An Intelligent Interface Integrated Services Environment for Electronic Commerce

This paper proposes an intelligent interface integrated services environment for electronic commerce. It contains four main modules, i.e., dialog manager, EC transaction ontology, information collector, and data analyzer. The dialog manager manages the transaction history of the user to collect the user-specific information. It also provides different helping functions for the user. The EC transaction ontology stores the business type of electronic commerce in the system. It classifies the business process into eight categories, i.e., transaction type, ordering pattern, merchandise type, logistic type, customer category, transport vehicle, delivery type, and service type. It also provides the relations and constraints between different business steps. The information collector instantiates and dispatches different information agents to extract, filter, and synthesize relevant transaction data from different data sources timely. The data analyzer is the main component of the system. It instructs the dialog manager to provide proper helping functions for the different users. It then uses the user model to classify the knowledge and skill level of a user. It also predicts the goal of the user by using case-based reasoning and fuzzy Petri-Net to recommend the user with the best transaction plan and browsing behavior. Finally, it monitors the quality of service that the system provided for the user. This environment not only provides an integrated human-machine interface but also manages the business information thoroughly for the users

Modeling and control of flatness in cold rolling mill using fuzzy petri nets

Today, having a good flatness control in steel industry is essential to ensure an overall product quality, productivity and successful processing. Flatness error, given as difference between measured strip flatness and target curve, can be minimized by modifying roll gap with various control functions. In most practical systems, knowing the definition of the model in order to have an acceptable control is essential. In this paper, a fuzzy Petri net method for modeling and control of flatness in cold rolling mill is developed. The method combines the concepts of Petri net and fuzzy control theories. It focuses on the fuzzy decision making problems of the fuzzy rule tree structures. The method is able to detect and recover possible errors that can occur in the fuzzy rule of the knowledge-based system. The method is implemented and simulated. The results show that its error is less than that of a PI conventional controller.<br /

Fuzzy-Petri-Net Reasoning Supervisory Controller and Estimating States of Markov Chain Models

Markov chain models are efficient tools for representing stochastic discrete event processes with wide applications in decision and control. A novel approach to fuzzy-Petri-net reasoning generated solution to initial or another state in Markov-chain models is proposed. Reasoning is performed by a fuzzy-Petri-net supervisory controller employing a fuzzy-rule production system design and a fuzzy-Petri-net reasoning algorithm, which has been developed and implemented in C++. The reasoning algorithm implements calculation of the degrees of fulfilment for all the rules and their appropriate assignment to places of Petri net representation structure. The reasoning process involves firing active transitions and calculating degrees of fulfilment for the output places, which represent propositions in the knowledge base, and determining of fuzzy-distributions for output variables as well as their defuzzified values. Finally, these values are transferred to assign the state of Markov-chain decision model in terms of transition probabilities

A Fuzzy Petri Nets Model for Computing With Words

Motivated by Zadeh's paradigm of computing with words rather than numbers, several formal models of computing with words have recently been proposed. These models are based on automata and thus are not well-suited for concurrent computing. In this paper, we incorporate the well-known model of concurrent computing, Petri nets, together with fuzzy set theory and thereby establish a concurrency model of computing with words--fuzzy Petri nets for computing with words (FPNCWs). The new feature of such fuzzy Petri nets is that the labels of transitions are some special words modeled by fuzzy sets. By employing the methodology of fuzzy reasoning, we give a faithful extension of an FPNCW which makes it possible for computing with more words. The language expressiveness of the two formal models of computing with words, fuzzy automata for computing with words and FPNCWs, is compared as well. A few small examples are provided to illustrate the theoretical development.Comment: double columns 14 pages, 8 figure