Development Of Expert System Research Articles

REVIEW OF METHODOLOGIES AND APPLICATIONS OF EXPERT SYSTEMS: OPTIMIZATION PERSPECTIVE

A comprehensive study of research carried out by eminent researchers givesa critical analysis of concepts, methodologies and applications used for their research work. It gives context for the continuation of ongoing research or inspires new research ideas.In general, a literature evaluation aids in the identification of research gaps. This research paper presents a systematic study of components, methodologies and applications of various expert systems introduced in the diverse range of sectors. This paper surveys the development of expert systems through the study of various research articles related to the expert system methodologies, applications, and components that include knowledge acquisition, knowledge representation schemes, inference engines, learning tools etc.

A Narrative Improvement Techniques Used with The Expert Systems

The technologies used for an expert system development have a vital role and take the design to the next level of innovation. These innovations offer essential help to save lots of energy, resources and conjointly to secure the specified infrastructure. The paper concentrates on the innovative technologies used for building an expert system. An expert system also contains associate Interface within users interact and an Interface Engine that performs data reasoning. The planned design interconnects multiple programming languages, hardware and software parts to build the system.

A practical review and taxonomy of fuzzy expert systems: methods and applications

PurposeExpert systems are computer-based systems that mimic the logical processes of human experts or organizations to give advice in a specific domain of knowledge. Fuzzy expert systems use fuzzy logic to handle uncertainties generated by imprecise, incomplete and/or vague information. The purpose of this paper is to present a comprehensive review of the methods and applications in fuzzy expert systems.Design/methodology/approachThe authors have carefully reviewed 281 journal publications and 149 conference proceedings published over the past 37 years since 1982. The authors grouped the journal publications and conference proceedings separately accordingly to the methods, application domains, tools and inference systems.FindingsThe authors have synthesized the findings and proposed useful suggestions for future research directions. The authors show that the most common use of fuzzy expert systems is in the medical field.Originality/valueFuzzy logic can be used to manage uncertainty in expert systems and solve problems that cannot be solved effectively with conventional methods. In this study, the authors present a comprehensive review of the methods and applications in fuzzy expert systems which could be useful for practicing managers developing expert systems under uncertainty.

ІНФОРМАЦІЙНО-КОМУНІКАЦІЙНІ ТЕХНОЛОГІЇ В ОСВІТІ ЯК СКЛАДОВА ПЕДАГОГІЧНОЇ НАУКИ УКРАЇНИ В ГАЛУЗІ ТЕОРІЇ ПЕДАГОГІКИ В 90-Х РОКАХ ХХ СТОРІЧЧЯ

Удосконалення системи підготовки наукових кадрів з інформаційно-комунікаційних технологій в освіті спирається на досвід розвитку досліджень у цій науковій галузі, що, своєю чергою, потребує уваги до історії. В історико-педагогічних працях ретельно проаналізовано розвиток наукових досліджень з теорії та методики інформатики (13.00.02) та сучасної спеціальності 13.00.10 – Інформаційно-комунікаційні технології в освіті. Дослідження інформаційно-комунікаційних технологій в освіті кінця ХХ і початку ХХІ століть з точки зору теорії педагогіки, дидактики, теорії та методики професійної освіти висвітлені недостатньо. Метою даної роботи є аналіз підготовки кадрів вищої кваліфікації з інформаційно-комунікаційних технологій як складової наукових досліджень у 90-х роках ХХ сторіччя в межах наукової спеціальності 13.00.01 – Теорія і історія педагогіки. За результатом перегляду каталогів та електронних ресурсів Національної бібліотеки України імені В. І. Вернадського (nbuv.gov.ua) та фондів наукової бібліотеки ХНПУ імені Г. С. Сковороди виявлено 22 дисертації, які були захищені в 90-х роках ХХ сторіччя за спеціальністю 13.00.01 і за змістом пов’язані з використанням інформаційно-комунікаційних технологій в освіті. У цих наукових працях здійснено науковий аналіз та презентовано практичні напрацювання в напрямах створення та використання комп’ютерно орієнтованих засобів навчання, психолого-педагогічного аналізу методів навчання за допомогою інформаційно-комунікаційних технологій, розвитку змісту й розробки методичних систем навчання інформатичних дисциплін та інформаційно-комунікаційних технологій у різних галузях освіти, проблем застосування інформаційно-комунікаційних технологій для вимірювання рівня навчальних досягнень; поставлено питання стосовно розробки експертних систем для оптимізації педагогічного проєктування та запропоновано модель застосування інформаційно-комунікаційних технологій в управлінні освітою на рівні району. Аналіз авторефератів дисертацій дав змогу визначити наукові центри в Україні, у яких були виконані відповідні дослідження, та установи,у яких відбулись захисти дисертацій, і визначити провідних фахівців, які виявились найбільш активними в підготовці кадрів вищої кваліфікації з теорії педагогіки (13.00.01) в напрямку застосування інформаційно-комунікаційних технологій в освіті в 90-х роках ХХ сторіччя.

