat/DurfeeT11 fatcat:fdakz4i23zgnfbdzl4vm3m3joq

The Early Detection of Diabetes Mellitus (DM) Using Fuzzy Hierarchical Model

Rian Budi Lukmanto, E. Irwansyah
2015 Procedia Computer Science  
As a form of our efforts to contribute to the prevention of this phenomenon we propose an application of computational intelligence by using fuzzy hierarchical model that has the ability to perform early  ...  In 2013 the number of patients with Diabetes Mellitus (DM) in the world has reached 382 million. It is estimated that the prevalence will increase 55% in 2035 1 .  ...  In order to overcome that problems, it has been possible to estimating the potential of DM in someone's body with the application of computational intelligence techniques that demands efficiency and effectiveness  ... 
doi:10.1016/j.procs.2015.07.571 fatcat:3zqxwznqa5cjhbjoclgxbvd3jy

Modeling of Transient Groundwater Flow Using Fuzzy Approach

Qassem H. Jalut, Rasul M. Khalaf, Thulfikar R. Abdul-Mehdi
2013 Modern Applied Science  
The model outputs can be used as the inputs for the subsequent risk analysis, decision making-processes and evaluation.  ...  The groundwater flow problem analysis requires interval input values for the parameters, the output may be presented in terms of mean value, upper and lower bounds of the hydraulic head.  ...  The environmental-guideline-based risk (ER) and health risk (HR) due to xylene ingestion were systematically examined to obtain the general risk levels through a fuzzy rule base.  ... 
doi:10.5539/mas.v7n4p77 fatcat:6vvbn4kwr5dg5o4p4afsjtoh7m

Adaptive Contextual Risk-Based Model to Tackle Confidentiality-Based Attacks in Fog-IoT Paradigm

Satiaseelan Selvan, Manmeet Mahinderjit Singh
2022 Computers  
for the fuzzy risk model to compute the risk factor.  ...  The Internet of Things (IoT) allows billions of physical objects to be connected to gather and exchange information to offer numerous applications.  ...  Two types of risk estimation methods are created to quantify the risk, risk assessment, and fuzzy model.  ... 
doi:10.3390/computers11020016 fatcat:ryxi666hrzdi7pficiaapsnbgq

Fuzzy Online Risk Assessment for Distributed Intrusion Prediction and Prevention Systems

Kjetil Haslum, Ajith Abraham, Svein Knapskog
2008 Tenth International Conference on Computer Modeling and Simulation (uksim 2008)  
The novelty of this paper is the detailed development of Fuzzy Logic Controllers to estimate the various risk(s) that are dependent on several other variables based on the inputs from HMM modules and the  ...  To develop the fuzzy risk expert system, if-then fuzzy rules were formulated based on interviews with security experts and network administrators.  ...  Fuzzy Modeling of Risk The risk is estimated by F LC 4 and is based on the output from the three fuzzy logic controllers F LC 1 − F LC 3 .  ... 
doi:10.1109/uksim.2008.30 dblp:conf/uksim/HaslumAK08 fatcat:4f75o2woyrfprgkfdt53nzesba

Maritime Intelligent Monitoring System Based on Wireless Sensor Network and Construction of Shipping Legal System

Hong Fang
2022 Wireless Communications and Mobile Computing  
value of the index level.  ...  If the fuzzy subset method is used to determine the membership matrix in the fuzzy comprehensive evaluation, then there will be a sudden drop in the degree of membership due to a slight change in the critical  ...  Experimental Analysis of Risk Assessment Index System for Maritime Law Enforcement Comprehensive Analysis of Examples.  ... 
doi:10.1155/2022/1394946 doaj:4ad5235b781e4ca69e6d656723c9071b fatcat:mnr66cpr4zgsdp2g76t4iglvuq

A fuzzy approach to real option valuation

Christer Carlsson, Robert Fullér
2003 Fuzzy sets and systems (Print)  
In this paper we shall introduce a (heuristic) real option rule in a fuzzy setting, where the present values of expected cash flows and expected costs are estimated by trapezoidal fuzzy numbers.  ...  In their study, present values of expected costs and expected cash flows are calculated by trapezoidal fuzzy numbers.  ...  or estimating future cash flows is not stochastic in nature, and that the use of the probability theory leads to a misleading level of precision.  ... 
doi:10.1016/s0165-0114(02)00591-2 fatcat:ym2acrkm2bft7lside7jszezya

Formal Fire Safety Assessment of Passenger Ships

S. W. Kim, J. Wang, A. Wall, Y. S. Kwon
2005 The journal of the Safety and Reliability Society  
During the course of the research, it is with much gratitude and sincere respect that I acknowledge and thank my principal supervisor, Professor  ...  A fuzzy inference engine comprises the selection or development of the type/types of fuzzy membership function used to represent risk levels and fuzzy rule bases to generate fuzzy safety estimates.  ...  A fuzzy inference engine comprises the selection or development of the type/types of fuzzy membership function used to represent risk levels and fuzzy rule bases to generate fuzzy safety estimates.  ... 
doi:10.1080/09617353.2005.11690813 fatcat:mydhdfwuczefvdpvykiw4e5y4q
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