Flow-production systems whose pieces are connected in a row may not have maintenance scheduling procedures fixed because problems occur at different times (electricity plants, cement plants, water desalination plants). Contemporary software and artificial intelligence (AI) technologies are used to fulfill the research objectives by developing a predictive maintenance program. The data of the fifth thermal unit of the power station for the electricity of Al Dora/Baghdad are used in this study. Three stages of research were conducted. First, missing data without temporal sequences were processed. The data were filled using time series hour after hour and the times were filled as system working hours, making the volume of the data relatively high for 2015-2016-2017. 2018 was utilized as a test year to assess the modeling work and validate the experimental results. In the second step, the artificial neural networks approach employs the python program as an AI, and the affinity ratio of real data using the performance measurement of the mean absolute error (MAE) was 0.005. To improve and reduce the value of absolute error, the genetic algorithm uses the python program and the convergence ratio became 0.001. It inferred that the algorithm is efficient in improving results. Thus, the genetic algorithm provided better results with fewer errors than the neural network alone. This concludes that the shown network has superior performance over others and the possibility of its long-term predictions for 2030. A Sing time series helped detect future cases by reading and inferring system data. The development of appropriate work plans will lower internal and external expenses of the systems and help integrate other capabilities by giving correct data sources of raw materials, costs, etc. To facilitate prediction for maintenance workers, an interface has been created that facilitates users to apply them using the python program represented by entering the times, an hour, a day, a month, a year, to predict the type and place of failure.
Psychological damage is one of the damages that can be compensated under the fault of negligence in the framework of English law, where the latter intends to include an enumeration of civil errors on the basis of which liability can be determined, and aims under each of these errors to protect a specific interest (for example, defamation protects Among the damage to reputation and inconvenience are the rights contained on the land), and the same is true for the rest of the other errors. Compensation for psychological damage resulting from negligence has raised problems in cases where the psychological injury is "pure", that is, those that are not accompanied by a physical injury, which required subjecting them to special requirements by the
... Show MoreWater saturation is the most significant characteristic for reservoir characterization in order to assess oil reserves; this paper reviewed the concepts and applications of both classic and new approaches to determine water saturation. so, this work guides the reader to realize and distinguish between various strategies to obtain an appropriate water saturation value from electrical logging in both resistivity and dielectric has been studied, and the most well-known models in clean and shaly formation have been demonstrated. The Nuclear Magnetic Resonance in conventional and nonconventional reservoirs has been reviewed and understood as the major feature of this approach to estimate Water Saturation based on T2 distribution. Artific
... Show MoreLow oil extraction and early high water production are caused in part by reservoir heterogeneity. Huge quantities of water production are prevalent issues that happen in older reservoirs. Polyacrylamide polymer gel systems have been frequently employed as plugging agents in heterogeneous reservoirs to regulate water output and increase sweep efficiency. Polyacrylamide polymer gel systems are classified into three classes depending on their composition and application conditions, which are in-situ monomer gel, in-situ polymer gel, and preformed particle gel (PPG).
This paper gives a comprehensive review of PPG’s status, preparation, and mechanisms. Many sorts of PPGs are categorized, for example, millimeter-sized preformed p
... Show MoreIn this paper we proposed a new method for selecting a smoothing parameter in kernel estimator to estimate a nonparametric regression function in the presence of missing values. The proposed method is based on work on the golden ratio and Surah AL-E-Imran in the Qur'an. Simulation experiments were conducted to study a small sample behavior. The results proved the superiority the proposed on the competition method for selecting smoothing parameter.
The research aims to present a proposed strategy for the North Oil Company, and the proposed strategy took into account the surrounding environmental conditions and adopted in its formulation on the basis and scientific steps that are comprehensive and realistic, as it covered the main activities of the company (production and exploration activities, refining and refining activities, export and transport of oil, research and development activity, financial activity, information technology, human resources) and the (David) model has been adopted in the environmental analysis of the factors that have been diagnosed according to a
... Show MoreLong memory analysis is one of the most active areas in econometrics and time series where various methods have been introduced to identify and estimate the long memory parameter in partially integrated time series. One of the most common models used to represent time series that have a long memory is the ARFIMA (Auto Regressive Fractional Integration Moving Average Model) which diffs are a fractional number called the fractional parameter. To analyze and determine the ARFIMA model, the fractal parameter must be estimated. There are many methods for fractional parameter estimation. In this research, the estimation methods were divided into indirect methods, where the Hurst parameter is estimated fir
... Show MoreThis paper proposes a hybrid speech enhancement estimator that integrates the Perceptually-motivated Karhunen–Loève Transform (PKLT) with the Dual-Masking Harmonic-based (DMH) algorithm in a unified framework termed PKDMH. The main novelty lies in combining perceptual subspace projection with harmonic-residual suppression, enabling the system to jointly remove noise while preserving speech-relevant spectral cues. PKLT first performs perceptual subspace projection and suppresses inaudible components, after which DMH eliminates remaining broadband and harmonic residuals. The proposed PKDMH system was evaluated using the TIMIT dataset contaminated with five noise types: White, Pink, F16, Airport, and Car noise—across five SNR leve
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