Transit Shift Response Analysis Through Fuzzy Rule Based-Choice Model: A Case Study of Indian Metropolitan City

Software birthmark is a unique quality of software to detect software theft. Comparing birthmarks of software can tell us whether a program or software is a copy of another. Software theft and piracy are rapidly increasing problems of copying, stealing, and misusing the software without proper permission, as mentioned in the desired license agreement. The estimation of birthmark can play a key role in understanding the effectiveness of a birthmark. In this paper, a new technique is presented to evaluate and estimate software birthmark based on the two most sought-after properties of birthmarks, that is, credibility and resilience. For this purpose, the concept of soft computing such as probabilistic and fuzzy computing has been taken into account and fuzzy logic is used to estimate properties of birthmark. The proposed fuzzy rule based technique is validated through a case study and the results show that the technique is successful in assessing the specified properties of the birthmark, its resilience and credibility. This, in turn, shows how much effort will be required to detect the originality of the software based on its birthmark.

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Assessing flood vulnerability using a rule-based fuzzy system

Water Science & Technology ◽

10.2166/wst.2012.346 ◽

2012 ◽

Vol 66 (8) ◽

pp. 1766-1773 ◽

Cited By ~ 1

Author(s):

J. Yazdi ◽

S. A. A. S. Neyshabouri

Keyword(s):

Fuzzy Rule ◽

Vulnerability Analysis ◽

Human Knowledge ◽

Small Watershed ◽

Flood Vulnerability ◽

Rule Based ◽

Rule Based System ◽

Vulnerability Map ◽

Flood Prone Areas

Population growth and urbanization in the last decades have increased the vulnerability of properties and societies in flood-prone areas. Vulnerability analysis is one of the main factors used to determine the necessary measures of flood risk reduction in floodplains. At present, the vulnerability of natural disasters is analyzed by defining the various physical and social indices. This study presents a model based on a fuzzy rule-based system to address various ambiguities and uncertainties from natural variability, and human knowledge and preferences in vulnerability analysis. The proposed method is applied for a small watershed as a case study and the obtained results are compared with one of the index approaches. Both approaches present the same ranking for the sub-basin's vulnerability in the watershed. Finally, using the scores of vulnerability in different sub-basins, a vulnerability map of the watershed is presented.

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Fuzzy rule-based model to optimize outflow in single reservoir operation

MATEC Web of Conferences ◽

10.1051/matecconf/201927004015 ◽

2019 ◽

Vol 270 ◽

pp. 04015

Author(s):

Edy Anto Soentoro ◽

Nina Pebriana

Keyword(s):

Water Availability ◽

Reservoir Operation ◽

Life Experiences ◽

Real Life ◽

Fuzzy Rule ◽

Basic Pattern ◽

Output Data ◽

Data Set ◽

Rule Based

Reservoir operations, especially those which regulate the outflow (release) volume, are crucial for the fulfillment of the purpose to build the reservoir. To get the best results, outflow (release) discharges need to be optimized to meet the objectives of the reservoir operation. A fuzzy rule-based model was used in this study because it can deal with uncertainty constraints and objects without clear or well-defined boundaries. The objective of this study is to determine the maximum total release volume based on water availability (i.e., a monthly release is equal to or more than monthly demand). The case study is located at Darma reservoir. A fuzzy rule-based model was used to optimize the monthly release volume, and the result was compared with that of NLP and the demand. The Sugeno fuzzy method was used to generate fuzzy rules from a given input-output data set that consisted of demand, inflow, storage, and release. The results of this study showed that the release of Sugeno method and the demand have the same basic pattern, in which the release fulfill the demand. The overall result showed that the fuzzy rule-based model with Sugeno method can be used for optimization based on real-life experiences from experts that are used to working in the field.

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A case study on the application of instance selection techniques for Genetic Fuzzy Rule-Based Classifiers

2012 IEEE International Conference on Fuzzy Systems ◽

10.1109/fuzz-ieee.2012.6251191 ◽

2012 ◽

Cited By ~ 2

Author(s):

Bruno Giglio ◽

Francesco Marcelloni ◽

Michela Fazzolari ◽

Rafael Alcala ◽

Francisco Herrera

Keyword(s):

Fuzzy Rule ◽

Instance Selection ◽

Rule Based

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Permeability prediction in shaly formations: The fuzzy modeling approach

Geophysics ◽

10.1190/1.1484526 ◽

2002 ◽

Vol 67 (3) ◽

pp. 817-829 ◽

Cited By ~ 6

Author(s):

Jose Finol ◽

Xu‐Dong D. Jing

Keyword(s):

Clustering Algorithm ◽

Fuzzy Inference ◽

Fuzzy Rule ◽

Learning Task ◽

Well Log ◽

Rule Based ◽

Maracaibo Basin ◽

Core Permeability ◽

Rule Based Approach

This paper shows how fuzzy rule‐based systems help predict permeability in sedimentary rocks using well‐log responses. The fuzzy rule‐based approach represents a global nonlinear relationship between permeability and a set of input log responses as a smooth concatenation of a finite family of flexible local submodels. The fuzzy inference rules expressing the local input‐output relationships are obtained automatically from a set of observed measurements using a fuzzy clustering algorithm. This approach simplifies the process of constructing fuzzy systems without much computation effort. The benefits of the methodology are demonstrated with a case study in the Lake Maracaibo basin, Venezuela. Special core analyses from three early development wells provide the data for the learning task. Core permeability and well‐log data from a fourth well provide the basis for model validation. Numerical simulation results show that the fuzzy system is an improvement over conventional empirical methods in terms of predictive capability.

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