Adaptive fuzzy petri nets for dynamic knowledge representation and inference

Li, Xiaoou; Lara-Rosano, Felipe

doi:10.1016/s0957-4174(00)00036-1

Cited by 95 publications

(34 citation statements)

References 17 publications

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“…Fuzzy Petri nets model proposed by X. Li and F. Lara Rosano [13], for dynamic knowledge representation and inferences. This model aimed for more generalized expert system trained using neural networks.…”

Section: A Existing Knowledge Representation Modelsmentioning

confidence: 99%

Towards MORK: Model for Representing Knowledge

Kamala¹,

Selwyn²

2016

IJMECS

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Abstract-Smart world needs intelligent system for effective and timely decision making. This is achieved only through a knowledge based system with functional knowledge representation units. In this paper, two models are proposed for representing knowledge. This process involves in getting the data and placing the information in the correct location. Logical notations are used for taking the clauses and graph is used for putting the entities. In Model one, the data is translated into logical statements using predicate logics, later the knowledge is stored in conceptual graph and retrieved. Whereas in Model two, the given information is translated using First Order Logic (FOL), by applying description logic concept rules are defined and as a result reasoning is done. Storage is done by using concept-relation graph. The main aims of our models are to have easy and simple access over the information. These models return the required exact answer, for the higher order query posted by the end user to the intelligent system.

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Section: A Existing Knowledge Representation Modelsmentioning

confidence: 99%

Towards MORK: Model for Representing Knowledge

Kamala¹,

Selwyn²

2016

IJMECS

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“…FPN are used for fuzzy knowledge representation and reasoning. The fuzziness concept can be incorporated in Petri Nets by applying a fuzzy reasoning mechanism over the Petri Nets structure [12]. Generally a FPN is capable of modeling fuzzy production rules (of type if …”

Section: B Fuzzy Petri Netmentioning

confidence: 99%

“…FPN can effectively analyze concurrent systems by verifying the safety rules and standards for traffic operations, also it uses a graphical presentation that is easy to understand, easy to modify because of its modularity. Reader looking for more information about FPN can refer to [12]. In our approach we adapt the fuzzy logic for modeling PN transition object that concentrates on if-then fuzzy production rules realized by truth values to describe ambiguity of packet's movement.…”

Section: B Fuzzy Petri Netmentioning

confidence: 99%

“…In our approach, packet is represented by a token in FPN place, and packet's operation is exemplified by FPN transition that is responsible to move packet from one place to another [12], [22]. Once the packet is captured by a gate; it moves to place where checking and matching with ACL is done, in addition an instant copy of this packet is moved to the traffic analysis part to extract the packet's parameters (features) like number of packets of ICMP protocol coming through time period.…”

Section: A Level 1-fuzzy Filteringmentioning

confidence: 99%

“…Due to Petri Nets inability to face with systems working on obscure data and continues events, the trend to adopt an extension of PN called a Fuzzy Petri Nets (FPN) that is a combination of fuzzy set theory and Petri Net concept. FPN is a tool for the representation of uncertain knowledge about a system state and has the ability to describe fuzzy event-condition-action rule in a good vision [12]. This paper presents a new packet filtering firewall approach that utilizes traffic behavior of incoming packets to assess the threat from the outside and invest this assessment to enhance packet filtering process.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Approach for Improving Performance of a Packet Filtering Firewall Based on Fuzzy Petri Net

Ali¹,

Darwish²,

Guirguis³

2015

JACN

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Abstract-With the rapid development of Internet, the security of networks becomes an important issue today and monitoring network traffic is necessary for realizing different purposes such as system performance, network debugging and/or information security. As a major measure to implement enterprise security, firewall technique ensures the security of local networks. Traditional firewall technologies have their own weaknesses in architecture, configuration, monitoring and management that affect to firewall performance. Furthermore, it lacks to deal with vague and uncertainty associated with filtering packets from outside. Architecture of a new kind of firewall, intelligence firewall is presented in this paper. The main contribution is to utilize Fuzzy Petri Net as a tool for modeling discrete event systems characterized by an imprecise knowledge. The graphical power of Petri Nets makes the packet filtering model easy to design, test, improve and maintain. Another contribution is to present 2-level fuzzy filtering algorithm to enhance ordering of filtering rules list that permits us to model the dynamic behavior of monitoring system concerning uncertainty associated with packet filtering. Experimental results for local network are given, which show the effectiveness of the suggested approach and demonstrate the enhancement of the firewall sensitivity against the risk coming from network traffics.Index Terms-Firewall, fuzzy petri net, packet filtering, access control list (ACL).

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Soft Modeling of Knowledge Systems Through Fuzzy Petri Nets

Lara-Rosano¹

IFIP — The International Federation for Information Processing

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Knowledge in the social and human Sciences cannot be modeled with old time mathematical modeling techniques. In this situation, it would be very useful to have modeling approaches capable to express the richness of social reality, including its vagueness and uncertainty. Aiming at this objective, a soft modeling approach is proposed, implemented as a generalized fuzzy Petri net. This model can be then used to make inferences and to solve problems related to the complex system.

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Adaptive fuzzy petri nets for dynamic knowledge representation and inference

Cited by 95 publications

References 17 publications

Towards MORK: Model for Representing Knowledge

Towards MORK: Model for Representing Knowledge

An Approach for Improving Performance of a Packet Filtering Firewall Based on Fuzzy Petri Net

Soft Modeling of Knowledge Systems Through Fuzzy Petri Nets

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