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Highly imbalanced datasets continue to be a challenge in many data mining applications. It is surprising that state-of-the-art techniques countering class imbalances are usually very computationally expensive and therefore unscalable. Most research effort has been directed into enhancing those techniques, e.g., by focusing on borderline examples or combining multiple techniques. This is usually accompanied...
The paper proposes the solution of the actual scientific problem of load balancing and efficient use of distributed system resources. The proposed method is based on the calculation of the load of the central processor, memory and bandwidth fractal information streams of different classes of service for each server and the entire distributed system. The method allows calculating the imbalance of all...
One of the most critical situations in the operation of medium and low speed synchronous generators appears when they are subjected to torque imbalances. This could be the case of internal combustion engines driven generators. In these engines, torque has a periodic oscillation due to variations in the combustion process and pressure development between cylinders. Consequently, a fuel excess or a...
The dispatching in electrical systems always has to face the problem of instantaneous balance between produced power and consumed power. In recent decades, with the advent of distributed generation, especially from non-programmable renewable sources, dispatching has become increasingly more difficult, and more and more attention was paid to the opportunity to limit the imbalances between foreseen...
In the context of grid-connected prosumers with an integrated photovoltaic-battery system, imbalance is the difference between the hourly net energy measured at the point of delivery and the associated forecast. Besides contributing with the increasing of the self-consumption, batteries can also compensate for imbalances if opportunely operated. This paper proposes two strategies to operate batteries...
Imbalanced data streams are found in many real world applications such as spam email detection, and internet traffic data. The classification of such data is challenging, since data stream usually changes, and the model should be updated to maintain the performance. However, obtaining the true labels of the samples to build a new model is not easy, since labeling is expensive and time consuming. Additionally,...
The paper proposes a solution an actual scientific problem related to load balancing and efficient utilization of resources of the distributed system. The proposed method is based on calculation of load CPU, memory, and bandwidth by flows of different classes of service for each server and the entire distributed system and taking into account multifractal properties of input data flows. Weighting...
A critical task in corner detection in 2D images is on the distinction between a corner pixel and a pixel with a large gradient (i.e., an edge pixel). Imbalanced point detection was proposed to address this problem, where a corner pixel is characterized as a pixel with an imbalanced appearance, while an edge pixel has the opposite property. With extensive experiments, an imbalanced point detector...
Data sets are the backbone for data mining and knowledge engineering field. The class imbalance problem exists in many real-time data sets. In this paper we investigate the existing approaches for class imbalance problem in the context of classification and ordinal classification. In particular, this investigation extends the study of issues in ordinal classification with respect to the data set and...
Domain adaptation methods can be highly sensitive to class balance, particularly the usually unknown balance of the unlabeled test set. In this work, we analyze the effect of imbalance on a well-known algorithm, ARTL (Adaptation Regularization Transfer Learning) and propose four approaches for mitigating the adverse effects of imbalance. These include (1) balancing the training set for pseudo-label...
The method of calculating distributed system imbalance based on the calculation of node system load was proposed in the work. Calculation of node system load is carried out by calculating the average coefficient of utilization of CPU, memory, bandwidth of each system node, taking into account multifractal properties of input data flows. The simulation of the proposed method for different multifractal...
Traditional classification algorithms addressing imbalanced-class dataset mostly concentrate on the majority classes' accuracy, such that the minority class's accuracy is usually ignored. Focusing on this issue, we propose a novel classification algorithm using Ensemble Feature Selections (EFS) for imbalanced-class dataset. This algorithm utilizes the superiority of EFS in accuracy, then considers...
In all power sectors around the world the issue of balancing revenues with costs is one of the key elements for the markets' efficiency management and success. When an imbalance of these two parameters occur a financial gap will emerge as a tariff deficit and can generate deep revision of the sector regulation together with impacts on the financial performance of energy companies. AF Mercados is advising...
Long-lead prediction of heavy precipitation events has a significant impact since it can provide an early warning of disasters, like a flood. However, the performance of existed prediction models has been constrained by the high dimensional space and non-linear relationship among variables. In this study, we study the prediction problem from the prospective of machine learning. In our machine-learning...
GitHub has accumulated a great number of developers and open source projects. In this research, we utilize property graph model to explore complex relationships and entities of GitHub. We attempt to answer three questions associated with GitHub using the dataset from MSR2014 data challenge. Firstly, we propose a graph based method to find out the cross technology background developers on GitHub. Secondly...
The development of a model classification intrusion detection using Weighted Extreme Learning Machine was examined with KDD'99 data set ad 4 types of main attack : Denial of Service Attack (DoS), User to Root Attack (U2R), Remote to Local Attack (R2L), and Probing Attack, when comparing the effectiveness of working process of the method presented to SVM+GA[6] and ELM, found that weighted technique...
In this work, piece-wise linear upper bounds to the near- and far-end conversion loss in unbalanced differential lines are cast as function of geometrical parameters of the line cross-section. To this end, the measurement setup exploiting a four-port Network Analyzer is modeled in the modal domain, and the mixed-mode scattering parameters at the line terminations are derived resorting to the assumption...
Data imbalance is a common problem both in single-label classification (SLC) and multi-label classification (MLC). There is no doubt that the predicting result suffers from this problem. Although, a broad range of studies associate with imbalance problem, most of them focus on SLC and for MLC is relatively less. Actually, this problem arising in MLCis more frequent and complex than in SLC. In this...
This work introduces new ensemble margin criteria, to evaluate the performance of Random Forests (RF), in the context of large area land cover classification, using imbalanced and noisy training data. Experiments using binary and multiclass classification problems reveal insights into the behaviour of RF over big data, in which training data contains noise and may not be evenly distributed among classes...
This paper presents a study of applying the equivalent effective voltage concept according to IEEE Standard 1459-2010 for determining reference compensation currents of the three-phase three-wire shunt active power filter in the a-b-c reference frame. The APF reference current calculator is developed and is realized on the DSP board through processor-in-the-loop simulation for validating the effectiveness...
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