The objective of the research , is to shed light on the most important treatment of the problem of missing values of time series data and its influence in simple linear regression. This research deals with the effect of the missing values in independent variable only. This was carried out by proposing missing value from time series data which is complete originally and testing the influence of the missing value on simple regression analysis of data of an experiment related with the effect of the quantity of consumed ration on broilers weight for 15 weeks. The results showed that the missing value had not a significant effect as the estimated model after missing value was consistent and significant statistically. The results also

It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological

The Fourth Industrial Revolution represents an advanced stage of technological development, characterized by the integration of digital, physical, and biological technologies, with a strong focus on smart connectivity and advanced data analysis. At the core of this revolution stands Artificial Intelligence (AI), which enables the processing of vast amounts of data, decision-making with speed and accuracy, automation of processes, and enhancement of productivity and quality. This research examines the transformative role of AI in the humanities, particularly in archaeological, historical, and geographical studies, where traditional methods face limitations in handling complex and extensive datasets.The study aims to highlight these l

Ferritin is a key organizer of protected deregulation, particularly below risky hyperferritinemia, by straight immune-suppressive and pro-inflammatory things. , We conclude that there is a significant association between levels of ferritin and the harshness of COVID-19. In this paper we introduce a semi- parametric method for prediction by making a combination between NN and regression models. So, two methodologies are adopted, Neural Network (NN) and regression model in design the model; the data were collected from مستشفى دار التمريض الخاص for period 11/7/2021- 23/7/2021, we have 100 person, With COVID 12 Female & 38 Male out of 50, while 26 Female & 24 Male non COVID out of 50. The input variables of the NN m

Abstract:          

                Interest in the topic of prediction has increased in recent years and appeared modern methods such as Artificial Neural Networks models, if these methods are able to learn and adapt self with any model, and does not require assumptions on the nature of the time series. On the other hand, the methods currently used to predict the classic method such as Box-Jenkins may be difficult to diagnose chain and modeling because they assume strict conditions.

This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the cov

Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University

The research aims to demonstrate the dual use of analysis to predict financial failure according to the Altman model and stress tests to achieve integration in banking risk management. On the bank’s ability to withstand crises, especially in light of its low rating according to the Altman model, and the possibility of its failure in the future, thus proving or denying the research hypothesis, the research reached a set of conclusions, the most important of which (the bank, according to the Altman model, is threatened with failure in the near future, as it is located within the red zone according to the model’s description, and will incur losses if it is exposed to crises in the future according to the analysis of stress tests