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Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem
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Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bayesian regularized neural networks (BRNNs), Bayesian additive regression trees (BART), extreme gradient boosting (xgBoost), and hybrid neural fuzzy inference system (HNFIS) were used considering the complex relationship of rainfall with sea level pressure. Principle components of SLP domain correlated with daily rainfall were used as predictors. The results revealed that the efficacy of AI models is predicting daily rainfall one day before. The relative performance of the models revealed the higher performance of BRNN with normalized root mean square error (NRMSE) of 0.678 compared with HNFIS (NRMSE = 0.708), BART (NRMSE = 0.784), xgBoost (NRMSE = 0.803), and ELM (NRMSE = 0.915). Visual inspection of predicted rainfall during model validation using density-scatter plot and other novel ways of visual comparison revealed the ability of BRNN to predict daily rainfall one day before reliably.

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Publication Date
Sat Jun 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Predicting of Temperature Distribution in Direct Contact Heat Transfer
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An experimental and theoretical investigation of three phase direct contact heat transfer by evaporation of refrigerant drops in an immiscible liquid has been carried out. Refrigerant Rl2 and R134a were used for the dispersed phase, while water and brine were the immiscible continuous phase. A numerical analysis is presented to predict the temperature distribution throughout the circular test column radially and axially is achieved. Experimental measurements of the temperature distribution have been compared with the numerical results and are discussed .A comparison between the experimental and theoretical results showed acceptable agreement and applicability of the derived equations. Comparison with other related work showed similar beh

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Publication Date
Sun Dec 30 2001
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Predicting the Change in Volume of Mixed Oil Stocks
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Publication Date
Wed Aug 17 2022
Journal Name
Applied Sciences
Predicting Fruit’s Sweetness Using Artificial Intelligence—Case Study: Orange
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The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co

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Publication Date
Tue Dec 25 2018
Journal Name
Journal Of Engineering Science And Technology
RIETVELD TEXTURE REFINEMENT ANALYSIS OF LINDE TYPE A ZEOLITE FROM X-RAY DIFFRACTION DATA
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Publication Date
Sun Jan 01 2023
Journal Name
8th Engineering And 2nd International Conference For College Of Engineering – University Of Baghdad: Coec8-2021 Proceedings
Preliminary quality assurance of printgrammetry technique-3D modeling from Google Earth 3D imagery data
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Publication Date
Sun Oct 06 2013
Journal Name
Journal Of Educational And Psychological Researches
The Effect of a Behavioral-Cognitive Training Program on Problems Solving among college students in the faculty of education for women : Baghdad University
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The purpose of this study was to investigate the effect of a Cognitive- Behavioral Training Program in reducing Problems Solving among a sample of education university  College Students, the study sample consisted of (50) students were randomly assigned to two groups: experimental, and control; (25) students per group, the results of (ANOVA) revealed that there were significant differences at (p < 0.05) between experimental and control group in Problems Solving level, while there were significant differences between both groups in achievement. The researchers recommended further studies on the other variables which after training students on the method of solving problems and techniques to reduce stress.<

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Publication Date
Sun Apr 08 2018
Journal Name
Al-khwarizmi Engineering Journal
Design of Hybrid Neural Fuzzy Controller for Human Robotic Leg System
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 In this paper, the human robotic leg which can be represented mathematically by single input-single output (SISO) nonlinear differential model with one degree of freedom, is analyzed and then a simple hybrid neural fuzzy controller is designed to improve the performance of this human robotic leg model. This controller consists from SISO fuzzy proportional derivative (FPD) controller with nine rules summing with single node neural integral derivative (NID) controller with nonlinear function. The Matlab simulation results for nonlinear robotic leg model with the suggested controller showed that the efficiency of this controller when compared with the results of the leg model that is controlled by PI+2D, PD+NID, and F

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Publication Date
Tue May 16 2023
Journal Name
Journal Of Engineering
Investigation of Backfill Compaction Effect on Buried Concrete Pipes
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The present study deals with the experimental investigation of buried concrete pipes. Concrete pipes are buried in loose and dense conditions of gravelly sand soil and subjected to different surface loadings to study the effects of the backfill compaction on the pipe. The experimental investigation was accomplished using full-scale precast unreinforced concrete pipes with 300 mm internal diameter tested in a laboratory soil box test facility set up for this study. Two loading platforms are used namely, uniform loading platform and patch loading platform. The wheel load was simulated through patch loading platform which have dimensions of 254 mm *508 mm, which is used by AASHTO to model the wheel load of a HS20 truck. The pipe-soil system

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Publication Date
Thu Dec 31 2015
Journal Name
Kerbala Journal Of Pharmaceutical Sciences
Investigation the Factors Affecting on Gatifloxacin Eye Drop Stability
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This research included the study of different factors that may effect on gatifloxacin stability (anew quinolone synthetic antibacterial agent) in its aqueous solution in order to develop and optimize the best delivary of the drug to the eye (as eye drop) with maximum local concentration and minimum systemic absorption and toxicity.Different formulas of gatifloxacin solution for ophthalmic use (0.3%)w/v were prepared in citrate, acetate,citrate/phosphate and phosphate buffers,their tonicity adjusted with suitable quantity of sodium chloride.The effect of different factors that might affectthe stability of gatifloxacin in its prepared ophthalmic solution was studied and determined spectrophotometrically at 287 nm. The results showed t

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Publication Date
Fri Jul 21 2023
Journal Name
Journal Of Engineering
Laboratory Investigation on Roller Compaction Technique in Concrete Construction
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Roller compacted concrete (RCC) is a concrete compacted by roller compaction. The concrete mixture in its unhardened state must support a roller while being compacted. The aim of this research work was to investigate the behavior and properties of roller compacted concrete when constructed in the laboratory using roller compactor manufactured in local market to simulate the field conditions. The roller compaction was conducts in three stages; each stage has different loading and number of passes of the roller. For the first stage, a load of (24) kg and (5) passes in each direction had been employed. For the second stage, a load of (104) kg and (10) passes in each direction were conducted. Finally, at the third stage, a load of (183) kg a

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