Electric Network Power Quality assessment using Fuzzy Expert System Methodology

An important aspect of the production of quality software is that of software assessment and certification. This involves the measurement of a finished software product using a set of recognised Software Assessment Units. It is essential that at the specification of a piece of software a set of relevant software attributes with a suitable subset of Assessment Units is identified. The set is used to determine whether or not the finished product meets an appropriate quality standard. It has been recognised that a Software Assessment Advisor (SAA) is a necessary tool to assist with this task. An SAA can help in determining the software attributes which should be measured and in selecting an appropriate set of Assessment Units. The SAA will use information concerning the categorisation and functions of a proposed software product, the user's requirements, available tools, and prior assessment experiences in these tasks. So far, no clear approach has been identified for the development of an SAA. The investigation of the modelling required by an SAA indicates that Expert Systems techniques could provide a useful step forward in this development. Expert Systems techniques are able to relate the information required by the certification procedure intelligently by means of the knowledge model and to support symbolic reasoning to advise the software certifier. Also an Expert System's capability for knowledge learning is significant with respect to the relatively young area of Software Assessment and Certification. This paper discusses the activities involved in the Assessment and Certification process, describes how an SAA can assist for the process and how an Expert Systems approach has been used in the development of a prototype SAA.

Assessing the performance of academics at different levels is increasingly difficult to achieve using traditional methods based mainly on numerical scores in evaluating teaching and research activity. The indexing of academic performance in various international databases with impact indices at different scales has led to the need for advanced computer models, such as expert systems based on fuzzy logic, proposed in this research, which address the evaluation of teachers even in the face of imprecise information and under conditions of uncertainty. In this research, as a contribution and novelty, a fuzzy logic model was developed in which an algorithm was simulated and implemented in Matlab using the Mandami toolkit, which allows inference of the rules of fuzzy logic and visualization. 3D. The system implementation was done by software in Matlab environment, using systems with fuzzy Mandami logic. The result of this pilot study was to test and validate the proposed model through a graphical interface, giving the results according to minimum criteria and with additional explanations.

Power transformers are very vital components in electrical power network. Deterioration of transformer’s insulation has significant impacts on its health condition. Hence, detailed analysis of insulation testing attributes is very important in diagnosing the transformer. It is possible with an effective decision-making system. In the present paper, a new grey relational-based fuzzy logic expert system is proposed for continuous health monitoring of power transformers. In this approach, ranking-based qualitative relational analysis is initially carried out in order to reduce large number of input attributes into three input health grades. These input grades are further integrated with a technically designed expert fuzzy rule base. Outputs of the proposed model are validated with the outputs of multi-criterion based fuzzy logic model presented in [Mharakurwa E T and Goboza R 2019 Multiparameter-based fuzzy logic health index assessment for oil-immersed power transformers Adv. Fuzzy Syst. 2019]. Testing data of 200 in-service transformers are utilised in the validation of both the models. It is observed from the comparison that similarity index of the proposed grey-fuzzy system is 92 percent. Several issues exist in regular transformer health assessment models such as the large number of rules, uncertainties, requirement of large training data, complexity issues are overcome by integrating the grey relational analysis with the fuzzy logic system. The proposed model can be easily implemented by all utilities and diagnostic experts of transformers.

Limitations on the representation of knowledge, and hence the inference methods, naturally limit the domains of the first-generation expert systems. In response to these limitations, fuzzy expert systems or the second-generation of expert systems provide two essential and unique advantages in the design, development, and implementation of expert systems: (1) fuzzy knowledge representation and (2) fuzzy inference methods. It is suggested that second-generation expert systems be designed and implemented with the expressive powers of representation and improved inference methods based on fuzzy logic. A number of research topics and application areas are identified. >

Several applications need to stock and interrogate fuzzy data in a flexible manner. Unfortunately, these two requirements are not supported by the database management systems which currently dominate the databases servers market. Several works have tried to cure these insufficiencies; we speak henceforth of fuzzy databases and flexible querying of these databases. The design problem of such databases did not receive the interest that it deserves. The fuzzy data types are numerous and varied what puts the designer of a fuzzy database in front of a complex problem of choice. In this paper, we propose an approach based on an expert system which helps the designer to choose the appropriate data types for the columns susceptible to stock fuzzy data or interrogated by flexible queries. This solution suits the migration toward a fuzzy database as well as a fuzzy database under design. Although this solution is based on the fuzzy model GEFRED (GEneralised model for Fuzzy RElational Database), it can be applied to other fuzzy models. This expert system can be integrated into the classic design environments like Rational Rose, Power AMC, etc.

