Rough set theory is a useful tool for data mining. It based on equivalence relations and has been extended to covering-based generalized rough set. This paper studies three kinds of covering sets dealing with the vagueness granularity in information systems. First, we examine properties approximation operations generated by comparison those Pawlak's sets. Then, propose concepts conditions two coverings generate an identical lower operation upper operation. After discussion interdependency...

Trajectory prediction of objects in moving databases (MODs) has garnered wide support a variety applications and is gradually becoming an active research area. The existing trajectory algorithms focus on discovering frequent patterns or simulating the mobility via mathematical models. While these models are useful certain applications, they fall short describing position behavior network-constraint environment. Aiming to solve this problem, hidden Markov model (HMM)-based algorithm proposed,...

Large-scale wireless sensor network (LSWSN) is composed of a huge number nodes that are distributed in some region interest (ROI), to sense and measure the environmental conditions like pressure, temperature, pollution levels, humidity, wind, so on. The objective collect data for real-time monitoring appropriate actions can be taken promptly. One used an LSWSN called sink node, which responsible processing analyzing collected information. It works as station between administrator. Also, it...

High dimensionality is quite commonly encountered in data mining problems, and hence reduction becomes an important task order to improve the efficiency of learning algorithms. As a widely used technique reduction, feature selection about selecting subset being guided by certain criterion. In this paper, three unsupervised algorithms are proposed addressed from viewpoint sparse graph embedding learning. First, using self-characterization given data, we view themselves as dictionary, conduct...

Harris' hawk optimization (HHO) is a recent addition to population-based metaheuristic paradigm, inspired from hunting behavior of hawks. It has demonstrated promising search while employed on various problems, however the diversity agents can be further enhanced. This paper represents novel modified variant with long-term memory concept, hence called HHO (LMHHO), which provides information about multiple regions in problem landscape, for improvised results. With this information, LMHHO...

The need to fight the progressive negative impact of fake news is escalating, which evident in strive do research and develop tools that could this job. However, a lack adequate datasets good word embeddings have posed challenges make detection methods sufficiently accurate. These resources are even totally missing for “low-resource” African languages, such as Amharic. Alleviating these critical problems should not be left tomorrow. Deep learning contributed lot devising automatic...

Graph data have become increasingly important, and graph node clustering has emerged as a fundamental task in analysis. In recent years, gradually moved from traditional shallow methods to deep neural networks due the powerful representation capabilities of learning. this article, we review some representatives latest methods, which are classified into three categories depending on their principles. Extensive experiments conducted real-world datasets evaluate performance these methods. Four...

Rough sets, a tool for data mining, deal with the vagueness and granularity in information systems. This paper studies type of covering generalized rough sets. After presenting their basic properties, this explores inter dependency between lower upper approximation operations, conditions under which two coverings generate same operation, axiomatic systems these operations. In end, establishes relationships sets other literature