Expert Systems

Shaalan, K., A. Hendam, and A. Rafea, "Rapid development and deployment of bi-directional expert systems using machine translation technology", Expert Systems with Applications, vol. 39, issue 1, no. 1, pp. 1375 - 1380, 2012. Abstractks_mt_eswa_2012.pdfWebsite

The present work reports our attempt in developing an English–Arabic bi-directional machine translation tool in the agriculture domain. It aims to achieve automated translation of agricultural expert systems. In particular, we describe the translation of domain knowledge base, including, prompts, responses, explanation text, and advices. In the Central Laboratory for Agricultural Expert Systems (CLAES) where many successful agricultural expert systems have been developed, this tool is found to be essential in developing bi-directional (English–Arabic) expert systems because both English and Arabic versions are needed for development, deployment, and usage purpose. The tool also helps knowledge engineers in overcoming the language barrier by acquiring knowledge from either English or Arabic speaking domain experts. This paper discusses our experience with the developed machine translation tool and reports on results of its application on real agricultural expert systems.

Rafea, A., and K. Shaalan, "Using expert systems as a training tool in the agriculture sector in Egypt", Expert Systems with Applications, vol. 11, issue 3, no. 3: Elsevier Science Ltd, pp. 343–349, 1996. Abstractusingesasatrainingtoolintheagriculture.pdfWebsite

{This paper describes the Egyptian experience in using Expert Systems (ES) as a training tool in the agriculture sector. The work described here is part of an ongoing research to study the use of ES in human resources development. In particular, we present the use of such a tool as an instructional device for increasing the efficiency of extension workers through improving their general decision-making skills in their jobs. To clarify this process, we conducted an experiment and analyzed its results.}

El-Korany, A., K. Shaalan, H. Baraka, and A. Rafea, "An Approach for automating the verification of KADS-based expert systems", New Review of Applied Expert Systems, vol. 4, London, United Kingdom, Taylor Graham, pp. 107–123, 1998. Abstractver_esreview98.pdf

{Reliability has emerged as significant issue in developing of expert systems. Verification plays an important role in assuring the reliability of expert systems. Expert systems verification involves checking the knowledge base for consistency, completeness, and other errors. Our study indicates that in order to verify an expert system, it is necessary to have a conceptual model of the knowledge base. The KADS methodology lends itself to conceptual modeling of the knowledge base, This enabled us to build an automatic verification tool. This tool is able to detect different knowledge base error types. A novel feature of this tool is its ability to detect consistency errors that arise due to using KADS methodology in knowledge modeling.}

Shaalan, K., M. El-Badry, and A. Rafea, "A multiagent approach for diagnostic expert systems via the internet", Expert Systems with Applications, vol. 27, no. 1, Tarrytown, NY, USA, Pergamon Press, Inc., pp. 1–10, jul, 2004. Abstractamultiagentapproachfordiagnosticesviatheinternet.pdfWebsite

In recent years there has been considerable interest in the possibility of building complex problem solving systems as groups of co-operating experts. This has led us to develop a multiagent expert systems capable to run on servers that can support a large group of users (clients) who communicate with the system over the network. The system provides an architecture to coordinate the behavior of several specific agent types. Two types of agents are involved. One type works on the server computer and the other type works on the client computers. The society of agents in our system consists of expert systems agents (diagnosis agents, and a treatment agent) working on the server side, each of which contains an autonomous knowledge-based system. Typically, agents will have expertise in distinct but related domains. The whole system is capable of solving problems, which require the cumulative expertise of the agent community. Besides to the user interface agent who employs an intelligent data collector, so-called communication model in KADS, working on the client sides. We took the advantage of a successful pre-existing expert systems—developed at CLAES (Central Laboratory for Agricultural Expert Systems, Egypt)—for constructing an architecture of a community of cooperating agents. This paper describes our experience with decomposing the diagnosis expert systems into a multi-agent system. Experiments on a set of test cases from real agricultural expert systems were preformed. The expert systems agents are implemented in Knowledge Representation Object Language (KROL) and JAVA languages using KADS knowledge engineering methodology on the WWW platform.

Shaalan, K., M. Rizk, Y. Abdelhamid, and R. Bahgat, "An expert system for the best weight distribution on ferryboats", Expert Systems with Applications, vol. 26, no. 3, pp. 397-411, apr, 2004. Abstractanesforthebestweightdistributiononferryboats.pdfWebsite

There are some problems that need expertise in order to get a satisfactory solution. Ferryboat carries goods, fresh water, diesel oil, luggage and storing rooms up to its permissible draft in order to maintain safety according to the international safety regulations. The best weight distribution on ferryboat needs human expertise to handle many variables, such as the amount of the bunker and fresh water that allow us to use more rooms for charging in order to maximize the profit. This sort of problems can be classified under Configuration Problem. In this paper, we address the development of a ferryboat expert systems (WDFB) using CommonKADS knowledge engineering methodology. We propose a reusable problem-solving approach, which is an enhancement of the structure-oriented approach, capable of solving the ferryboat configuration problem. The proposed model includes heuristics that make the search of suitable configuration more efficient, taking into consideration the transformation knowledge and the optimality criteria. The results of testing the system on a real-world data from National Navigation Company, Suez, Egypt, were satisfactory.

Shaalan, K., A. Hendam, and A. Rafea, "An English-Arabic Bi-directional Machine Translation Tool in the Agriculture Domain", Intelligent Information Processing V, vol. 340, Berlin, Heidelberg, Springer Boston, pp. 281–290, 2010. Abstractbi_direct_a_e_mt.pdf

The present work reports our attempt in developing an English-Arabic bi-directional Machine Translation (MT) tool in the agriculture domain. It aims to achieve automated translation of expert systems. In particular, we describe the translation of knowledge base, including, prompts, responses, explanation text, and advices. In the central laboratory for agricultural expert systems, this tool is found to be essential in developing bi-directional (English-Arabic) expert systems because both English and Arabic versions are needed for development, deployment, and usage purpose. The tool follows the rule-based transfer MT approach. A major design goal of this tool is that it can be used as a stand-alone tool and can be very well integrated with a general (English-Arabic) MT system for Arabic scientific text. The paper also discusses our experience with the developed MT system and reports on results of its application on real agricultural expert systems.