PhD in Statistics
Statistics, Mathematics, Computer Science, Artificial Intelligence, Machine Learning, Deep Learning, Neural Networks, Digital Signal Processing, Image Processing, Time Series Analysis
Statistics and Artificial Intelligence
The grey system model GM(1,1) is the model of the prediction of the time series and the basis of the grey theory. This research presents the methods for estimating parameters of the grey model GM(1,1) is the accumulative method (ACC), the exponential method (EXP), modified exponential method (Mod EXP) and the Particle Swarm Optimization method (PSO). These methods were compared based on the Mean square error (MSE) and the Mean Absolute percentage error (MAPE) as a basis comparator and the simulation method was adopted for the best of the four methods, The best method was obtained and then applied to real data. This data represents the consumption rate of two types of oils a heavy fuel (HFO) and diesel fuel (D.O) and the use of tests to conf
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يقدم هذا البحث الانموذج الرمادي GM(1,1) من الرتبة الأولى و بمتغير واحد و هو أساس نظرية النظام الرمادي تناول هذا البحث خصائص الانموذج الرمادي ومجموعة من طرائق تقدير معالم الانموذج الرمادي GM(1,1) وهي طريقة المربعات الصغرى (LS) , طريقة المربعات الصغرى الموزونة (WLS) , طريقة المربعات الصغرى الكلية (TLS) و طريقة الانحدار التدريجي (DS) حيث تمت المقارنة بين هذه الطرق اعتمادا على نوعين من المقاييس متوسط مربع الخطأ MSE))
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The importance of forecasting has emerged in the economic field in order to achieve economic growth, as forecasting is one of the important topics in the analysis of time series, and accurate forecasting of time series is one of the most important challenges in which we seek to make the best decision. The aim of the research is to suggest the use of hybrid models for forecasting the daily crude oil prices as the hybrid model consists of integrating the linear component, which represents Box Jenkins models and the non-linear component, which represents one of the methods of artificial intelligence, which is long short term memory (LSTM) and the gated recurrent unit (GRU) which represents deep learning models. It was found that the proposed h
... Show MoreForecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti
... Show MoreGeneralized multivariate transmuted Bessel distribution belongs to the family of probability distributions with a symmetric heavy tail. It is considered a mixed continuous probability distribution. It is the result of mixing the multivariate Gaussian mixture distribution with the generalized inverse normal distribution. On this basis, the paper will study a multiple compact regression model when the random error follows a generalized multivariate transmuted Bessel distribution. Assuming that the shape parameters are known, the parameters of the multiple compact regression model will be estimated using the maximum likelihood method and Bayesian approach depending on non-informative prior information. In addition, the Bayes factor was used
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