Data represents a compendium of information that perpetually expands with each passing moment, contributed by individuals worldwide. Within the domain of medical science, this reservoir of data accumulates at an almost exponential rate, doubling in volume annually. The emergence of advanced machine learning tools and techniques, subsequent to a substantial evolution in data mining strategies, […]
In this paper, we develop a non-visual automatic wrapper to extract data records from search engine results pages which contain important information for computer users. Our wrapper consists of a series of data filter to detect and remove irrelevant data from the web page. In the filtering stages, we incorporate two main algorithms which are […]
Intrusion Detection System (IDS) deals with very large amount of data that includes redundant and irrelevant features. Therefore feature selection is a necessary data pre-processing step to design IDSs that are lightweight. In this paper, a novel feature selection method based on data mining techniques is proposed which uses fuzzy association rules to obtain the […]
Modern distribution system including Distributed Generation (DG) requires reliable and fast islanding detection algorithms in order to determine the grid status. In this paper, a new multi-model classification-based method is proposed, in order to detect islanding condition for photovoltaic units. Decision tree is chosen as the classification algorithm to classify input feature vectors. The final […]
With the availability of websites and the growth of comments, reviews of user-generated content published on the Internet. Sentiment Classification is one of the most common problems in text mining, which applies to categorize reviews into positive and negative classes. Pre-processing has an important role when these textual contexts employed by machine learning techniques. Without […]
Energy losses in the electricity distribution and transmission network and electricity theft detection are major challenges of electricity suppliers around the world. Advanced metering infrastructure (AMI) is an essential segment of the smart grids that is responsible for gathering, measuring and analyzing consuming data of customers. The addition of a security layer to AMI has […]
Today, electricity theft is one of the main challenges for energy distribution and transmission companies around the world. Early detection of abnormal consumers can prevent security and financial losses. Extensive research studies have been done to detect electricity theft by analyzing customer consumption patterns. Today, one of the most widely used methods is convolutional neural […]
