Combination Of Expert System Research Articles

Potential advantages and limitations of using information fusion in media forensics\u2014a discussion on the example of detecting face morphing attacks

Information fusion, i.e., the combination of expert systems, has a huge potential to improve the accuracy of pattern recognition systems. During the last decades, various application fields started to use different fusion concepts extensively. The forensic sciences are still hesitant if it comes to blindly applying information fusion. Here, a potentially negative impact on the classification accuracy, if wrongly used or parameterized, as well as the increased complexity (and the inherently higher costs for plausibility validation) of fusion is in conflict with the fundamental requirements for forensics.The goals of this paper are to explain the reasons for this reluctance to accept such a potentially very beneficial technique and to illustrate the practical issues arising when applying fusion. For those practical discussions the exemplary application scenario of morphing attack detection (MAD) is selected with the goal to facilitate the understanding between the media forensics community and forensic practitioners.As general contributions, it is illustrated why the naive assumption that fusion would make the detection more reliable can fail in practice, i.e., why fusion behaves in a field application sometimes differently than in the lab. As a result, the constraints and limitations of the application of fusion are discussed and its impact to (media) forensics is reflected upon.As technical contributions, the current state of the art of MAD is expanded by:The introduction of the likelihood-based fusion and an fusion ensemble composition experiment to extend the set of methods (majority voting, sum-rule, and Dempster-Shafer Theory of evidence) used previouslyThe direct comparison of the two evaluation scenarios “MAD in document issuing” and “MAD in identity verification” using a realistic and some less restrictive evaluation setupsA thorough analysis and discussion of the detection performance issues and the reasons why fusion in a majority of the test cases discussed here leads to worse classification accuracy than the best individual classifier

On the Analysis of Web-Based Intelligent English Self-Learning System

With the development of Web-based Intelligent Learning System in the information society, we should pay attention to its usage in autonomous English learning. At first, this thesis shows the basic knowledge of Artificial Intelligence and discusses the feasibility of combining Artificial Intelligence with Web-based Intelligent English self-learning system. Second, it analyzes the combination of Expert system with Web-based Intelligent English self-learning system. Finally, it probes into that this new system will promote the revolutionary of the English self-learning mode.

Study of Intelligence Diagnosis System for Wind Turbine Gearbox Fault

According to the current application and maintenance situation of gearbox of wind turbine, this paper analyzed the remote fault diagnosis system used for monitoring fault occurrence and diagnosing fault, which is a combination of Expert System and Artificial Neural Networks. A practical fault instance of gearbox of wind turbine is analyzed to define the expert system’s knowledge base structure and reasoning method. And verify its feasibility in fault diagnosis by using Matlab language. DOI: http://dx.doi.org/10.11591/telkomnika.v11i8.3107

Mechanical Fault Diagnosis Based on Data Mining Technology

Data mining is a variety of analysis tools using the data found in the mass relationship between model and data technology, and relationships of these models can be used to predict. Organically with the combination of expert system, can solve the problem of automatic acquisition of knowledge. It from a large number, incomplete, noisy, fuzzy, random data mining the hidden decision-making has important reference value to generate the information. Data mining technology used in machinery fault diagnosis system, the scene of large quantities of raw data into valuable knowledge for specialists to explore the information they are interested in, but also describes the evolution trend of mechanical malfunction, the expert decision-making support information. And, after years of development, data mining technology has matured and widely used. The purpose of this study is that data mining technology used in machinery fault diagnosis and to study its feasibility. If applicable, must be able to open up a mechanical fault diagnosis, a new diagnostic method, which greatly promote the development of mechanical fault diagnosis technology.

Hybrid intelligence utilization for construction site layout

In case of the shortages and limitations in solving the problem of construction site layout, there is a need for simulation prior to work commencement. By using a combination of Expert System (ES) and Artificial Neural Networks (ANN) technology, a new methodology for solving this problem has been developed. This system applies hybrid intelligence technology, and is presented in this text. Based on site investigation and analysis of effective factors in site layout, a hybrid intelligence model and system, named Hybrid System for Site Layout (HSSL), was developed. The evolution of this concept and its mechanism of integration are delineated in this text, so as to allow the reader to have an overview of its content, while at the same time providing for the specifics of how the system operates.

Pressure control of a Moscow water supply system using expert system technology

Automating the pressure control of typical Russian types of water distribution systems can result in greater than average benefits. The potential exists for improving the system efficiency and reliability while reducing the on-line operational manning requirements. To this end the paper presents modelling and simulation studies of the current semi-manual and the proposed fully automatic pressure control schemes for the Zelenograd water supply system. Dynamic operational simulations are an essential feature of the project. However, it was necessary to enhance the network hydraulic simulator, to include pressure feedback controls, in order to produce acceptable results. Analyses of the operational requirements and the simulation results provide a basis for the design of an improved controller using an expert system approach. A major part of the paper covers the methods in use for obtaining an adequate set of control rules for the Zelenograd system. Extended time period operational simulations are used to verify the rules and to compare the results with those of existing practice. There are expectations of immediate benefits in terms of operating economies. Typically these will arise from reductions in water leakage, electricity charges and control manpower. Work is now proceeding on actual implementation using a combination of expert system and fuzzy logic methods.

NETMAT: a knowledge-based grid system analysis tool

The increasing expansion of electric power systems renders the power system operator's task increasingly complex. The integration into energy management systems of further analytical algorithms implies that more data has to be analysed by the control engineer. For these reasons and many others, more sophisticated tools are required by power engineers to ease the pressure under which they perform their task. The advent of knowledge-based systems has led to a new approach to the problem. The combination of expert systems and numerical algorithms can be advantageously exploited to assist the power system engineer in operating the system. This paper presents the development of a knowledge-based tool for grid system analysis. The tool, NETMAT (NETwork Modelling AssistanT) , is to be used to analyse the impact of grid system maintenance and modification procedures and of new generating plants on power utilities, and in particular on their ability to generate and sell electricity. NE TMAT consists of a number of numerical applications interfaced to an expert system shell through specific problem domain knowledge bases. Results are presented based on the use of the IEEE-30 busbar network as a test network.

A PC-based expert system assistant for power system operational control

In general, conventional computer programs manipulate data and hence stress the efficiency of these numerical manipulations. Expert systems, on the other hand, manipulate knowledge and emphasize the use and accuracy of the knowledge represenation. The combination of expert systems and numerical algorithms can be exploited adBantageously to assist the power engineer in the decision-making processes of system control. This paper discusses the integration of an optimal power flow program, expert system and database for an application for Scottish Hydro-Electric Plc, which is responsible for the generation, transmission and distribution of electricity in the North of Scotland. The guidance afforded by the expert system in consultation with the optimal load flow and databases is shown to support an improved operating state.

Expert System for Cold-Forging Process Based on FEM Simulation

Since it is difficult to collect universal and reliable knowledge Por cold forging from human experts, a method to utilize the result of FEN simulation as a sort of experience for expert system is proposed. In this method, the necessary data Por expert system are collected from hundreds of simulations. The data are transformed Into the rules by using statistical technique and neural networks. It is Pound that the combination of expert system with FEN simulation and neural networks is effective for knowledge acquisition. The problem of self-learning of knowledge can be partly realized by Introducing the neural networks.

Fuzzy Match and Floating Threshold Strategy for Expert System in Traditional Chinese Medicine

The expert system has been used in the computerized diagnosis and treatment system in traditional Chinese medicine. The fuzzy match and floating threshold has been adapted in the expert system. Combination of expert system and data base technique will produce a conception of the large-scale expert system.