Implementation Of Expert System Research Articles

Development of an Expert System for Diabetic Type-2 Diet

A successful intelligent control of patient food for treatment purpose must combines patient interesting food list and doctors efficient treatment food list. Actually, many rural communities in Sudan have extremely limited access to diabetic diet centers. People travel long distances to clinics or medical facilities, and there is a shortage of medical experts in most of these facilities. This results in slow service, and patients end up waiting long hours without receiving any attention. Hence diabetic diet expert systems can play a significant role in such cases where medical experts are not readily available. This paper presents the design and implementation of an intelligent medical expert system for diabetes diet that intended to be used in Sudan. The development of the proposed expert system went through a number of stages such problem and need identification, requirements analysis, knowledge acquisition, formalization, design and implementation. Visual prolog was used for designing the graphical user interface and the implementation of the system. The proposed expert system is a promising helpful tool that reduces the workload for physicians and provides diabetics with simple and valuable assistance.

Design and Implementation of Instruction Expert System Based on Improved Genetic Algorithm

In this paper, the author designed the model of instruction expert system based on improved genetic algorithm and described the realization of improving exercises in detail. In this system, the students can online learn through different modes and receive the guidance from the teacher, meanwhile the analysis to effect the parameter of intelligent tests generating will be produced. So the following exercises focus on the student’s weakness, this is useful to enhance the students’ the knowledge level and operation ability.

Implementation of Web-Based Expert System for Forest Fire Prevention

In this paper, we have a research of expert system application in forest fire prevention. Carefully analyzing and studying the method and the way of extinguishing forest fire, hard summarizing the domestic and international forest fire prevention technique, making use of the expert system, the WEB technique and the technique of COM, We have designed a network expert system which may predict the fire and may save reasonable with a fire after taking place.

Grounds for the implementation of expert systems to aid the decision-making process in environmental law

Este artigo visa apresentar bases conceituais e teóricas para o desenvolvimento de sistemas de inteligência artificial voltados para a gestão ambiental, assim como alguns desenvolvimentos já realizados neste sentido. Será enfocado o contexto de desenvolvimento de um programa especialista que se propõe a auxiliar o usuário em sua conduta para com o meio ambiente rural, fornecendo educação ambiental e jurídica, desenvolvido ao longo do projeto CRHA (2003-2006). Este trabalho é útil para demonstrar a viabilidade de aplicações computacionais envolvendo as Geociências Agrárias e Ambientais e Ciências Jurídicas, demonstrando também as potencialidades da análise lógica aplicada aos conhecimentos técnicos e científicos.

Implementation of an Intelligent Course Advisory Expert System

Academic advising of students is an expert task that requires a lot of time, and intellectual investments from the human agent saddled with such a responsibility. In addition, good quality academic advising is subject to availability of experienced and committed personnel to undertake the task. However, there are instances when there is paucity of capable human adviser, or where qualified persons are not readily available because of other pressing commitments, which will make system-based decision support desirable and useful. In this work, we present the design and implementation of an intelligent Course Advisory Expert System (CAES) that uses a combination of rule based reasoning (RBR) and case based reasoning (CBR) to recommend courses that a student should register in a specific semester, by making recommendation based on the student’s academic history. The evaluation of CAES yielded satisfactory performance in terms of credibility of its recommendations and usability.

Design, Development and Implementation of a Robust Decision Support Expert System (branDEC) in Multi Criteria Decision Making

In today's dynamic business scenario, in order to sustain within the global turmoil, decision plays a pivotal role. Today's market is completely driven with the choice of the consumer or the end user and toprolong this unprecedented uproar an adroit, firm and stable decision has to be taken. To acclimatize with the changing scenario, the situation demands for development of an expert system to expedite the decision making activity. Advent in MCDM (Multi Criteria Decision Making) techniques diffused with high end mathematical sub-layers isserving this purpose for the past decade. Literature survey reveals lack of availability of a robust expert system encompassing a numerous MCDM techniques, normalization techniques and weight determination techniques. Therefore this project is to mitigate this paucity and to develop a decision support expert system branDEC-V:1R:1 [bran is an eponym derived by taking the first letter of the authors name and DEC is short form of“decision”]which can simultaneously harness all the existing offline MCDM methods and which make a decision avoiding time and computational complexity.

Implementation of expert systems to support the functional evaluation of stand-to-sit activity.

