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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
Thu Aug 17 2023
Journal Name
Revista De Gestão Social E Ambiental
Complete Street as a Key for Urban Environment Development
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Purpose: The concept of complete street is one of the modern trends concerned with diversifying means of transportation and reducing the disadvantages of mechanical transportation modes. This paper discusses the role of complete streets can play in developing the urban environment in the Alyarmok District of Baghdad.   Method/design/approach: The linear regression method used to analyze the opinions of 100 respondents surveyed in the study area in order to find the relationship between the urban environment and the complete street elements.   Theoretical framework: The Modern trends in urban planning aim to find alternatives to the policies of traditional transportation planning that focus on vehicular mobi

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Publication Date
Tue Nov 05 2019
Journal Name
Cardiff University
Technology development for nanoscale InSb quantum split-gate structures
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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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Publication Date
Tue Oct 15 2019
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Combining Convolutional Neural Networks and Slantlet Transform For An Effective Image Retrieval Scheme
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In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The reality of smart city development management in the comprehensive development plan for the city of Baghdad 2030
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Abstract

Abstract has many advantages as has historically been one of the regions leading cultural centers . for centuries , it has been a center of commertial and financial operations in Iraq. it is also rich in archeological sites and natural resources, but because of its wars and implementation of urban development strategies are effective and sustainable , so contracted the secretariat of Baghdad with the company (khatib and scirntiffic) for the preparation of the comprehensive development plan for the city of Baghdad in 2030 and funded by the world bank and the fact that the plan was approved ( three stages of it ) and only one phase remains the fourth stage, which is under discussion the aim of the

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison between the Methods of Ridge Regression and Liu Type to Estimate the Parameters of the Negative Binomial Regression Model Under Multicollinearity Problem by Using Simulation
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The problem of Multicollinearity is one of the most common problems, which deal to a large extent with the internal correlation between explanatory variables. This problem is especially Appear in economics and applied research, The problem of Multicollinearity has a negative effect on the regression model, such as oversized variance degree and estimation of parameters that are unstable when we use the Least Square Method ( OLS), Therefore, other methods were used to estimate the parameters of the negative binomial model, including the estimated Ridge Regression Method and the Liu type estimator, The negative binomial regression model is a nonline

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Publication Date
Wed Mar 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Using Quadratic Form Ratio Multiple Test to Estimate Linear Regression Model Parameters in Big Data with Application: Child Labor in Iraq
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              The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter

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Publication Date
Tue May 16 2023
Journal Name
Political Sciences Journal
Educational Policies in Singapore and their Reflections on Development
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Singapore has invested its human resources for the development of the country since earlier times, so it has directed attention to the education sector. Education and development complement each other, as investment in education has contributed over several years to the development of Singapore economy and has made it one of the strongest economies in Asia and the world. Despite the obstacles that faced educational policies in Singapore, the presence of a wise leadership capable of overcoming difficulties and solving them, and providing the appropriate atmosphere for the development of education has contributed significantly to making it one of the most advanced educational systems in the world, and making this system the main pillar for

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Publication Date
Tue Jun 11 2019
Journal Name
Al-kindy College Medical Journal
Effect of HLA-B27 on Development of Psoriatic Arthropathy
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Background: Psoriatic arthritis is a type of arthritis that can often affect some patients who suffer from psoriasis. Approximately 40-50% of individuals with psoriatic arthritis have the HLA-B27 genotype

Objective: To investigate whether we could confirm the role of HLA-B27 alleles and psoriatic arthritis in Iraqi Arab Muslims patients.

Method: A cross sectional case control comparative study included thirty Iraqi Arab Muslims who had psoriatic arthritis that consulted the Dermatological and Rheumatological Department in AL-Kindy Teaching Hospital from November 2014 to June 2015. HLA-genotyping for HLA-B27 were assessed. A control group consisted of fifty-one healthy vol

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Publication Date
Mon Jan 11 2021
Journal Name
Journal Of Planner And Development
The impact of recycling abandoned sites on sustainable development
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In today's cities, it is easy to see large numbers of vacant lands and unused abandoned sites in downtown areas that are not only ugly but also potentially becoming fertile ground for criminal activities that endanger residents and visitors and contribute to the further degradation of neighborhoods,

can provide reuse of spaces Neglected opportunities to reshape the appearance of the city and to improve the city center for its users that the presence of many neglected sites, whether they were abandoned buildings or sites for destroyed buildings in Mosul after the war on ISIS and with large areas amid the urban fabric led to the emergence of the research problem is (lack of urban planning to reactivate abandoned sites within the ci

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