In this article, a semi-analytical technique is proposed to predict stable sustained periodic responses of AC electrical machines. Based on such desired outputs, the proper selections of machine variables are captured, such as the perturbation parameter arisen from the relative movement between the stationary and rotating parts. Compared to the experimental results, the derived analytical results are relatively well-fitted with the studied practical cases.
communicated by: H. Bakouch MOS classification numbers: 03E99; 68T27;54A99Deciding participation level of a component to dubious information is essential, particularly all things considered are displaying issues. This paper will present a participation capacity of components that has a place with unverifiable information. The fundamental instrument is the similarity classes that came about because of the likeness connection of a data framework. We will likewise express a few properties and an examination between our work and the past one.
In this paper,we introduce an approach for analysis of information concerning electrical power system. The suggested method is a result of hybridizing rough set concepts with nano topology constructed on the set of all data using the boundary of uncertain decision sets and its lower approximation. Bases of nano topologies are used as indicators for selecting effective features in information system of a power control. This method is applied using the main experimental data which make the suggested model near from the real life information.
Most information systems usually have some missing values due to unavailable data. Missing values have a negative impact on the quality of classification rules generated by data mining systems. They make it difficult to obtain useful information from the data set. Solving the missing data problem is a high priority in the fields of knowledge discovery and data mining. The main goal of this paper is to suggest a method for converting a qualitative information system into a binary system, by using a distance function between condition attributes, we can detect the missing values for decision attribute according to the smallest distance. Most common values can be used to solve the problem of repeated small distance for some cases. This method will be discussed in detail through a case study.
The aim of this work is to introduce an approach for analysis of information system concerning plant diseases. This approach is based on Rough Set Theory and relied on extracting the original data as well as attribute reduction for the final diagnosis of the model of building a tomato
disease to provide practical diagnostic tool. We provided an example that shows how to deal with tomato disease.
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