BackgroundFunctional evaluation of sit-to-stand and stand-to-sit activities is often used by physiotherapists in patients with neurological and musculoskeletal disorders. The observation of the way these activities are executed is essential in identifying kinesiological problems. There are different methodologies used to describe the stand-to-sit activity and its evaluation is not yet standardized, which makes the practical application of resources on clinical observation difficult. The objective of this study is to automate the decision making process of an evaluation protocol, developed in previous study, and facilitate its utilization by professionals in the area.MethodsA decision-making system has been implemented through a computational tool, more specifically an Expert System that due its inherent characteristics emulates the decision-making process of a human expert in the domain area. A Shell called Expert Sinta was used to develop two knowledge bases, i.e. two expert systems, one for the anterior view and another for the lateral view of stand-to-sit activity. Variables, values, associated rules and confidence factors, objectives, and additional information questions were defined by the expert of domain and once implemented each expert system generates a number of questions to its user. These questions serve as a guide to physiotherapists and support the standardization of the activity evaluation. The developed systems were evaluated by physiotherapists through the application of a questionnaire that evaluates the knowledge base and the usability of the system. The physiotherapists’ answers were then evaluated through statistical estimation and percentage analysis.ResultsWhen asked about the systems’ “utility for clinical practice of the physiotherapist”, 67% of evaluators answered positively. An interesting finding was that most physiotherapists (i.e. 92%) considered that the systems are suitable for educational purposes, which was not the main objective of this study.ConclusionsThe developed expert systems can support the physiotherapist in evaluating stand-to-sit activity through a conclusion suggestion about the “level of inadequacy” for the “degree of inadequacy” searched during its execution. Results of experts’ evaluation analyzed through statistical methods indicate that the automation of protocols contributed to the standardization of the evaluation of stand-to-sit activity and that it has application for teaching purposes.

ST Algorithm for Medical Diagnostic Reasoning

The authors have previously described an approach for medical diagnostic reasoning based on the ST (Select and Test) model introduced by Ramoni and Stefanelli et al. This paper extends the previous approach by introducing the required algorithm for medical expert system development. The algorithm involves a bottom-up and recursive process using logical inferences, abduction, deduction, and induction. Pseudocode for the algorithm, and the data structures involved, are described, and the algorithm's implementation using a small sample knowledgebase and programmed in Java is included in appendixes. Implementation of a successful expert system is a challenging process; development of the necessary algorithm for its inference engine, and definition of a knowledgebase structure that models expert diagnostic reasoning and knowledge, only fulfils the initial step. Challenges associated with the remaining steps of the development process can be identified and dealt with using the CLAP software process model.

Uncertainty Problem in Decision Support System for Means of Transport Maintenance Processes Performance Development / Problem Niepewności W Systemie Wsparcia Decyzyjnego Procesów Utrzymania W Stanie Zdatności Środków Transportu

Abstract In this paper, the authors’ research work is focused on uncertainty analysis implementation in the developed DSS for transportation means’ maintenance processes performance. Thus, in the Introduction section, the transportation means’ maintenance processes issues and the uncertainty problem are described. Later, there is briefly literature overview in the research area discussed. In the next Section, the expert system for means of transport maintenance processes performance is also investigated. Following this, the uncertainty analysis is developed and the examples of expert system implementation are given. The work ends up with summary and directions for further research.

Pattern classification and audiovisual content management techniques using hybrid expert systems: A video-assisted bioacoustics application in Abdominal Sounds pattern analysis

The current paper focuses on the implementation of hybrid expert systems for audiovisual content description and management, by means of pattern analysis. The proposed methodology combines audio detection–segmentation, surveillance-video motion-detection and hierarchical audio pattern recognition, using neural networks, statistical clustering and syntactic pattern classification. The associated, video-assisted, bioacoustics application focuses on Abdominal Sounds (AS) pattern classification, promising to deliver new potentials in non-invasive Gastro-Intestinal Motility (GIM) monitoring. The current work introduces new techniques for content analysis automation of prolonged multi-channel recordings, facilitating automated GIM auscultation analysis. Thus, it seeks for the establishment of novel diagnostic tools over functional GIM disorders, with the advantage that subjects’ behavior and related psycho-physiological issues can be monitored to further analyze their dependencies. Qualitative and quantitative analysis validated the soundness of the adopted pattern classification taxonomy, resulting remarkable pattern recognition accuracy. Based on preliminary results, the proposed methodology can be successfully applied to general audiovisual content classification, description and management tasks (besides bioacoustics).

