Computation scheme for the general purpose VLSI fuzzy inference engine as expert system

Fuzzy inference engine, as one of the most important components of fuzzy systems, can obtain some meaningful outputs from fuzzy sets on input space and fuzzy rule base using fuzzy logic inference methods. In multi-input–single-output (MISO) fuzzy systems, in order to enhance the computational efficiency of fuzzy inference engine, this paper aims mainly to investigate three MISO fuzzy hierarchical inference engines employed fuzzy implications satisfying the law of importation with aggregation functions (LIA). We firstly find some aggregation functions for well-known fuzzy implications such that they satisfy LIA. The fuzzy implication satisfying LIA with respect to a given aggregation function is then characterized. Finally, three fuzzy hierarchical inference engines in MISO fuzzy systems are constructed according to aforementioned theoretical developments. Three examples are also provided to illustrate our theoretical arguments.

Fuzzy Inference in Rule-Based Real-Time Control

This article is an introduction to artificial intelligence (AI), especially the place of expert systems (ES) in AI. Some applications of expert systems in other industries are discussed, as well as potential areas of application within the pharmaceutical industry. Advantages and disadvantages of developing ES using so-called AI languages v ES shells are covered. A product review is presented, including AI languages, induction ES shells, straightforward rule shells, and sophisticated ES development environments. Also included is a discussion of the problems and pitfalls that may await anyone attempting to develop ES in pharmaceutical R&D. Finally, some recommendations are offered that they may be useful to those just getting started in this area.

Abstract: The First Symposium on The Theory and Application of Expert Systems in Emergency Management, held at the Department of Commerce, Washington, D.C. (April 24 and 25, 1985) was funded by the Federal Emergency Management Agency and organized by the National Bureau of Standards' Operations Research Division. The purpose of the symposium was to bring together researchers in expert systems, artificial intelligence, and emergency operations in a forum to review the concepts of expert systems and the problems of emergency management, with the objective of determining how expert systems can be used to augment the experience of local, State and Federal emergency managers faced with the difficult tasks of determining the best response to an emergency situation. Speakers addressed the following areas: The theory and uncertainty aspects of expert systems, artificial intelligence's future role in emergency management, technology for building and using expert systems, emergency management decisions and information needs and uses, applications of expert systems in the management of chemical spills and shipboard and coal mine fires, and the role and use of simulation in emergency management expert systems.

At school, especially in Automotive Vocational High Schools, a learning process is carried out by helping students to recognize and overcome problems that occur in motorbike/car damage. One of the SMKs that has an Automotive expertise program is SMK Negeri 2 Bengkulu City. So far, the automotive learning system has used books and pictures to support the learning process at school. However, this sometimes has problems, where students do not fully understand the material given, and on the other hand students have difficulty learning independently either in the school environment or at home. Expert systems in helping students diagnose car engine damage using the Expert System Development Life Cycle (ESDLC) method can be accessed online with internet access via the web link http://riska.vad.my.id. This expert system application is made using the PHP programming language and MySQL database. This expert system application has been embedded with the ESDLC method with the Forward Chaining inference engine which is used to trace damage to car engines based on the symptoms experienced by the car engine. This expert system application can help facilitate the understanding of students at SMK Negeri 2 Bengkulu City in diagnosing car engine damage, by providing consultation directions starting from entering symptoms to getting consultation results. Based on the system testing that has been done, it can be concluded that the functionality of the application has been running well and this expert system can provide consultation results based on the symptoms selected by the user through the stages of the Expert System Development Life Cycle (ESDLC) method.

In this study contains an expert system design for web-based lecturer scheduling that can facilitate the Chair of the Study Program in scheduling courses for lecturers. This system was built using Notepad ++ software, XAMPP with HTML, CSS, JavaScript, PHP and database programming languages using MYSQL. Subjects in this study are expert system applications as the media schedule lecturer subjects. Data collection in this study uses the interview method and questionnaire method. This system is built with the Waterfall model namely analysis, design, coding and testing. This application in the inference engine used is the forward chaining method. The results of this study are expert system applications to schedule lecturers’ subjects according to the questionnaire data. Based on the results of the trial it can be concluded that this expert system application can facilitate the Chair of the Study Program in accurately scheduling courses, classes, days, hours, space, and lecturers

