Developing a marketing decision model using a knowledge-based system

This paper describes using a knowledge-based system for developing a marketing decision model. The approach used in this study uses a decision table as a knowledge engineering tool. The decision table is used as a means of representing a set of decision rules to construct a developed marketing decision model. To support the modeling process, Prologa, an existing decision table engineering workbench, is used. The developed marketing decision model is used to determine the entrance time of a new product into market by utilizing knowledge-based systems. Presentation of a new product to the market at the best time will provide an advantage to competing companies and will increase their market share.     

A model of explanation for financial knowledge-based systems

In this paper we describe a method for explanation generation in financial knowledge-based systems. The underlying financial model consists of a mixture of quantitative and qualitative relations. The method described can be embedded in a theory of scientific explanation. In a case-study we compare textbook analyses with the output of a program which implements our theory of explanation.     

KBMS: a knowledge-based system for modeling software systemspecifications

Recent research results in software engineering have shown that the process of formalizing and automating software specification activity is moving towards knowledge-based specification systems. A modeling approach and a knowledge-based system that assist in the requirement acquisition, development, and maintenance of such software system specifications are presented     

Developing a knowledge-based early warning system for fish disease/health via water quality management

Fish disease is becoming the major factor damaging the sustainable development of aquaculture and the quality security of aquatic product in China. Many researchers provide assistances and advice in fish disease diagnosis and appropriate treatment measures. However, the risk of misdiagnosis, incorrectly treatment or over-treatment also exists due to carrying out after disease outbreaks. So it is necessary to develop an early warning system. Taking into account that fish disease outbreak is mainly caused by suboptimal water quality in north of China, the best way is to develop decision aids tool that can assess and early warning the risk of fish disease based on water quality management. This paper introduces a knowledge-based early warning system for fish disease via water quality management. The architecture, the process for knowledge engineering, main components and their functions, especially a series of water quality management mathematic models are described. At present, the system is in pilot in the city of Tianjin in China. The stage achievements in developing the intellectual system of fish disease early warning are summarized.     

End-user manipulation of a knowledge-based system: a study of an expert's practice

The advent of end-user manipulation of knowledge-based systems (EUKMS) provides new opportunities for addressing the problems of encapsulating domain expertise. Interfaces which enable the expert, a professional and/or scientific practitioner, to create, refine and evaluate rules about the constituent elements of their knowledge provide a means of circumventing some of the current barriers to successful knowledge encapsulation. The critical feature of the design of such systems is the provision of facilities for the automatic conversion of the expert's rules into code. In a study of scientific work involving the capture of phonetics expertise in a knowledge-based system, key aspects of a speech scientist's working practice were identified. This paper discusses that use of the Speech Knowledge Interface system (SKI) in the context of investigations into the construction of an enhanced model of speech production for a speaker independent, continuous speech recognizer. Evidence that providing the expert with an appropriate interface to a knowledge-based system stimulates questions about existing knowledge and gives rise to new insights into the scope of the investigations, was found. Thus, the process of knowledge externalization, both of knowledge which was only partially realized and knowledge that was perceived as "new" by the expert, was facilitated by the interaction with the system.     

Formalizing dialectical explanation support for argument-based reasoning in knowledge-based systems

The concept of explanation has received attention from different areas in Computer Science, particularly in the knowledge-based systems and expert systems communities. At the same time, argumentation has evolved as a new paradigm for conceptualizing commonsense reasoning, resulting in the formalization of different argumentation frameworks and the development of several real-world argument-based applications. Although the notions of explanation and argument for a claim share many common elements in knowledge-based systems their interrelationships have not yet been formally studied in the context of the current argumentation research in Artificial Intelligence. This article explores these ideas by providing a new perspective on how to formalize dialectical explanation support for argument-based reasoning. To do this, we propose a formalization of explanations for abstract argumentation frameworks with dialectical constraints where different emerging properties are studied and analyzed. As a concrete example of the formalism introduced we show how it can be fleshed out in an implemented rule-based argumentation system.     

Proposing an architectural framework of a hybrid knowledge-based system for production rescheduling

An architectural configuration of a knowledge-based system for production rescheduling reported in this paper uncovers a number of points of interest to practitioners as well as researchers. The study shows that knowledge-based methods applied to production rescheduling are a valuable approach for manufacturers to manage production disturbances and deliver customer orders on time. Very often, developing an effective scheduling system whilst solving some problems requires an appropriate combination of a rigorous analysis of the production system state and the rules of thumb used by the human scheduler. In the actual performance of this hybrid system, an expert simulation system was used to produce new schedules that fit the real production environment.     

Designing a knowledge-based system for benchmarking: A DEA approach

First developed by Xerox in 1979, benchmarking provides measurement and comparison to improve processes and achieve higher performance. Benchmarking has proven a powerful tool for total quality management and process improvement. Successful benchmarking implementation is based on an effective benchmarking tool. To effectively implement benchmarking processes, this work proposes an integrated framework for the benchmarking tool and knowledge-based system using the data envelopment analysis (DEA) method, and then develops an intellectual benchmarking knowledge-based system (BKBS) for benchmarking, performance evaluation and process improvement. Accordingly, this work illustrates how the benchmarking knowledge-based system (BKBS) is implemented in a medical center. This system can help determine the particular benchmarking partners to evaluate the relative efficiency and fill the gaps between the benchmarking partners in the healthcare industry. Finally, the intellectual benchmarking knowledge-based system offers a very fast way to implement the benchmarking processes.     

