The aim of this paper is to design artificial neural network as an alternative accurate tool to estimate concentration of Cadmium in contaminated soils for any depth and time. First, fifty soil samples were harvested from a phytoremediated contaminated site located in Qanat Aljaeesh in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. The inputs are the soil depth, the time, and the soil parameters but the output is the concentration of Cu in the soil for depth x and time t. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Cadmium. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this work show that the ANN technique trained on experimental measurements can be successfully applied to the rapid estimation of Cadmium concentration
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 relativel
... Show MoreThe Purpose of this study is mainly to improve the competitive position of products economic units using technique target cost and method reverse engineering and through the application of technique and style on one of the public sector companies (general company for vegetable oils) which are important in the detection of prices accepted in the market for items similar products and processing the problem of high cost which attract managerial and technical leadership to the weakness that need to be improved through the introduction of new innovative solutions which make appropriate change to satisfy the needs of consumers in a cheaper way to affect the decisions of private customer to buy , especially of purchase private economic units to
... Show MoreIn recent years, the steady stream of artificial intelligence into economic systems has become a torrent. It is changing how we generate wealth and grow anew. Manufacturing, finance, health care energy, agriculture and education are just a few of the areas where AI may result in dramatic increases in productivity as well as innovation and sustainability. Predictive analytics, AI, robotics and natural language processing have significantly contributed in the improvement of resource allocation mechanisms and decision making as well as reaching SDGs. The concept of Artificial Humanity is also introduced in the paper. It shows how AI could become a global cognitive network to foster knowledge. By comparison and references of the literature, thi
... Show MoreThe process of risk assessment in the build-operate transfer (BOT) project is very important to identify and analyze the risks in order to make the appropriate decision to respond to them. In this paper, AHP Technique was used to make the appropriate decision regarding response to the most prominent risks that were generated in BOT projects, which includes a comparison between the criteria for each risk as well as the available alternatives and by mathematical methods using matrices to reach an appropriate decision to respond to each risk.Ten common risks in BOT contracts are adopted for analysis in this paper, which is grouped into six main risk headings.The procedures followed in this paper are the questionnaire method
... Show MoreThe aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).
Eichhornia, or water hyacinth represents a serious threat to potable water basins. This problem is materialized majorly in consuming large amounts of water and dissolved Oxygen that is necessary for aquatic life, and minorly in hindering water streams. Even there are limited trials to overcome such pests, none of them presents an acceptable solution economically and logically. Chlorine is a well-known biocide and broadly used in water industry. It could give a possible method to fight such weed. To investigate that, concentration-time plot should be introduced similar to any other microorganisms; especially, bacteria in water. In this work, various doses of Chlorine along various time
This study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators
Permeability determination in Carbonate reservoir is a complex problem, due to their capability to be tight and heterogeneous, also core samples are usually only available for few wells therefore predicting permeability with low cost and reliable accuracy is an important issue, for this reason permeability predictive models become very desirable.
This paper will try to develop the permeability predictive model for one of Iraqi carbonate reservoir from core and well log data using the principle of Hydraulic Flow Units (HFUs). HFU is a function of Flow Zone Indicator (FZI) which is a good parameter to determine (HFUs).
Histogram analysis, probability analysis and Log-Log plot of Reservoir Qua
... Show More“Smart city” projects have become fully developed and are actively using video analytics. Our study looks at how video analytics from surveillance cameras can help manage urban areas, making the environment safer and residents happier. Every year hundreds of people fall on subway and railway lines. The causes of these accidents include crowding, fights, sudden health problems such as dizziness or heart attacks, as well as those who intentionally jump in front of trains. These accidents may not cause deaths, but they cause delays for tens of thousands of passengers. Sometimes passers-by have time to react to the event and try to prevent it, or contact station personnel, but computers can react faster in such situations by using ethical
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