<span>Dust is a common cause of health risks and also a cause of climate change, one of the most threatening problems to humans. In the recent decade, climate change in Iraq, typified by increased droughts and deserts, has generated numerous environmental issues. This study forecasts dust in five central Iraqi districts using machine learning and five regression algorithm supervised learning system framework. It was assessed using an Iraqi meteorological organization and seismology (IMOS) dataset. Simulation results show that the gradient boosting regressor (GBR) has a mean square error of 8.345 and a total accuracy ratio of 91.65%. Moreover, the results show that the decision tree (DT), where the mean square error is 8.965, comes in second place with a gross ratio of 91%. Furthermore, Bayesian ridge (BR), linear regressor (LR), and stochastic gradient descent (SGD), with mean square error and with accuracy ratios of 84.365%, 84.363%, and 79%. As a result, the performance precision of these regression models yields. The interaction framework was designed to be a straightforward tool for working with this paradigm. This model is a valuable tool for establishing strategies to counter the swiftness of climate change in the area under study.</span>
Abstract
The following research is marked by "social intelligence and its role in demonstration the potential abilities for individuals." The discussion dealt with the concepts of contemporary is very important because of their significant role in influencing the work of the Organization, as adopted link between the concepts of social intelligence and the potential role of the first to show the second .The research hypotheses tested in three health institutions in the city of Mosul, the research community is represented (Al-Salam Hospital and General Hospital and the son of ether), while the sample were the leaders of these institutio
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In light of the great technological development and the emergence of globalization has increased global competition, where it became competitive exercise pressure on all sectors. In light of this companies mast enviorment depend on the means that keeps them on the competitive position through access to information about competitors in order to help them to draw a strategy that will achieve a competitive edge either through excellence or reduce the costs of their products and this means intelligence competitive and reverse engineering that help to gain information on competitors analyze and put of the decision-maker From this point formed the idea of research in the statement of the role of
... Show MoreThis study aims to reveal the role of one of the artificial intelligence (AI) techniques, “ChatGPT,” in improving the educational process by following it as a teaching method for the subject of automatic analysis for students of the Chemistry Department and the subject of computer security for students of the Computer Science Department, from the fourth stage at the College of Education for Pure Science (Ibn Al-Haitham), and its impact on their computational thinking to have a good educational environment. The experimental approach was used, and the research samples were chosen intentionally by the research community. Research tools were prepared, which included a scale for CT that included 12 items and the achievement test in b
... Show MoreThe main objective of this paper is to designed algorithms and implemented in the construction of the main program designated for the determination the tenser product of representation for the special linear group.
Intrusion detection system is an imperative role in increasing security and decreasing the harm of the computer security system and information system when using of network. It observes different events in a network or system to decide occurring an intrusion or not and it is used to make strategic decision, security purposes and analyzing directions. This paper describes host based intrusion detection system architecture for DDoS attack, which intelligently detects the intrusion periodically and dynamically by evaluating the intruder group respective to the present node with its neighbors. We analyze a dependable dataset named CICIDS 2017 that contains benign and DDoS attack network flows, which meets certifiable criteria and is ope
... Show MoreIn this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in
Semiparametric methods combined parametric methods and nonparametric methods ,it is important in most of studies which take in it's nature more progress in the procedure of accurate statistical analysis which aim getting estimators efficient, the partial linear regression model is considered the most popular type of semiparametric models, which consisted of parametric component and nonparametric component in order to estimate the parametric component that have certain properties depend on the assumptions concerning the parametric component, where the absence of assumptions, parametric component will have several problems for example multicollinearity means (explanatory variables are interrelated to each other) , To treat this problem we use
... Show MoreThe use of non-parametric models and subsequent estimation methods requires that many of the initial conditions that must be met to represent those models of society under study are appropriate, prompting researchers to look for more flexible models, which are represented by non-parametric models
In this study, the most important and most widespread estimations of the estimation of the nonlinear regression function were investigated using Nadaraya-Watson and Regression Local Ploynomial, which are one of the types of non-linear
... Show MoreIn this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .
Background: The integration of modern computer-aided design and manufacturing technologies in diagnosis, treatment planning, and appliance construction is changing the way in which orthodontic treatment is provided to patients. The aim of this study is to assess the validity of digital and rapid prototyped orthodontic study models as compared to their original stone models. Materials and methods: The sample of the study consisted of 30 study models with well-aligned, Angle Class I malocclusion. The models were digitized with desktop scanner to create digital models. Digital files were then converted to plastic physical casts using prototyping machine, which utilizes the fused deposition modeling technology. Polylactic acid polymer was chose
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