An expert system for vehicle accident reconstruction

The paper presents the capabilities of the developed expert system for vehicle accident reconstruction. The system determines converted energy for each vehicle, post-collision and pre-collision vehicles speeds, vehicle braking deceleration, the times in the braking process and total stopping distance. This system provides an opportunity to investigate the impact of various parameters at vehicle accident reconstruction. The developed expert system significantly reduces the time for the preparation of the expertise and the admission of errors. It can be used in expert practice and training.

МОДЕЛИРОВАНИЕ ТРАЕКТОРИИ ДВИЖЕНИЯ АВТОМОБИЛЯ ПРИ ИССЛЕДОВАНИИ ДОРОЖНО-ТРАНСПОРТНЫХ ПРОИСШЕСТВИЙ

The article proposes one of the ways to evaluate the trajectory of the cars movement in the study of the causes of the occurrence and reconstruction of the traffic accidents circumstances. The aim is to propose, based on the theory of fuzzy sets and experimental studies, a method for reducing the uncertainty of constructing the calculated trajectory of a vehicle during braking under inaccurate initial data. The basis of the proposed method is a mathematical model for evaluating the trajectory of a vehicle during braking, which allows for the redistribution of vertical reactions not only along the axes, but along the sides of the car, and makes it possible to determine the instant of occurrence of the skid of each wheel by the criterion j/g. A feature of the proposed method is the use of previously developed expert systems for evaluating the braking torques on the wheels of the car and determining the coefficient of adhesion of the car with the road. The use of fuzzy expert information on the importance of factors that affect brake moments and the coefficient of adhesion allows to reduce the volume of experimental studies and significantly shorten the time to reach an objective decision on the causes of emergencies. The discrepancy between the results of the expert system forecast and the experimental data is 5% and 3%, respectively. Presented are the results of experimental studies of the behavior of the car during braking in road conditions, taking into account the magnitude of the braking torques that were applied to the wheels of the car, the magnitude of the coefficient of adhesion along the sides of the car, as well as the transverse displacement of the center of mass of the car due to uneven distribution of cargo. The maximum error in the discrepancy between the simulation results and the experimental data does not exceed 8%. A reference algorithm for estimating the trajectory of a vehicle during braking is presented, which allows one to take into account the stochastic and indistinct uncertainty of the initial data and reduce the range of possible modeling error by 39%. Investigation of road accidents related to changing the trajectory of the car during braking, confirmed the possibility of applying the proposed method in the auto-technical examination.

Perancangan Sistem Pakar Gejala Penyakit Saluran Pencernaan Dengan Pengobatan Tanaman Herbal Berbasis Web

Abstract - Expert system is a software package or computer program package that is intended as a provider of advice and help tools in solving problems in certain areas of specialization such as medical, education, and so on. The development of the development of expert systems in the biomedical field is one thing that is expected to improve the quality of human life. One of them is by applying an expert system by using the Forward Chaining method to diagnose psychotic disorders due to substances. This study aims to increase knowledge about how to make an inference engine to control the process of identifying solutions using the Forward Chaining method, as well as designing expert system applications using the Forward Chaining method to diagnose substance-induced psychotic disorders.
 Keywords: Expert System Programs, Digestive Diseases, Herbal Plants

Heart Arrhythmia Classification Based on Statistical Moments and Structural Co-occurrence

The electrocardiogram (ECG) is a widely disseminated method for detecting heart diseases due to its lower cost than other tests. But, some steps are important for detecting cardiac arrhythmias in ECG signals, which are: preprocessing, segmentation, feature extraction and classification. In this work, we assess how four non-morphological feature extraction methods provide useful ECG classification. Moreover, we propose an innovation in the configuration of the structural co-occurrence matrix (SCM), by combining it with the Fourier transform to extract the main frequencies of the signal. We tested theses methods on four well-known classifiers used in the literature and compare the results with six classical feature extraction methods. Moreover, we followed high standard protocols for developing expert systems for clinical usage. The database chosen for evaluation is the MIT-BIH arrhythmia database. We increased the identification of heart dysrhythmia by 2%, representing an advance on reports on the literature. The developed system is 1.3% more reliable than the current best approach reported, being \(10^6\) times faster, as well. The HOS with naive Bayes classified pathologies in 22 patients with 94.3% of accuracy. We perceived that SCM–Fourier is 1.5% more accurate than the SCM or Fourier standalone. The feature extractor proposed in this paper compress 97% of the useful information to provide a reliable arrhythmia classification.

