A Review on Expert System Applications in Power Plants

Mark Watson Morgan Kaufmann Publishers, San Francisco, 1997, 377 pp. ISBN 1-55860-420-0, $44.95 This book is well written and organized to cover how to apply AI (Artificial Intelligence) techniques for practical Internet and Intranet tools by using the Java programming language. In the book, the author uses neural network and genetic algorithms to develop distributed systems that are applied for the Internet and Intranets, such as client/server model and information retrieval tool and so on. Part 1 begins with a good general introduction to AI. The history and survey of Artificial Intelligence research are given briefly. In addition, symbolic processing versus neural networks approaches are discussed. This author opts to use neural network to develop example Internet/Intranet systems in the book. Part 2 consists of Java programs developed for AI, neural networks, genetic algorithms, natural language processing, and expert systems. Chapter 2 illustrates Graphical User Interface (GUI) class that is derived from Applet and Canvas classes in Java, which is used in most example programs in the book. Chapter 3 introduces a frame data structure that is used as a message in distributed systems in the later chapters. Chapter 4 shows neural network classes developed in Java and its theory and implementation. Chapter 5 explains the genetic algorithms and the Java genetic algorithm classes. Chapter 6 describes how to develop and implement natural language processing classes using Java. Chapter 7 shows how to share data objects in distributed systems. For example, distributed AI agent classes are developed to share data objects, WWW data collection agent classes are shown to retrieve documents in the Internet, and small POP (Post Office Protocol) mail classes are developed to send and receive mails. Chapter 8 illustrates how to develop expert systems by using Java Jess, which is based on OPS5/CLIPS expert systems. Part 3 explains how to generate and implement the projects using the Java classes that are developed in Part 2. Chapter 9 shows the project that demonstrates the use of genetic algorithms in chapter 5 to control enemy ships in a scrolling arcade game. Chapter 10 describes the real-time handwriting recognition system developed by using the neural network classes in chapter 4. Chapter 11 illustrates a greedy algorithm to optimize neural networks that is based on the author’s hand-tuning neural training data. Chapter 12 improves neural network training data by applying genetic algorithms, to discard bad training data and to avoid discarding good training data. Chapter 13 describes the distributed natural language processing system that uses natural language processing classes in chapter 6. The data structures in chapter 2 are used to store historical data in a separate server application on any other computer in the Internet or Intranets. The final chapter provides the design and implementation of a complete agent-based information retrieval tool for the Internet. The retrieved documents are stored in ASCII or HTML format. This book is a very good reference book for anyone interested in developing systems using Java in distributed environments, especially applying AI techniques. Also, the author provides the CD-ROM that includes the source code for Java classes developed in the book. Haklin Kimm, University of Tennessee

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.

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.

Systems have no intrinsic value in and of themselves, but rather derive value from the contributions they make to the missions, decisions, and tasks they are intended to support. The estimation of the cost-effectiveness of systems is a prerequisite for rational planning, budgeting, and investment documents. Neural network and expert system applications, although similar in their incorporation of a significant amount of decision-making capability, differ from each other in ways that affect the manner in which they can be evaluated. Both these types of systems are, by definition, evolutionary systems, which also impacts their evaluation. This paper discusses key aspects of neural network and expert system applications and their impact on the evaluation process. A practical approach or methodology for evaluating a certain class of expert systems that are particularly difficult to measure using traditional evaluation approaches is presented.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Article Free Access Share on Neural networks: a new dimension in expert systems applications Author: Mohammed H. A. Tafti School of Business, Hofstra University School of Business, Hofstra UniversityView Profile Authors Info & Claims SIGBDP '90: Proceedings of the 1990 ACM SIGBDP conference on Trends and directions in expert systemsSeptember 1990 Pages 423–433https://doi.org/10.1145/97709.97739Online:01 September 1990Publication History 0citation1,705DownloadsMetricsTotal Citations0Total Downloads1,705Last 12 Months6Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

