Neurules: improving the performance of symbolic rules

IFIP Advances in Information and Communication Technology

2011

Abstract. In this paper, we present the design, implementation and evaluation of intelligent methods that assess bank loan applications. Assessment concerns the ability/possibility of satisfactorily dealing with loan demands. Different loan programs from different banks may be proposed according to the applicant's characteristics. For each loan program, corresponding attributes (e.g. interest, amount of money that can be loaned) are also calculated. For these tasks, two separate intelligent systems have been developed and evaluated: a fuzzy expert system and a neuro-symbolic expert system. The former employs fuzzy rules based on knowledge elicited from experts. The latter is based on neurules, a type of neuro-symbolic rules that combine a symbolic (production rules) and a connectionist (adaline unit) representation. Neurules were produced from available patterns. Evaluation showed that performance of both systems is close although their knowledge bases were derived from different types of source knowledge.

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Section: Introductionmentioning

confidence: 99%

Fuzzy and Neuro-Symbolic Approaches to Assessment of Bank Loan Applicants

IFIP Advances in Information and Communication Technology

2011

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“…The expert system's knowledge representation formalism is based on neurules, a type of hybrid rules integrating symbolic rules with neurocomputing. The attractive feature of neurules is that they improve the performance of symbolic rules [6] and simultaneously retain their naturalness and modularity [7] in contrast to other hybrid approaches.…”

Section: Expert Systemmentioning

confidence: 99%

“…Each neurule is individually trained via the LMS (Least Mean Square) algorithm. In case of inseparability in the training set, special techniques are used [6], [7]. In this way, the neurules contained in the pedagogical model and the user modeling component are constructed.…”

Section: Expert Systemmentioning

confidence: 99%

“…Based on this information, it constructs lesson plans and selects the appropriate course units for teaching each individual user. The functionality of the system is controlled by an expert system based on neurules, a type of hybrid rules integrating symbolic rules with neurocomputing [6], [7].…”

Section: Introductionmentioning

confidence: 99%

“…The expert system employs a hybrid knowledge representation formalism, called neurules [6]. In the following, we elaborate on the system's key aspects.…”

Section: Introductionmentioning

confidence: 99%

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A web-based intelligent tutoring system teaching nursing students fundamental aspects of biomedical technology

Koutsojannis

2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Self Cite

Abstract-In this paper, we present the architecture of a Web-based Intelligent Tutoring System (ITS) for distant education of nursing students in fundamental aspects of the most common medical equipment. It offers course units covering the needs of users with different knowledge levels and characteristics. It tailors the presentation of the educational material to the users' diverse needs by using AI techniques to specify each user's model as well as to make pedagogical decisions. This is achieved via an expert system that uses a hybrid knowledge representation formalism integrating symbolic rules with neurocomputing. Keywords -Intelligent Tutoring Systems, health care technology I. INTRODUCTIONThe introduction of new technologies in health care, can be seen as improved diagnosis and treatment as well as increased efficiency of the services involved. At the same time, however, the implementation of these new improved technologies, introduces concerns about trained personnel and imposes new demands for tools and methods for their overall management. The support services, for biomedical technology, address a variety of technical and administrative issues, concerning the safe and efficient operation of medical equipment over the period of its intended use. Health care technology is our first line of defence against any disease. Health care professionals such as nurses have to be familiar with the most common medical equipment used in health care units. Educational programs already include courses with the fundamental aspects of the proper care and safety of medical instruments [12] In this paper, we present the architecture of a Web-based ITS for teaching the use and safety aspects of health care technology. The system is addressed to nursing students or health professionals. It includes course units covering the needs of users with different knowledge levels and characteristics. The system models the users' knowledge state and skills. Based on this information, it constructs lesson plans and selects the appropriate course units for teaching each individual user. The functionality of the system is controlled by an expert system based on neurules, a type of hybrid rules integrating symbolic rules with neurocomputing [6], [7]. Fig. 1 depicts the basic architecture of the ITS. It consists of the following components: II. SYSTEM DESCRIPTION• the domain knowledge, containing the structure of the domain and the educational content. The educational content refers to the following main chapters: magnetic resonance, computed tomography, nuclear medicine, electro-medicine, ultrasound, anesthesia systems, radiographic systems, medical informatics, lasers and intensive care systems. Each chapter concerns specific equipment. For each piece of equipment primary learning items involve its structure, its manipulation and internationally recognized safety standards.• the user modeling component, which records information concerning the user, • the pedagogical model, which encompasses knowledge regarding various pedagogical decision...

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Rule-based update methods for a hybrid rule base

Data & Knowledge Engineering

2005