The transition of customers from one telecom operator to another has a direct impact on the company's growth and revenue. Traditional classification algorithms fail to predict churn effectively. This research introduces a deep learning model for predicting customers planning to leave to another operator. The model works on a high-dimensional large-scale data set. The performance of the model was measured against other classification algorithms, such as Gaussian NB, Random Forrest, and Decision Tree in predicting churn. The evaluation was performed based on accuracy, precision, recall, F-measure, Area Under Curve (AUC), and Receiver Operating Characteristic (ROC) Curve. The proposed deep learning model performs better than other prediction models and achieves a high accuracy rate of 91%. Furthermore, it was noticed that the deep learning model outperforms a small size Neural Network for the customer churn prediction.
In this study the Fourier Transform Infrared Spectrophotometry (FTIR) provides a quick, efficient and relatively inexpensive method for identifying and quantifying gypsum concentrations in the samples taken from different sites from different localities from Alexandria district southwest Baghdad. A comprehensive spectroscopic study of gypsum-calcite system was reported to give good results for the first time by using IR for analytical grades of gypsum (CaSO4.2H2O) and calcite (CaCO3) pure crystals. The spectral results were used to create a calibration curve relates the two minerals concentrations to the intensity (peaks) of FTIR absorbance and applies this calibration to specify gypsum and calcite concentrations in Iraqi gypsiferous soi
... Show MoreThe increased food requirement puts intense pressure on the agriculture community to grow more from the same resources resulting in people leaving the farming business. This happened not exclusively due to the industrial pressure to produce more but to the lack of technology adoption among growers. The use of the sensor in agriculture is not new, but its adoption among agriculture producers is a challenge for industry and scientists. This study aimed to determine sensors used in agricultural fields with challenges and prospects. The study found that sensors have successfully been used at the industry level with highly skilled labor; however, their adoption is challenging in rural agriculture systems due to the lack of a support
... Show MoreThis work presents the UC@MOOC project as a pedagogical innovation to face the effects of massification that are making Moroccan universities endure many constraints for the past ten years, as well as other African universities. It aims, among its objectives, to cope with the massification factor and to overcome the language difficulties encountered by students. In this project, our top priority is to reduce academic failure then we will get to the point of responding to the training' needs. Courses are scripted and posted online which did not require many resources, so their production cost is relatively low. Audiovisual digital content also helps us to save time, and go to a hybrid teaching or even flipped classrooms in some cases. The
... Show MoreDifferent ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach
Astronomy image is regarded main source of information to discover outer space, therefore to know the basic contain for galaxy (Milky way), it was classified using Variable Precision Rough Sets technique to determine the different region within galaxy according different color in the image. From classified image we can determined the percentage for each class and then what is the percentage mean. In this technique a good classified image result and faster time required to done the classification process.
The use of remote sensing technologies was gained more attention due to an increasing need to collect data for the environmental changes. Satellite image classification is a relatively recent type of remote sensing uses satellite imagery to indicate many key environment characteristics. This study aims at classifying and extracting vacant lands from high resolution satellite images of Baghdad city by supervised Classification tool in ENVI 5.3 program. The classification accuracy was 15%, which can be regarded as fairly acceptable given the difficulty of differentiating vacant land surfaces from other surfaces such as roof tops of buildings.
The analysis of the hyperlink structure of the web has led to significant improvements in web information retrieval. This survey study evaluates and analyzes relevant research publications on link analysis in web information retrieval utilizing diverse methods. These factors include the research year, the aims of the research article, the algorithms utilized to complete their study, and the findings received after using the algorithms. The findings revealed that Page Rank, Weighted Page Rank, and Weighted Page Content Rank are extensively employed by academics to properly analyze hyperlinks in web information retrieval. Finally, this paper analyzes the previous studies.
The objective of the current research is to find an optimum design of hybrid laminated moderate thick composite plates with static constraint. The stacking sequence and ply angle is required for optimization to achieve minimum deflection for hybrid laminated composite plates consist of glass and carbon long fibers reinforcements that impeded in epoxy matrix with known plates dimension and loading. The analysis of plate is by adopting the first-order shear deformation theory and using Navier's solution with Genetic Algorithm to approach the current objective. A program written with MATLAB to find best stacking sequence and ply angles that give minimum deflection, and the results comparing with ANSYS.
Traditionally, path selection within routing is formulated as a shortest path optimization problem. The objective function for optimization could be any one variety of parameters such as number of hops, delay, cost...etc. The problem of least cost delay constraint routing is studied in this paper since delay constraint is very common requirement of many multimedia applications and cost minimization captures the need to
distribute the network. So an iterative algorithm is proposed in this paper to solve this problem. It is appeared from the results of applying this algorithm that it gave the optimal path (optimal solution) from among multiple feasible paths (feasible solutions).
Predicting weather by numerical models have been used extensively in research works for Middle East, mostly for dust storms, rain showers, and flash floods with a less deal of interest on snow precipitation. In this study, the Global/Regional Integrated Model System (GRIMs) that was developed in South Korea was used to predict a rare snowfall event occurred in three countries in Middle East (Syria, Jordan and Iraq) located between (25-65 oE; 12-42 oN) in year 2008. The main aim of this study was to test GRIMs efficiency, which would be used for the first time in Middle East, to make predictions of weather parameters such as pressure, temperature, and relative humidity especially in the selected ar
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