تناولت الدراسة الحالية واحدة من أهم المشاكل التي تعاني منها المنظمات الرياضية عالية الاداء وهي عدم الاستفادة القصوى من تطبيقات تقنيات الذكاء الاصطناعي، فلقد تمثلت مشكلة البحث الأساسية في معرفة أثر تطبيق تقنيات الذكاء الاصطناعي في ادارة المنظمات الرياضية عالية الأداء وما مدى مساهمة تطبيقات تقنيات الذكاء الاصطناعي في تشخيص ومعالجة المعوقات الادارية والتقنية في اقسام النشاط الرياضي والمدرسي في المديريات العامة للتربية في محافظة بغداد للتوجه نحو الاداء العالي وفي هذا السياق، فلقد تمثل هدف الدراسة الرئيس في بناء مقياس للاطار المفاهيمي لتطبيقات تقنيات الذكاء الاصطناعي في المنظمات الرياضية عالية الاداء -اقسام النشاط الرياضي والمدرسي في المديريات العامة للتربية في محافظة بغداد أنموذجاً. ولغرض تحقيق أهداف الدراسة اتبعت الباحثتان المنهج الوصفي بالأسلوب التحليلي لملامته لطبيعة المشكلة كذلك القيام بدراسة استطلاعيه غير مقننه في اقسام النشاط الرياضي والمدرسي وكانت الاستبانة هي الأداة المستخدمة في ذلك، وتوصلت الدراسة إلى بناء مقياس رصين لتطبيقات تقنيات الذكاء الاصطناعي في المنظمات الرياضية عالية الاداء ومكون من خمس محاور وهي النظم الخبيرة والواقع الافتراضي والوكلاء الاذكياء وتقنيات المعلومات واتمتة العمليات وقد جاء اختيار حجم العينة مساويا للمجتمع لتلام طبيعة البحث، وقد تم اثبات صدق وموثوقية هذا المقياس من خلال الوسائل الإحصائية كمعامل الفا كرو نباخ بمقدار 89,7، لقد احتوت محاور المقياس الخمسة على خمسة وعشرون عبارة، ولقد تراوحت الأهمية النسبية لهذه العبارات ما بين (63-84)%، وكانت اعلى قيمه للأهمية النسبية تبلغ 84% لعباره الثانية من محور النظم الخبيرة وهي (تعمل النظم الخبيرة كخبير استشاري للإدارة العليا في اقسام النشاط الرياضي والمدرسي لتسهم في اتخاذ القرارات الصحيحة)، بينما كانت اقل قيمة للأهمية النسبية لعبارة الأولى من محور الواقع الافتراضي وهي (استخدام الواقع الافتراضي في اقسام النشاط الرياضي والمدرسي يسهم في اكتساب مهارات متنوعة للموظفين ويعمل على تطوير الاداء الاداري والتقني)

Edamame grade is determined based on edamame quality parameters with several parameters that are quite a lot. The process of deciding edamame grade is relatively complicated and challenging. To determine the edamame grade, an experienced expert in the field is needed. With limited grading experts, the design of expert systems for grading edamame can help users or companies to determine edamame grade. This study aims to design an expert system for determining edamame grade, which can determine the quality of edamame accurately. The Design of an expert system in this research uses the forward chaining method. The stages of designing an expert system include problem identification, knowledge acquisition, building a data flow diagram, compile the database, building a decision tree diagram, and developing a user interface. The results showed that the expert system has been verified and validated well. Verification test results show that all the menu buttons on the expert system application are functioning correctly. Then, the validation results also show that the edamame quality output produced by the expert system is compatible with the expert solution, meaning that the expert system's output data is by following with the results of the decision given by the expert. In testing the validation of determining the quality is appropriate. The results of the verification and validation of the edamame grading expert system show that the expert system has produced satisfactory outcomes. Expert system output is compatible with the solution provided by the expert.

The authors review and categorize the research in applications of artificial intelligence (AI) and expert systems (ES) in new product development (NPD) activities. A brief overview of NPD process and AI is presented. This is followed by a literature survey in regard to AI and ES applications in NPD, which revealed twenty four articles (twenty two applications) in the 1990–1997 period. The applications are categorized into five areas: expert decision support systems for NPD project evaluation, knowledge-based systems (KBS) for product and process design, KBS for QFD, AI support for conceptual design and AI support for group decision making in concurrent engineering. Brief review of each application is provided. The articles are also grouped by NPD stages and seven NPD core elements (competencies and abilities). Further research areas are pointed out.

