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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 Oct 01 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

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Publication Date
Mon Oct 17 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

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Publication Date
Tue Jun 22 2021
Journal Name
Expert Systems
Hybrid intelligent technology for plant health using the fusion of evolutionary optimization and deep neural networks
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Publication Date
Mon Jun 01 2026
Journal Name
Indonesian Journal Of Chemistry
Synthesis, Multi-Identifications of Some Complexes with a Newly Ligand (4-FADPD) Derived from Caffeine and Evaluation of the Anticancer Activity of Au(III) Nano-Complex
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A novel ligand ((1E)-(2-(4-fluorobenzylidene)amino)methyl) phenyl)diazenyl)-1,3,7-trimethyl-3,7-dihydro-1H-purine-2,6-dione (4-FADPD) was synthesized via the azotization reaction of 2-aminobenzylamine with caffeine, and the resultant compound was condensed with 4-fluorobenzaldehyde to form a newly azo-Schiff base ligand. Its complexes with Cu(II), Ag(I), and Au(III) were synthesized. The results of multi-identifications, including XRD, elemental analysis (C.H.N), UV-vis spectroscopy, FTIR, and 1H-NMR, were used to propose the suggested structures using molar conductivity measurements. These data were utilized to propose appropriate geometric configurations for all complexes. The azo-Schiff base ligand coordinates toward the Cu(II) i

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Publication Date
Mon Aug 31 2020
Journal Name
Journal Of Research In Medical And Dental Science
The Effect of Super Oxidized Water Mouthwash on the Level of IL 1? in Gingival Crevicular Fluid for Patients with Gingivitis Randomized Clinical Trial
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Background: One of the most predominant periodontal diseases is the plaque induced gingivitis. For the past 20 years, super-oxidized solutions have be..

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Publication Date
Sat May 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Effect of adding different level of Bay laurel (Laurus nobilis L.) powder to diet on productive performance and some physiological traits for female Quail
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Abstract<p>This study was conducted at the Poultry Research Station, Animal Resources Research Department at the Agricultural Research Department / Ministry of Agriculture - Baghdad Abu Ghraib. To find the effect of adding different proportions of Bay Laurus powder on productive performance and some physiological characteristics of birds during the production stage as Eight Hundreds Female birds of quail were used at the age of 45 days, randomly deployed to 4 treatments with two replicates (100 birds / replicate ) each, and the bay laurel powder was added in the proportions 0.0, 0.5, 1.0, and 1.5% to the diets and for a period of 60 days divided into 4 periods of 15-day .The results indicated si</p> ... Show More
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Publication Date
Thu Jan 04 2024
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Estimating the impact of tax exemptions on achieving economic development in Iraq for the period (2015-2021): An Applied research in the General Authority for Taxes
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Abstract

          The research aims to identify tax exemptions, their objectives and types, as well as to shed light on the concept of sustainable development, its objectives, dimensions and indicators (economic, social and environmental), as well as to analyze the relationship between tax exemptions and economic development, in addition to measuring and analyzing the impact of tax exemptions on economic development in Iraq for the period ( 2015 - 2021) using the NARDL model. The research problem centers on the fact that failure to employ financial policy tools correctly led to a weakness in achieving economic justice, which leads to a failure to improve social welfar

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Publication Date
Sun Jun 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Stages of integration scenarios with strategic management From the perspective of study the historical development of scenarios
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Purpose: The present study seeks to examine various history stages in which undergone by the concept of scenarios, and development of this concept to integration with the strategic management practices:
Methodology: The current study relied on a literature review and approach in providing total picture of different stages undergone by this concept.
The main results: the scenarios did not reach maturity in their quest for integration with strategic management, and still need a great effort for the maturation of this thought in the framework of strategic management, and through it can contribute in creating important knowledge evolution.
Originality and value: providing a contemporary model linking the roots of this concept and cu

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Publication Date
Thu Jul 25 2019
Journal Name
Advances In Intelligent Systems And Computing
Solving Game Theory Problems Using Linear Programming and Genetic Algorithms
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Publication Date
Mon Oct 19 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Enamel defect of primary and permanent teeth in relation to nutrients daily intake among Down's syndrome children in comparison to normal children
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Background: Any child with Down's syndrome does not develop in the same manner as normal child. Therefore, the child should not be viewed as being like everyone else. Developmental enamel defects in primary teeth have been found at least twice as frequently in disabled children as in control children. Down's syndrome consumed protein more than the recommended daily allowance compared to other disabled groups. Therefore, the aim of this study was to investigate developmental defects of enamel and their relations to nutrient intake among Down's syndrome children in comparison to normal children. Materials and Methods: A sample consisted of fifty institutionalized Down's syndrome children (study group) and 50 normal children (control group)

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