Expert System Development for Course Enrollment Process Using Ripple Down Rules in a University in Surabaya

The research aimed to develop expert system for helping lecturers to decide which courses to be taken by students in the next semester. The expert system contained specific pieces of knowledge to solve specific problems involved in the forms of system development and maintenance. This expert system was in the form of a website using the PHP programming language and MySQL database. The researcher used the Ripple Down Rules (RDR) method to identify the courses by putting forward the questions so that the system could decide which courses the students should take in next semester. The result shows that this web-based expert system can identify which courses that the students have to enroll after the students have answered questions generated by the system. The available data on the courses in the system adapt to the rules, so it is in line with the enrolled courses.

Development of Expert System for the Selection of 3D Digitization Method in Tangible Cultural Heritage

Development of Expert System for the Selection of 3D Digitization Method in Tangible Cultural Heritage

Data mining methodology employing artificial intelligence and a probabilistic approach for energy-efficient structural health monitoring with noisy and delayed signals

Numerous methods have been developed in the context of expert and intelligent systems for structural health monitoring (SHM) with wireless sensor networks (WSNs). However, these techniques have been proven to be efficient when dealing with continuous signals, and the applicability of such expert systems with discrete noisy signals has not yet been explored. This study presents an intelligent data mining methodology as part of an expert system developed for SHM with noisy and delayed signals, which are generated by a through-substrate self-powered sensor network. The noted sensor network has been demonstrated as an effective means for minimizing energy consumption in WSNs for SHM. Experimental vibration tests were conducted on a cantilever plate to evaluate the developed expert system for SHM. The proposed data mining method is based on the integration of pattern recognition, an innovative probabilistic approach, and machine learning. The novelty of the proposed system for SHM with data interpretation methodology lies in the integration of the noted intelligent techniques on discrete, binary, noisy, and delayed patterns of signals collected from self-powered sensing technology in the application to a practical engineering problem, i.e., data-driven energy-efficient SHM. Results confirm that the proposed data mining method employing a probabilistic approach can be effectively used to reconstruct delayed and missing signals, thereby addressing the important issue of energy availability for intelligent SHM systems being used for damage identification in civil and aerospace structures. The applicability and effectiveness of the expert system with the data mining approach in detecting damage with noisy signals was demonstrated for plate-like structures with an accuracy of 97%. The present study successfully contributes to advance data mining and signal processing techniques in the SHM domain, indicating a practical application of expert and intelligent systems applied to damage detection in SHM platforms. Findings from this research pave a way for development of the data analysis techniques that can be employed for interpreting noisy and incomplete signals collected from various expert systems such as those being used in intelligent infrastructure monitoring systems and smart cities.

Early Childhood Development Detection based on Expert System and Developmental Pre-Screening Questionnaire

Psychology Bureau of Universitas Setia Budi (BP-USB) has a role in the life of the Surakarta city community as an officer carrying out child development checks using the KPSP form. Based on the results of interviews, BP-USB has obstacles in the process of examining the early childhood development, that the ineffectiveness of the inspection in terms of aspects: cost, energy and time. This study aims to build an early childhood development inspection based on android system using an expert system with the Forward Chaining Method based on KPSP to increase the effectiveness of examination time. The final results showed that the early childhood development expert system was able to shorten the examination time significantly. The effectiveness of examination time increased by 65%.
 Keywords: developmental pre-screening questionnaire, KPSP, expert system, forward chaining

Design and Development of Human-Computer Interaction through Judicial Expert System for Violence against Female

This paper focuses on Human-Computer interaction by designing and implementing for Crimes against Women Judicial Expert System (CAWJES). This CAWJES imitates the role of a lawyer or guidance counselor of NGO to offer a virtual mentor. Lawyer or legal advisers will at all times use this system to determine the crime happened on the women. However, CAWJES designed to change this manual system into computerized system. The CAWJES is rule-based expert system. Development of CAWJES carried out by using expert system development life cycle. This paper focuses on Human-Computer Interaction (HCI) applied in CAWJES.

An expert system for checking the correctness of memory systems using simulation and metamorphic testing

During the last few years, computer performance has reached a turning point where computing power is no longer the only important concern. This way, the emphasis is shifting from an exclusive focus on the optimisation of the computing system to optimising other systems, like the memory system. Broadly speaking, testing memory systems entails two main challenges: the oracle problem and the reliable test set problem. The former consists in deciding if the outputs of a test suite are correct. The latter refers to providing an appropriate test suite for determining the correctness of the system under test.In this paper we propose an expert system for checking the correctness of memory systems. In order to face these challenges, our proposed system combines two orthogonal techniques – simulation and metamorphic testing – enabling the automatic generation of appropriate test cases and deciding if their outputs are correct. In contrast to conventional expert systems, our system includes a factual database containing the results of previous simulations, and a simulation platform for computing the behaviour of memory systems. The knowledge of the expert is represented in the form of metamorphic relations, which are properties of the analysed system involving multiple inputs and their outputs. Thus, the main contribution of this work is two-fold: a method to automatise the testing process of memory systems, and a novel expert system design focusing on increasing the overall performance of the testing process.To show the applicability of our system, we have performed a thorough evaluation using 500 memory configurations and 4 different memory management algorithms, which entailed the execution of more than one million of simulations. The evaluation used mutation testing, injecting faults in the memory management algorithms. The developed expert system was able to detect over 99% of the critical injected faults, hence obtaining very promising results, and outperforming other standard techniques like random testing.