Knowledge-based operation and management of communications systems

In construction, many owners mitigate the risk of unforeseen contractor default by accepting only bonded contractors who must endure a rigorous evaluation process by surety brokers and surety underwriters. This evaluation process includes a financial analysis and a review of work on hand and past performance, all of which have reliable structured methods for their evaluation. Additionally, a number of subjective criteria are considered that are more difficult to capture and assess objectively but which can be modeled effectively using fuzzy logic. The purpose of this paper is to illustrate how fuzzy logic and expert systems can be combined to provide a structured approach to evaluating contractors for surety underwriting purposes. Fuzzy logic is used to model both the objective and subjective factors considered in contractor evaluation using linguistic terms, and expert rules are used to capture the surety experts’ reasoning process. A fuzzy expert system, SuretyAssist, is presented that can be used to provide an initial evaluation of general contractors as well as periodic reviews to determine whether or not to accept them as clients for bonding. SuretyAssist was validated using 31 actual cases of contractor evaluation and found to be accurate in 81% of the cases.

8 - Real-time fault-tolerant control systems

Decreasing supporting resources and increasing complexity of horticultural crop production necessitate the new technologies be developed to transfer information to farmers as well as commercial producers. Expert systems, a sub area of artificial intelligence of computer science offer the possibility to implement horticultural knowledge into field practice in the form of computer programme in order to support the farmers in decision making at farm level. This paper provides an overview of the concept of expert system and examples of areas of horticultural applications of these systems are in use at present are also outlined. This paper further examines how expert system techniques are being used at present in problem solving and why someone in the field of horticulture might want to use them.

Diagnosing the vibrating behaviour of the PWR internal structures using expert systems techniques and algorithmic treatment

As environmental regulations become more stringent, manufacturers are confronted with the of productdesign considering environmental impacts. Life Cycle Analysis (LCA) is a developing technique that attacks this problem. LCAs provide environmental information for decision making by consumers, manufacturers, and governments. These decisions significantly affect the ability to maximize source reduction, re-use, recyclability, and recycled content. LCAs can aid in diminishing the negative impact a product has on the environment and can be utilized as a partial solution of our nations' (worlds') growing waste management problem. To date, the application of LCAs has varied from product comparison to process development and improvement. The results from these analyses have differed because of differing assumptions and differing choices of boundary conditions. An appropriate Life Cycle Analysis should be consistent across products, locations, and especially across experimenters. The development of LCAs lends itself to computer-assisted design methods such as the techniques of Expert Systems, due to the large amount of information associated with successfully developing an LCA. In this paper, we will discuss using Hierarchical Classification, a specific task specific architecture expert systems approach, to organize the terms necessary in performing an LCA. Although not yet definitive, we believe our experience indicates that such approaches to organizing the vast knowledge necessary to accomplish an LCA may be a key factor in eventual successful development of comprehensive LCAs in industry.

An assessment of neonatal outcome may be obtained from analysis of blood in the umbilical cord of an infant immediately after delivery. This can provide information on the health of the newborn infant and guide requirements for neonatal care, but there are problems with the technique. Samples frequently contain errors in one or more of the important parameters, preventing accurate interpretation and many clinical staff lack the expert knowledge required to interpret results. The development and validation of an expert system to overcome these difficulties is described. The initial development utilised conventional 'crisp' logic within the rule base and this system was evaluated to commercial release. This expert system validates the raw data, provides an interpretation of the results for clinicians and archives all the results, including the quality control and calibration data, for permanent storage. Subsequent development went on to incorporate fuzzy logic into part of the expert system knowledge base, but tests of this preliminary fuzzy system showed that it performed worse than the original crisp expert system. A tuning algorithm was then employed to modify the fuzzy model and this process resulted in improved performance to a level comparable to clinicians and superior to the crisp system. Finally, the entire knowledge base was converted to utilise fuzzy logic and this 'integrated' fuzzy expert system was validated against international expert opinion.

Intelligent process-control system design

Today, with the rapid technological development, interest in electric vehicles is also increasing. This raises the question of what the effects of the vehicles on the electric power network will be. In this article, the adverse effects of charging scenarios of electric vehicles' batteries on the electric power network are examined and fuzzy logic based solutions are proposed to prevent or reduce the effects of charging electric vehicles during peak hours. In this article a fuzzy logic system that is providing the cheapest charging prices, also reducing the impact on the load curve of Turkey’s electrical network is provided.

Ebinformatics: Ebola fuzzy informatics systems on the diagnosis, prediction and recommendation of appropriate treatments for Ebola virus disease (EVD)