Design and Implementation of the Supervisory Control Expert System for Dynamic Scheduling

In the paper, the problem of dynamic scheduling with random disturbance is taken into consideration. Through analyzing the workshop disturbance, the processing strategy and simulation procedure is proposed. On this basis, the supervisory control expert system is developed on the platform of G2. The simulation results given at last illustrate the main function of the system, including manufacturing process monitoring, abnormal event warning, and rescheduling.

DIALOG ACT CLASSIFICATION USING ACOUSTIC AND DISCOURSE INFORMATION OF MAPTASK DATA

Dialog act (DA) classification is useful to understand the intentions of a human speaker. An effective classification of DA can be exploited for realistic implementation of expert systems. In this work, we investigate DA classification using both acoustic and discourse information for HCRC MapTask data. We extract several different acoustic features and exploit these features using a Hidden Markov Model (HMM) network to classify acoustic information. For discourse feature extraction, we propose a novel parts-of-speech (POS) tagging technique that effectively reduces the dimensionality of discourse features. To classify discourse information, we exploit two classifiers such as a HMM and Support Vector Machine (SVM). We further obtain classifier fusion between HMM and SVM to improve discourse classification. Finally, we perform an efficient decision-level classifier fusion for both acoustic and discourse information to classify 12 different DAs in MapTask data. We obtain 65.2% and 55.4% DA classification rates using acoustic and discourse information, respectively. Furthermore, we obtain combined accuracy of 68.6% for DA classification using both acoustic and discourse information. These accuracy rates of DA classification are either comparable or better than previously reported results for the same data set. For average precision and recall, we obtain accuracy rates of 74.89% and 69.83%, respectively. Therefore, we obtain much better precision and recall rates for most of the classified DAs when compared to existing works on the same HCRC MapTask data set.

Implementation of expert system on estimation of fatigue properties from monotonic mechanical properties including hardness

This paper describes implementation of the expert system on estimating fatigue properties from simple tensile data or hardness data. The fatigue properties are usually obtained by performing fatigue tests. However, as fatigue test requires time and high cost, many methods have been proposed to estimate the strain-life curves from monotonic mechanical properties including hardness. Though many useful estimation methods have been proposed and they afford every facility, a mechanical designer has some difficulties in making a decision to select the best method among the several methods for the fatigue strength design or assessment under given conditions. And then several researchers including authors evaluated the methods and proposed the best method according to material. In spite of those guidelines, it does not seem to be always easy for ordinary mechanical designer to apply. In this study, an expert system was developed to facilitate it. A commercial expert system shell, Acquire, was used and the user interfaces of the expert system were developed using Visual Basic. The expert system helps mechanical designer to select the best estimation method among methods for estimating fatigue properties from monotonic mechanical properties including hardness, depending on his or her knowledge level of fatigue and has some special functions to describe recommendation and remarks in detail and display the accuracy and predictability of estimation method.

Design and implementation of fuzzy expert system for Tehran Stock Exchange portfolio recommendation

The key issue for decision making in stock trading is selection of the right stock at the right time. In order to select the superior stocks (alternatives) for investment, a finite number of alternatives have to be ranked considering several and sometimes conflicting criteria that often are vague and have uncertainty conditions. Therefore, we are faced with a special Multiple Criteria Decision Making (MCDM) problem. The purpose of this paper is to develop a fuzzy expert system for selecting superior stocks in order to encounter the uncertainty of stock portfolio recommendation and model the recommendation rules which experts at Tehran Stock Exchange (TSE) use for portfolio recommendation. The results of implementing the designed fuzzy expert system at TSE were affirmative.

Design and Implementation of Safety Expert Information Management System of Coal Mine Based on Fault Tree

Using the principle and method of fault tree and combining computer information system, the safety information closed-loop control system is formed with the characteristics of automatic control and automatic conversion. It has very important significance for coal mine safety to predict and deal with the hidden danger automatically, rapidly and timely. Based on this, we develop a safety information processing system according to fault tree of coal mine, which runs under the way of WEB. In this paper, we firstly introduce the overall structure and the component of the expert system, illustrate the fault tree analysis method in detail; then describe the key technologies and implementation method of software development and the program is given; finally, explain the important role of system implementation in solving the safety information management problem of coal mine.