A Relational Database Interface for Design Expert Systems

The fuzzy sets theory is observed as an important and powerful tool, which aids numerous researchers and learners in a variety of ways and in countless disciplines by transforming oral information into mathematical data. The majority of our conventional tools for computing, analysis and modeling are based on clear cut, defined, deterministic and precise information (generally crisp in nature) and concentrate on true yes or true no type information rather than more or less type information. It is very easy to deal with the cases, where the statement refers true yes or true no type information, however it is critical to deal with more or less type of data information, which can be easily overcome by fuzzy sets theory. The presented chapter tries to give an idea to the learners and researcher about: the basic concepts of fuzzy, what is fuzzy and fuzzy number, what are the application fields of the developed fuzzy theory, how to import fuzzy data, what is linguistic and importance of linguistic in fuzzy theory, what are the existing developed techniques that integrate the fuzzy theory effectively, etc. The main objective of the presented chapter is to impart fuzzy knowledge to the new learners and readers, so that they augment and disseminate the fuzzy sets theory into new application fields to benefit the society and mankind.

This study aims to determine the level of user acceptance of the application of potato expert system in the diagnosis of plant pests and diseases based on Android that has been developed. The application of an expert system is intended to help farmers and extension workers in particular to identify types of plant pests and diseases based on symptoms that appear and control solutions easily, quickly and accurately. In this study, the effects of perceived ease of use and the perceived usefulness on behavioural intention to use based on the perspective of farmers and extension workers in the field were measured. The method used in this study is a survey with Technology Acceptance Model (TAM) with the total respondents of 204. The results showed the perceived ease of use has a positive correlation with behavioural intention to use; perceived usefulness has a positive correlation with behavioural intention to use, and both perceived ease of use and perceived usefulness have a positive correlation with behavioural intention to use.

Tolerance-based intuitionistic fuzzy-rough set approach for attribute reduction

Expert-system technology has emerged from beneath the umbrella of Artificial Intelligence and into the mainstream of engineering problem solving. There already are several notable examples of the application of this state-of-the-art technology in the petroleum industry. Clearly, expert systems that run efficiently on standard personal computers are particularly of value. A new expert-system generator that overcomes the speed, memory and mass-storage limitations of XT/AT-class personal computers is presented in this paper. The shell is optimized for the specific characteristics of the target user, knowledge expert and computer. Expert systems developed using this shell currently are being used by our technical personnel for drilling fluid and related applications.

Expert system applications in production and operations management: A selected bibliography (1975–1989)

As an important content in fuzzy mathematics, similarity measure is used to measure the similarity degree between two fuzzy sets. Considering the existing similarity measures, most of them do not consider the hesitancy degree and some methods considering the hesitancy degree are based on the intuitionistic fuzzy sets, intuitionistic fuzzy values. It may cause some counterintuitive results in some cases. In order to make up for the drawback, we present a new approach to construct the similarity measure between two interval‐valued intuitionistic fuzzy sets using the entropy measure and considering the hesitancy degree. In particular, the proposed measure was demonstrated to yield a similarity measure. Besides, some examples are given to prove the practicality and effectiveness of the new measure. We also apply the similarity measure to expert system to solve the problems on pattern recognition and the multicriteria group decision making. In these examples, we also compare it with existing methods such as other similarity measures and the ideal point method.

Emerging trends in soft set theory and related topics.

Although the use of expert systems (ESs) as a problem-solving tool is relatively new in the transportation profession, it has been recognized that a well-designed ES can contribute in areas where knowledge domain requires an integration of expertise from various disciplines or is very complex and difficult to quantify. To minimize the effort involved in developing essential ES mechanisms, researchers often prefer to use ES shells which provide a standard inference procedure, knowledge representation, and a user-friendly design environment. However, commercial ES shells tend to be designed for only certain classes of problems, and are not as general and flexible as programming languages. More than 150 commercial ES shells are available in the microcomputer market. Most ES shells are ususally claimed by their vendors to be usable for almost any conceivable applications, but such claims have often proved to be extravagant. Hence, the selection of an efficient yet cost-effective commercial shell is one of the most critical tasks in ES development. In reviewing the the vital task of ES shell selection, this paper presents our experience in evaluating more than 30 ES shells for developing an ES for signal design. The proposed ES includes signal settings, phasing plans, controllers, and detector locations.