Using fuzzy cognitive maps to identify multiple causes in troubleshooting systems

Perusich, Karl

doi:10.3233/ica-2008-15208

Cited by 24 publications

(9 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, if feature extraction function is not influenced against illuminance changes using an effective research [10], a tracking function will become more robust. Furthermore, if trouble shooting function is added in the system by using an effective research [13], the maintainability of the system will be improved. Therefore, we are considering the research to improve the automatic human tracking system.…”

Section: Resultsmentioning

confidence: 98%

See 1 more Smart Citation

Bypass methods for constructing robust automatic human tracking system

Kakiuchi¹,

Kawamura

Shimizu

et al. 2010

ICA

View full text Add to dashboard Cite

We have been proposing the automatic human tracking system to overcome limitations of existing video surveillance systems. This paper proposes two bypass methods to keep tracking a targeted person by the system constructed by using mobile agent technologies even if unexpected problems are occurred. The proposed methods are called as "Recalculation Bypass Method" and "Additional Calculation Bypass Method". These bypass methods utilize the algorithm which is elaborated in the paper, "An Algorithm to Determine Neighbor Nodes" [7]. The mobile agents are operating in automatic human tracking system and the bypass methods are utilized by the mobile agents. It is a very important ability for the mobile agent not to lose tracking in automatic human tracking systems. The bypass methods contribute to the realization of robust system and resolve two classifications of problem to ensure the tracking ability of mobile agents. The two classifications of problem are logical and physical problems. In the case of logical problems, they occur inside the system and they are called as "broken server". While in the case of physical problems, they occur outside the system and they are called as "pathway being modified". This system is able to track the targeted person continuously by utilizing the methods even if unexpected problems are occurred. We confirmed the effectiveness of the proposed bypass methods by the experiments that used more than one broken servers and pathway being modified.

show abstract

Section: Resultsmentioning

confidence: 98%

“…The inherited result is Table 7. The rows and columns of v 13 and v 14 represent the unnecessary non-camera nodes. And the adjacent matrix Y becomes Table 8.…”

Section: Eliminating Of Unnecessary Non-camera Nodementioning

confidence: 99%

Bypass methods for constructing robust automatic human tracking system

Kakiuchi¹,

Kawamura

Shimizu

et al. 2010

ICA

View full text Add to dashboard Cite

show abstract

“…20 Clustering of numerical data establishes the basis of many classification and system modeling applications. Due to the utilization of data clustering to compute fuzzy inference rules, the resultant rules are specifically tailored to the data.…”

Section: Fuzzy Inference Systemsmentioning

confidence: 99%

“…The FISs utilized in the development of the field and call performance classifiers, used subtractive clustering to generate the required membership functions and set of fuzzy inference rules. 20 The development of the field and call performance FIS classifiers involved the optimization of the cluster radius used within these components. The optimization process followed entailed the construction of various field and call performance inference systems with the cluster radius ranging from 0.01 to 1.…”

Section: Fuzzy Inference Systemsmentioning

confidence: 99%

Caller Behaviour Classification Using Computational Intelligence Methods

Patel

Marwala

2010

Int. J. Neur. Syst.

View full text Add to dashboard Cite

A classification system that accurately categorizes caller interaction within Interactive Voice Response systems is essential in determining caller behaviour. Field and call performance classifier for pay beneficiary application are developed. Genetic Algorithms, Multi-Layer Perceptron neural network, Radial Basis Function neural network, Fuzzy Inference Systems and Support Vector Machine computational intelligent techniques were considered in this research. Exceptional results were achieved. Classifiers with accuracy values greater than 90% were developed. The preferred models for field 'Say amount', 'Say confirmation' and call performance classification are the ensemble of classifiers. However, the Multi-Layer Perceptron classifiers performed the best in field 'Say account' and 'Select beneficiary' classification.

show abstract

“…Fuzzy sets can represent linguistic terms and imprecise quantities, and make systems more flexible and robust [47,79,81]. So, in addition to product preliminary design, fuzzy set theory can also be used in many engineering applications, where either crisp information is not available or information flexible processing is necessary [1][2][3]5,28,38,40,44,63,68,70,[72][73][74][75]77]. In [33], fuzzy applications in product management are identified in job shop scheduling, quality management, project scheduling, facilities location and layout, aggregate planning, production and inventory planning, and forecasting.…”

Section: Introductionmentioning

confidence: 99%

Extending engineering data model for web-based fuzzy information modeling

2013

ICA

View full text Add to dashboard Cite

Being an information modeling language to support the STEP (Standard for Exchange of Product Model Data), EXPRESS has been developed to share and exchange product design, manufacturing and production data in product life cycle. Also being the de-facto standard of data representation and exchange over the Web, XML (eXtensible Markup Language) has been widely applied in Web-based engineering applications for product data exchange and share. It is essential to integrate EXPRESS data model and XML data model in engineering data modeling. EXPRESS-G is the graphical representation of EX-PRESS and can serve as the conceptual design of Web-based engineering data models. Fuzzy engineering information is inherent in many engineering activities. In order to explicitly represent and handle fuzzy engineering information, this paper introduces an extended EXPRESS-G data model for different kinds of fuzziness modeling. After presenting the formal descriptions and corresponding representations of the fuzzy EXPRESS-G data model, the paper investigates the formal transformation from the fuzzy EXPRESS-G data model to the fuzzy XML model. The formal transformation approaches proposed in the paper are demonstrated with engineering application examples.

show abstract

Using fuzzy cognitive maps to identify multiple causes in troubleshooting systems

Cited by 24 publications

References 17 publications

Bypass methods for constructing robust automatic human tracking system

Bypass methods for constructing robust automatic human tracking system

Caller Behaviour Classification Using Computational Intelligence Methods

Extending engineering data model for web-based fuzzy information modeling

Contact Info

Product

Resources

About