Fuzzy experts on recreational vessels, a risk modelling approach for marine invasions

Understanding risks from the human-mediated spread of non-indigenous species (NIS) is a critical component of marine biosecurity management programmes. Recreational boating is well-recognised as a NIS pathway, especially at a regional scale. Assessment of risks from this pathway is therefore desirable for coastal environments where recreational boating occurs. However, formal or quantitative risk assessment for the recreational vessel pathway is often hampered by lack of data, hence often relies on expert opinion. The use of expert opinion itself is sometimes limited by its inherent vagueness, which can be an important source of uncertainty that reduces the validity and applicability of the assessment. Fuzzy logic, specifically interval type-2 fuzzy logic, is able to model and propagate this type of uncertainty, and is a useful technique in risk assessment where expert opinion is relied upon. The present paper describes the implementation of a NIS fuzzy expert system (FES) for assessing the risk of invasion in marine environments via recreational vessels. The FES was based on expert opinion gathered through systematic elicitation exercises, designed to acknowledge important uncertainty sources (e.g., underspecificity and ambiguity). The FES, using interval type-2 fuzzy logic, calculated an invasion risk value (integrating NIS infection and detection probabilities) for a range of invasion scenarios. These scenarios were defined by all possible combinations of two vessel types (moored and trailered), five vessel components (hull, deck, internal spaces, anchor, fishing gear), two infection modes (fouling, water/sediment retention) and six frequently visited marine habitats (marina, mooring, farm, ramp, wharf, anchorage). Although invasion risk values determined using the FES approach was scenario-specific, general patterns were identified. Moored vessels consistently showed higher invasion risk values than trailered vessels. Invasion risk values were higher for anchorages, moorings and wharves. Similarly, hull-fouling was revealed as the highest infection risk mode after pooling results across all habitats. The NIS fuzzy expert system presented here appears as a valuable prioritising and decision-making tool for NIS research, prevention and control activities. Its easy implementation and wide applicability should encourage the development and application of this type of system as an integral part of biosecurity, and other environmental management plans.

A fuzzy expert system (FES) tool for online personnel recruitments

The advent of the internet has facilitated greater access to the myriad of job opportunities available globally. Currently there exist many job application submission portals that are being used for online job recruitment purposes. However, the task of many of these job submission portals is limited to matching the professional and academic qualifications of applicants with the requirements of employers and several organisations and does not involve the ranking of applicants' credentials according to their relative suitability for the jobs applied for. In this paper, we describe the implementation of fuzzy expert system (FES) tool for selection of qualified job applicants with the aim of minimising the rigour and subjectivity associated with the candidate selection process. A performance evaluation of the FES tool that was conducted confirmed the viability of a FES-based approach in handling the fuzziness that is associated with the problem of personnel recruitment.

Constructing a Web-Based Fuzzy Expert System for Aeroengine Fault Diagnosis

Based on the analysis of current state of aeroengine fault diagnosis, this paper proposes the design and implementation of a web-based fuzzy expert system called WFESAFD, which is focused on the monitoring and fuzzy fault diagnosis of aeroengine. The system architecture and its components, such as web interface layer, monitor, knowledge acquisition and management, integrated data base, reasoning mechanism and knowledge base are illustrated. The detail process of system implementation and practical applications of WFESAFD are presented to illustrate and prove the proposed system’s applicability. Running results show the feasibility and reliability of the framework, which will be helpful to integrate the aeroengine diagnosis knowledge, improve the diagnosis efficiency and decrease the aeroengine diagnosis cost remarkably.

Using Ontological Reasoning for an Adaptive E-Commerce Experience

As e-commerce applications proliferates the Web, the authors are often overwhelmed by the task of sifting through the copious volumes of information. Since the nature of foraging for information in such digital spaces can be characterized as the interaction between internal task representation and the external problem domain, the authors look at how expert systems can be used to reduce complexity of the task. They describe a conceptual framework to analyze user interactions based on mental representations. They also detail an expert system implementation using the ontology language OWL to express the semantics of the representations and the rule language SWRL to define the rule base for contextual reasoning. The chapter illustrates how an expert system can be used to guide users in an e-commerce setting by orchestrating a cognitive fit between the task environment and the task solution.

A parallelized DPPQN based Expert System method and implementation

In this paper, we propose a parallelized Dual Projected Pseudo Quasi-Newton (parallelized DPPQN) based Expert System method to solve a kind of distributed constrained optimization problem. The proposed parallelized DPPQN based Expert System method differs from the conventional Lagrange method by treating the inequality constraints as the domain of the original variable in the dual function and uses projection theory to process the inequality constraints. The proposed algorithm was implemented in a n + 1 processors network. We also demonstrated the efficiency in solving a typical constrained weighted least squares problem in power system. The parallelized DPPQN based Expert System method associated with a projected Jacobi method can be applied to general large scale nonlinear network optimization problems in large distributed interconnected systems.