Using Ripple Down Rules for Actions and Planning

IDENTIFIKASI PENYAKIT PADA TERUMBU KARANG MENGGUNAKAN RIPPLE DOWN RULES

Jurnal Terapan Teknologi Informasi ◽

10.21460/jutei.2017.12.50 ◽

2018 ◽

Vol 1 (2) ◽

pp. 165-174

Author(s):

Agus Cahyo Nugroho

Keyword(s):

Coral Reef ◽

Expert System ◽

Expert Systems ◽

Specific Problem ◽

Specific Knowledge ◽

Web Based ◽

Human Thinking ◽

Ripple Down Rules

Along with the development of technology, people developed a system that capable of adopting processes and human thinking as an expert system that contains specific knowledge so that everyone can use it to solve a specific problem, namely the diagnosis of coral reef disease. The purpose of this study is to develop an expert system for diagnosing coral reef disease in the form of websites using PHP with a MySQL database. Expert system for diagnosing coral reef disease problem is using Ripple Down Rules (RDR) method has a goal to discover symptoms that appear in the form of questions that can diagnose the coral reef disease based on website. Web based expert system is able to recognize types of coral reef disease after consultation by answering a few questions that are displayed by the application of expert systems and can infer some types of coral reef disease. Data coral reef disease that already known adapt to rules which are made for matching the symptoms of coral reef disease.

Download Full-text

Ripple Down Rules

Decision-Making Support Systems ◽

10.4018/978-1-59140-045-5.ch013 ◽

2011 ◽

pp. 207-226 ◽

Cited By ~ 1

Author(s):

Debbie Richards

Keyword(s):

Expert Systems ◽

Knowledge Acquisition ◽

Clinical Decision Support System ◽

First Generation ◽

Clinical Decision ◽

Commercial Success ◽

Combined Use ◽

Representation Technique ◽

History Of ◽

Ripple Down Rules

Knowledge is becoming increasingly recognized as a valuable resource. Given its importance it is surprising that expert systems technology has not become a more common means of utilizing knowledge. In this chapter we review some of the history of expert systems, the shortcomings of first generation expert systems, current approaches and future decisions. In particular we consider a knowledge acquisition and representation technique known as Ripple Down Rules (RDR) that avoids many of the limitations of earlier systems by providing a simple, user-driven knowledge acquisition approach based on the combined use of rules and cases and which support online validation and easy maintenance. RDR has found particular commercial success as a clinical decision support system and we review what features of RDR make it so suited to this domain.

Download Full-text

Translations of Ripple Down Rules into Logic Formalisms

Knowledge Engineering and Knowledge Management Methods, Models, and Tools - Lecture Notes in Computer Science ◽

10.1007/3-540-39967-4_28 ◽

2000 ◽

pp. 366-379 ◽

Cited By ~ 7

Author(s):

Rex B.H. Kwok

Keyword(s):

Ripple Down Rules

Download Full-text

Uncovering the conceptual models in ripple down rules

Conceptual Structures: Fulfilling Peirce's Dream - Lecture Notes in Computer Science ◽

10.1007/bfb0027871 ◽

1997 ◽

pp. 198-212 ◽

Cited By ~ 3

Author(s):

Debbie Richards ◽

Paul Compton

Keyword(s):

Conceptual Models ◽

Ripple Down Rules

Download Full-text

Nested Ripple Down Rules (NRDR) as a Design Assistant in Mechanical Dimensional Tolerancing

Volume 3: Design and Manufacturing, Parts A and B ◽

10.1115/imece2010-39773 ◽

2010 ◽

Author(s):

Ramsey F. Hamade ◽

Ali H. Ammouri ◽

G. Beydoun

Keyword(s):

Knowledge Management ◽

Knowledge Acquisition ◽

Management System ◽

Knowledge Management System ◽

Design Knowledge ◽

Mathematical Functions ◽

Acquisition Process ◽

Engineering Standards ◽

To Receive ◽

Ripple Down Rules

The dimensional tolerancing knowledge management system presented in this paper uses Nested Ripple down Rules (NRDR) targeted towards incrementally capturing expert design knowledge. A demonstrated example of such captured knowledge is that which human designers utilize in order to specify dimensional tolerances on shafts and mating holes in order to meet desired classes of fit as set by relevant engineering standards. In doing so, NRDR interface was designed to receive mathematical functions with their specifications prior and during the KA process. This is necessary to be able to exploit relationships among several classes with respect to certain numerical features of the cases in order to accelerate the convergence of the NRDR knowledge acquisition process by generating artificial cases which are likely to trigger the addition of exception rules. The incorporation of equations constitutes a novel contribution to the field of knowledge acquisition with NRDR. The developed dimensional tolerancing knowledge management system would help mechanical designers become more effective in the time-consuming tolerancing process of their designs in the future.

Download Full-text