The prediction process of time series for some time-related phenomena, in particular, the autoregressive integrated moving average(ARIMA) models is one of the important topics in the theory of time series analysis in the applied statistics. Perhaps its importance lies in the basic stages in analyzing of the structure or modeling and the conditions that must be provided in the stochastic process. This paper deals with two methods of predicting the first was a special case of autoregressive integrated moving average which is ARIMA (0,1,1) if the value of the parameter equal to zero, then it is called Random Walk model, the second was the exponential weighted moving average (EWMA). It was implemented in the data of the monthly traff

Zubair Formation is one of the richest petroleum systems in Southern Iraq. This formation is composed mainly of sandstones interbedded with shale sequences, with minor streaks of limestone and siltstone. Borehole collapse is one of the most critical challenges that continuously appear in drilling and production operations. Problems associated with borehole collapse, such as tight hole while tripping, stuck pipe and logging tools, hole enlargement, poor log quality, and poor primary cement jobs, are the cause of the majority of the nonproductive time (NPT) in the Zubair reservoir developments. Several studies released models predicting the onset of borehole collapse and the amount of enlargement of the wellbore cross-section. However, assump

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

Polymer matrix composites are suitable materials for medical applications, such as denture base resin polymethyl methacrylate (PMMA). This includes light weight and high strength. This paper describes the effect of selected weight fractions (1, 2, 3, 4 & 5) % wt of nano(Alumina AL2O3, Zirconia ZrO2, Hydroxyapatite HA and Halloysite nanoClay) reinforcements on the biopolymer matrix (PMMA). Some tribology tests were used to evaluate the prepared system (impact strength, hardness surface, and wear rate) tests. The samples were fabricated by (Hand Lay-Up) with different particle reinforcement percentages. All tests were accomplished at room temperature, and samples were developed according to the ASTM standard. The weight fraction o

Polymer matrix composites are suitable materials for medical applications, such as denture base resin polymethyl methacrylate (PMMA). This includes light weight and high strength. This paper describes the effect of selected weight fractions (1, 2, 3, 4 & 5) % wt of nano(Alumina AL2O3, Zirconia ZrO2, Hydroxyapatite HA and Halloysite nanoClay) reinforcements on the biopolymer matrix (PMMA). Some tribology tests were used to evaluate the prepared system (impact strength, hardness surface, and wear rate) tests. The samples were fabricated by (Hand Lay-Up) with different particle reinforcement percentages. All tests were accomplished at room temperature, and samples were developed according to the ASTM standard. The weight fraction of (4% for AL