Artificial intelligence (AI) has made enormous progress in recent decades, significantly influencing various industries, including the medical field. An expert system is a type of artificial intelligence that deliver specialized services in addition to experts by gathering specialty knowledge and expert information in a specific field. In light of the swift rise of Internet technology, the way expert systems are created and supplied has changed. The study used Google Scholar as the online database that provides published content about expert systems that apply AI in the medical field and covers the period of 2019 to 2024 to collect the latest data. The influence and effectiveness of utilizing an expert system with AI across various specializations are emphasized in this study's analysis of their uses in medicine. By using expert systems, they can mimic the decision-making of a human expert, improving healthcare results. Several medical specialties, including gynecology, neurology, orthopedics, ophthalmology, and cardiology, use these solutions based on AI. However, every field has its own set of difficulties, and technological developments are impacting the accuracy and reliability of diagnosis, especially gynecological diseases, which are more complex and diverse. Despite the difficulties, expert systems with AI can provide innovative solutions that can improve patient care. Understanding how AI works can pave the way for future innovation and progress in medical technologies, creating better patient results and more efficient healthcare systems. Educating medical personnel about AI and its applications could help them use these tools more efficiently to provide better patient care.

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.

Development of an 'expert system' for elucidation of structures of acyclic organic compounds is described. An expert system is a computer program that embodies some of the heuristic problem-solving knowledge of human experts so that it can effectively be used as an aid to decision making. The expert system described in this paper is intended to assist a chemist in arriving at plausible structures, the input data being the mass spectrum, molecular formula and presence (if known) of functional groups. The program generates chemically possible structures for the given molecular formula and can use, where available, the constraints imposed by the mass spectrum of the compound and by any known functional groups. The program makes use of a new algorithm for obtaining a canonical representation of structures and a new heuristic for incorporating constraints of the mass spectrum. This work constitutes a case study of the application of artificial intelligence techniques in chemistry and the material presented highlights this motivation.

In today's technological era, computers are not only used as a tool to complete human work but can also run applications designed to access information quickly. Expert systems are one part of artificial intelligence. An Expert Systems application is an application that transfers expert knowledge to a computer. That way the computer can also solve problems as is usually done by experts. Expert systems have been widely developed in various fields, including the field of animal husbandry. Detection of tetelo disease can use an expert system application. One of them is to detect Tetelo disease. Therefore, breeders can access information about Tetelo disease that is diagnosed with the help of an expert system that uses the Certainty Factor method. The Certainty Factor method serves to determine the degree of certainty of the diagnosis result.

During the last few years many blackouts have been experienced throughout the world. It seems that modern power systems are more exposed to major blackouts. This raises the necessity of having an obvious restoration plan to rebuild the power system as soon as possible. This problem is characterized by a large solution space which can be constrained with expert knowledge. This paper describes a new power system restoration algorithm jointly using genetic algorithms (GA) and expert systems (ES). GA's are used to obtain optimized skeleton networks for power systems, while ES acts as an effective system operator to constrain the solution space for the GA. Also ES allows the GA to be more informed about the overall power system physical performance. This includes, for example, frequency response to sudden load pick up, reactive power balance, load-generation balance, stability limits, high and low voltage levels limits, MW and MVAR reserve requirement and line transfer capability, etc. In order to show the advantages of combining the GA and ES to this problem, this paper presents a comparative result between the hybrid algorithm and pure ES method. The case study presented in this study is 39 IEEE bus systems. The results presented in this paper show that the application of ES can be significantly enhanced by the stated combination.

Applications of expert systems within the design, testing, and operation of communication networks are discussed. The amenability of expert systems to support network monitoring, fault isolation, and system adaptation in degraded modes of operation is evaluated. Specific problems encountered in making network-wide control decisions, with only local or sector system status information that may be corrupted (including knowledge distorted by the presence of ambiguity, uncertainty, and incorrect or conflicting situation data) are presented. Examples of the design and operation of communication networks that use expert systems to support the network control function are discussed in case studies of three expert system projects under development and testing: EXACT (expert-system autonomous-control testbed), COMDAT (communications decision-aid tests), and FIESTA (fault-isolation expert system for TDRSS applications). >