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Closing prices of the financial stock market change daily at the end of each session. These changes happen because of many factors that affect the prices of the stocks. This study attempts to accurately predict closing prices by applying a data mining approach and investigate and identify the most influential factors of Dubai Financial Stock Market prices. The main objective of this study is to help...
Association rule discovery algorithms generate all rules satisfying minimum support and confidence thresholds. These techniques yield too many rules and are infeasible when the minimum support is low. Recently, Li [1] proposed the Optimal Rule Discovery (ORD) algorithm that discovers a family of rule sets that maximizes a range of interestingness metrics, other than the commonly used confidence metric...
A limited number of factors in critical areas are necessary to identify the sustainability of companies [30]. It was found that three factors were commonly used [2] and a maximum of seven factors was recommended [2]. In order to identify the optimal factors, we propose a method based on rough set theory that consisted of five main steps. These were data cleansing and preparation, dimensional reduction,...
In most parts of the world, the quality of the electrical power has become a major concern for many electricity users especially the industrial customers. To the power utility, all power quality disturbances must be detected, classified and diagnosed accurately so that proper mitigation measures can be implemented. This paper presents the application of the S-transform and support vector machine (SVM)...
There are various methods in data mining that can be applied in classification data. This paper discusses the experiments done in classifying ICU data. The dataset consists of 25 variables for 410 patients. The goal of this experiment is to determine the survival of the patients, so the targeted output are alive and dead. Three selected data mining methods are decision tree, Naives Bayes and logistics...
This paper proposes a new simple method of Discrete Cosine Transform (DCT) feature extraction that is used to accelerate the speed and decrease the storage needed in the image retrieving process. Image features are accessed and extracted directly from JPEG compressed domain. This method extracts and constructs a feature vector of histogram quantization from partial DCT coefficient in order to count...
Signature zones' identification has been used in signature recognition and verification. The identification of an offline signature requires the whole image of the signature to be processed without considering other features in the signature. One of the signature features that are frequently used as the precondition for other subsequent algorithms in signature recognition and verification is the baseline...
In this work, we have studied the behavior and mobility of a cellular network subscriber who belong to a determined class such as (personal employee, student, retired and others) between different areas. Our contribution in this work is a proposition of a mobility model that reproduce in deterministic and probabilistic case, the possible traffic of cellular network subscriber between specified areas...
Voltage sags are an important power quality problem for which the dynamic voltage restorer (DVR) is known as an effective device to mitigate them. This paper presents a new control algorithm for dynamic voltage restorer (DVR) that mitigates voltage sag by low active power injection with short time delay. This work is based on two-vector control technique using 12 pulse inverter. A smooth control technique...
Conventional methods currently used by power utilities for detecting power quality disturbances are primarily based on visual inspection of the rms value of voltage and current waveforms recorded by power quality recorders. The disturbance detection and classification results can help to identify any potential degrading trends in the electrical system. Once identified, inspection and preventive maintenance...
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