English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The inference process in many existing artificially intelligent embedded systems is mostly based on a snapshot of incoming input data. It may sometimes be inappropriate to make a decision based on these current input data. The ability to suspend the current inference process and reactivate it upon specified conditions is crucial in many real-time applications. The objective of this research is to design and implement a decision support system that will detect time-related events. This system allows a representation of temporal conditions and actions so that temporal inference invocation, suspension and reactivation are possible.This decision support system consists of three major modules: the Development Engine (DE), the Knowledge Base Manager (KBM), and the Time Sensitive Inference Engine (TSIE).The development engine module allows experts to specify their knowledge in terms of rules, especially with temporal conditions; for example, “If water level is below 10 after the valve B is turned on for 2 minutes, state is warning”, and “If state is warning and the temperature of the reactor is above 1000 degree for 30 seconds, state is alarm and turn on the water pump”The user interface in this development Engine module is completely interactive, and decision tables are the tool used for rule specification. These rules will be automatically checked for inconsistency, redundancy and then stored in the knowledge base for later use by the time sensitive inference engine.A DBMS and a data base which contains historical data are required for analysis purposes. Existing database packages can be used for this.The knowledge base manager module is used to maintain and monitor the created knowledge base. The KBM also plays a role as an interface between the DBMS and the TSIE, which accesses the data base through function calls to the DBMS program. This makes the data base acceptable to TSIE.The time sensitive inference engine performs the inference and control processes on the on-line process data. These processes may be activated, suspended, and reactivated depending on the rules set by the expert. Two major sub-modules of the time sensitive inference engine are the Event Manager and the Action Executive. The event manager is responsible for periodically checking the event list, which keeps both historical and predicted events. The action executive monitors the on-line control of the system.The system is being developed on IBM personal computer. It is intended to support experts in building up knowledge bases and to support realtime process control. If users are involved in the inference process, it can be expanded with a user interface, which of course requires some kind of checking function against incomplete requests or contradictory input data. Applications of such a system would include manufacture automation systems, air traffic monitoring systems, financial market analysis and investment systems, etc.

Design of an on-line decision support system for process control