Mivar models of reconstruction and expertise of emergency events of road accidents

The article deals with the problem of creating expert systems for the reconstruction and analysis of motor vehicle accidents (MVA). The need for development of the special expert system of the analysis and examination of road accident for the solution of this problem was formulated. Also, in the article the compatibility models of the Mivar Expert System and the abstract system of simulation modeling were described. In this article, the Mivar expert system “Analysis MVA” is considered as a promising solution for the reconstruction and analysis of traffic accidents. Much attention is drawn to the principles of operation of the mivar systems in the expert analysis of accidents.

SeDeM Expert System：A review and new perspectives

The SeDeM Expert System was first known as a galenic pre-formulation system, which was based on the experimental research and quantitative determination of powdered substances. And the mathematical formula provided by the SeDeM Expert System has plays an important role in the study of powder properties. The system can be used not only to evaluate the powder direct compression (DC) of excipients and active pharmaceutical ingredients (API's), but also to predict the possible formulations, so it can reduce unnecessary research and trials, and shorten the time of development. In this paper, the research development and application of SeDeM Expert System in DC was summarized, and the results showed that with a few exceptions, the system was skilled in predicting acceptable tablet formulations. Finally, the new application prospect of the system is presented, including the application of the Internet traffic and content management (iTCM) database and the new co-processed excipients.

The modern concept of selecting publications for the research library collections

In recent decade, the collection development expert system has been introduced into acquisition practice at the RAS Library for Natural Sciences CLS. Its major components are: the «experts’ institute», information base (Russian Book Chamber database, publishers’ information), and evaluation system. The system long-term successful operation is provided by simple and friendly interface, both for experts and acquisition librarians and applied technological solutions. Implementation of the system enables to solve a series of problems of research libraries: prompt informing scholars on the works published in the country, developing library collection that meets users’ information needs to full extent. The statistical data obtained from the expert system enables acquisition librarians to clarify selection criteria for nonperiodic domestic publications, to form the list of publishers, whose products are mostly demanded by scholars, important subjects and documents corresponding them. The statistical data for 2008–2017 (the experts’ roaster, the scope of their research interests; information of participants of domestic market of scholarly literature; data on scholarly publications demanded by scholars, etc.) are presented in the paper and conclusions are made upon them.

Development of Expert System by using Logical Comparative Conclusion in the Function of Organizational Performance Improvement

Development of Expert System by using Logical Comparative Conclusion in the Function of Organizational Performance Improvement

English

This study is concerned with the water coning phenomenon that takes place around production wells of hydrocarbon reservoirs. In this paper, the development of artificial neural networks to predict the water saturation buildup around vertical and horizontal wells with a good level of accuracy is described. In the development of expert systems, it is assumed that water encroachment originates from an active aquifer which is located under the hydrocarbon reservoir (reservoir with bottom water drive). A high-fidelity numerical model is utilized in generating training data sets that are used in structuring and training the artificial neural networks. The artificial expert systems that are developed in this paper are universal and are capable of predicting the change of water saturation around the wellbore as a function of time and the prediction process is faster than a reservoir simulator and requires less data, which saves time and effort. With the help of these models, it will be possible to predict the position of high water saturation zones around the wellbore ahead of time so that remedial actions such as closing the perforations that produce the water can be implemented on a timely basis. Key words: Bottom water drive, water coning, neural network, water saturation, vertical well, horizontal well. &nbsp

ADAPTIVE LEARNING EXPERT SYSTEM FOR DIAGNOSIS AND MANAGEMENT OF VIRAL HEPATITIS

Viral hepatitis is the regularly found health problem throughout the world among other easily transmitted diseases, such as tuberculosis, human immune virus, malaria and so on. Among all hepatitis viruses, the uppermost numbers of deaths are result from the long-lasting hepatitis C infection or long-lasting hepatitis B. In order to develop this system, the knowledge is acquired using both structured and semi-structured interviews from internists of St.Paul Hospital. Once the knowledge is acquired, it is modeled and represented using rule based reasoning techniques. Both forward and backward chaining is used to infer the rules and provide appropriate advices in the developed expert system. For the purpose of developing the prototype expert system SWI-prolog editor also used. The proposed system has the ability to adapt with dynamic knowledge by generalizing rules and discover new rules through learning the newly arrived knowledge from domain experts adaptively without any help from the knowledge engineer