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This paper describes a study to develop a ubiquitous expert system that aims to diagnose dermatological ailment present in a user. Diagnosing dermatological ailments has proven challenging due to the characteristic similarity in the symptoms of various diseases which usually require biopsies that are difficult to accurately read. This has brought about artificial intelligence researches into the automated...
Expert systems based on artificial intelligence techniques help to experts by using in various areas. Especially recently they contribute to a fast and accurate diagnosis in regions that lack doctors by using in medical areas and they can provide confort for both doctors and patients, saving on time and labour-saving by reducing the time for talks between the patient and physician. Heart disease is...
The current research looks at possibilities of creating a smart compiler based on explicit and implicit cluster parallelism, and suggests a design option. With this view, smart compilation procedures are studied, and we also analyze the algorithms of explicit parallelism, and define a production model of and expert system to monitor operations and build a route. We define an algorithm of implicit...
The RETE algorithm is an efficiently organized pattern matching algorithm for implementing production rule systems, used to determine which of the production rules should fire based on its data store. This paper presents how RETE algorithm can be used to improve the efficiency of expert system recommendation. The ‘COURSE FINDER’ is an expert undergraduate course recommendation system. This system...
The work identifies the problem of comparing the analysis results of automated power metering system data produced by using a variety of mathematical, statistical and intelligent methods. Today, operators of such systems analyzing the charts of energy consumption independently decide on inspection of electrical power facilities. With the proliferation of such systems in the household sector, this...
The paper describes the architecture of the information expert system designed and dedicated to stock exchange data processing, analyzing and presentation. The system uses Artificial Neural Networks (ANN) combined with technical analysis and fractal analysis to predict future price of stock exchange assets. It also enables selection of companies, which assets will be increased. The selection of companies...
A compact measuring - information multi-channel spectroellipsometric system for monitoring the quality of aquatic environment, that is based on the combined use of spectroellipsometry and training, classification, and identification algorithms is described. This system is differed from modern analogues by the use of a new and very promising method of ellipsometric measurements, an original element...
Current research in automatic train operation concentrates on optimizing an energy-efficient speed profile and designing control algorithms to track the speed profile, which may reduce the comfort of passengers and impair the intelligence of train operation. Different from previous studies, this paper presents two intelligent train operation (ITO) algorithms without using precise train model information...
A common task in various machine learning (ML) application areas involves observing regularly gathered data for ‘interesting’ events. This mission is predominant in reconnaissance, but also in responsibilities fluctuating from the investigation of scientific data to the observing of unsurprisingly happening events, and from controlling engineering procedures to noticing human behavior. We will refer...
The usage of the neuronetwork model of experts' interaction in forecasting the influence of results of innovation's industrial implantation is offered. The concept of the web oriented expert system construction is proved.
With the advent of modern computer networks, fault diagnosis has been a focus of research activity. This paper reviews the history of fault diagnosis in networks and discusses the main methods in information gathering section, information analyzing section and diagnosing and revolving section of fault diagnosis in networks. Emphasis will be placed upon knowledge-based methods with discussing the advantages...
Data acquisition and analysis of various cardiac /transducer signals based on virtual instrument technology is gaining importance. This paper introduces a novel way of automating the diagnosis of cardiac disorders using an expert system developed on the basis of information derived from the analysis of Electrocardiogram (ECG) and also provides the online monitoring of cardiac patient. Cardiologists...
Document classification tasks can be divided into two sorts: supervised document classification and unsupervised document classification. Supervised learning algorithm always has a better performance than unsupervised learning. However, it is very difficult to assign enough teacher signal. In this study, we developed a customer intention aware system for document analysis. The system starts from an...
A model is proposed for security assessment system based on providing strategy and expert system. A system is designed under the frame of this model which can assess the security risk efficiently. In the process of development, fuzzy theory is employed to analyze the data from port scan, digraph method to analyze the data from vulnerability scan. Expert system CLIPS is used to realize the vulnerability...
In this paper, the optimal design of a wind generator, implemented with the hybridized GA(Genetic Algorithm) and ES(Expert System), has been performed to maximize the AEP (Annual Energy Production) over the whole wind speed characterized by the statistical model of wind speed distribution. In particular, ES has contributed to reducing the excessive computing time maintaining the reliable accuracy...
This paper introduces a new type of finite state machine (FSM) - The FSM based on inexact inference expert system. The paper analyzes the uncertainty of issues of the classic FSM which is major difficulties of the classic FSM, and gives an algorithm of inexact inference in detail according to the uncertainty issues analysis. This new type of FSM based on the algorithm can handle most of uncertainty...
Design of time-way for electroplating machine is a complicated job especially in "H" configuration machine. Experienced engineer are the designers for these job. However, not only the result is not accurated, but also cause more setup time. This paper describes techniques to design time-way for cyclic hoist scheduling (CHS) of electroplating machine, which have an "H" configuration...
With the rapid progress of economy, the land prices change quickly, thus demanding frequent update that is hard to accomplish in time. This paper addresses these problems by employing geographic information system (GIS) and spatial data mining (SDM) to dynamically grade and evaluate the prices of land parcels. In the paper, the author briefly introduced the integrated techniques between GIS and SDM,...
Agricultural informationization is a main trend in agricultural development. Expert system (ES) is a capable assistant during agricultural production. However, now most country areas were not able to use the ES at all, it had influenced and restricted the development of the agricultural informationization seriously. This paper proposed a solution of voice service system of ES, which is suitable for...
In this paper, we present a Modified Robust Particle Swarm Optimization based learning technique for automatic extraction of fuzzy rules and subsequently for updating the parameters of a self-organized neuro-fuzzy network. The learning algorithm of network parameters is based on assigning balanced importance on local and global information. Experiments, conducted with standard benchmark problems,...
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