TUNEX: a knowledge-based system for performance tuning of the UNIXoperating system

TUNEX, an expert system developed for performance tuning of the UNIX operating system, is described. TUNEX was developed on UNIX system V. It uses the properties, commands and utilities of this version. The tuning activities it is concerned with include: (1) adjusting operating system tunable parameters, such as number of disk buffers; (2) running maintenance routines, i.e. reorganizing file systems; (3) developing operation rules, such as off-peak hour runs of backups; and (4) modifying hardware, buying an additional disk drive. The structure of TUNEX is presented and performance analysis modules which provide quantitative information to this tool are briefly described. The overhead in the resource usage introduced by the performance monitoring and tuning tool itself is discussed; the author points to the areas in which additional resources are required by TUNEX     

A knowledge-based standards processor for structural component design

This paper presents a design strategy in which structural components are designed automatically by applying three types of knowledge: knowledge in a design standard; textbook knowledge of structural, material, and geometrical relationships; and knowledge representing designer-dependent design expertise. The design strategy selects from the designer-dependent knowledge source the behavior limitations—limit states of an object in a given stress state—to consider, translates the behavior limitations into a subset of corresponding standard requirements, generates a set of constraints from the requirements and the relations in the knowledge-base of textbook relationships, satisfies the constraints, and then checks the satisfaction of all remaining applicable requirements. By using this design strategy, it is possible to construct a knowledge-based design strategy that is standard independent, so that the same design process can be performed regardless of which design standard is explicitly represented.The design strategy described has been implemented in a prototype knowledge-based system, SPEX, which has a blackboard architecture similar to, but much simpler than, that of HEARSAY. The blackboard represents the level of abstraction through which a component design progresses. The knowledge-base in SPEX consists of several knowledge sources that perform portions of the component design task. Control of the design process knowledge sources in SPEX is rule-based.     

A causal knowledge-based expert system for planning an Internet-based stock trading system

This study describes a causal knowledge-based expert system for planning an Internet-based stock trading system, abbreviated CAKES-ISTS. The case base of this system consists of the qualities that promote ISTS use, two specific facets of ISTS use (stock amount purchased and frequency of use), and user satisfaction. Planning ISTS requires consideration of the complex causal relationships between system qualities, system use, and performance (i.e., user satisfaction). This study also examines the factors affecting the level of system usage and performance. First, this study uses a fuzzy cognitive map (FCM) to develop the causal knowledge base of the expert system for ISTS planning. Second, this study uses structural equation modeling to estimate the relevant relationships among FCM components as well as their direction and strength. Third, this study develops rules based on system qualities to predict the usage and performance level of ISTS, allowing the identification of the qualities essential to enhance system usage and performance. This clearly shows how effective ISTS planning is possible through the inference process provided by CAKES-ISTS.     

ISIS—a knowledge-based system for factory scheduling

Abstract: Analysis of the job shop scheduling domain has indicated that the crux of the scheduling problem is the determination and satisfaction of a large variety of constraints. Schedules are influenced by such diverse and conflicting factors as due date requirements, cost restrictions, production levels, machine capabilities and substitutability, alternative production processes, order characteristics, resource requirements, and resource availability. This paper describes ISIS, a scheduling system capable of incorporating all relevant constraints in the construction of job shop schedules. We examine both the representation of constraints within ISIS, and the manner in which these constraints are used in conducting a constraint-directed search for an acceptable schedule. The important issues relating to the relaxation of constraints are addressed. Finally, the interactive scheduling facilities provided by ISIS are considered.     

Decopan Design: a knowledge-based system for industrial controlgear panels design

A wide domain for expert systems application is that of design processes. Decopan Design is a knowledge-based system supporting the design of industrial controlgear panels. Such a design process requires declarative knowledge, heuristic knowledge and human experience and skill, which are excellent subjects in order to be incorporated in a knowledge-based expert system. Decopan Design has been created using an expert system shell and has been linked with a computer-aided drafting program for drawing purposes.     

Libra: a high fidelity knowledge-based system for recommending scheduling programs

Contemporary knowledge systems are usually neither easy to use or understand. We propose a new class of knowledge systems, which we call high fidelity systems, that use representations and processes that closely resemble the objects and tasks with which people are already familiar. To illustrate the concept of high fidelity, we describe Libra, one such system for recommending scheduling programs. Our initial experience with Libra and its usage suggests that high fidelity not only enhances the user acceptability of knowledge-based systems, but it also facilities high speed design and implementation.We chose to replicate the knowledge in Libra because it is already published, and because we wanted to show that a Libra user can have an interface similar to the diagrams drawn in the journal paper. The latter was used to describe the knowledge-based framework for selecting scheduling systems. If we can replicate them in the user interface, we would have successfully created a high fidelity system — that is, the Libra user interface would be at least as able to communicate the framework to the user as the journal paper.