Preferred Language
Articles
/
ixaF44sBVTCNdQwCV-Nn
Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem
...Show More Authors

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.

Scopus Clarivate Crossref
View Publication
Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Between Maximum Likelihood and Bayesian Methods For Estimating The Gamma Regression With Practical Application
...Show More Authors

In this paper, we will illustrate a gamma regression model assuming that the dependent variable (Y) is a gamma distribution and that it's mean ( ) is related through a linear predictor with link function which is identity link function g(μ) = μ. It also contains the shape parameter which is not constant and depends on the linear predictor and with link function which is the log link and we will estimate the parameters of gamma regression by using two estimation methods which are The Maximum Likelihood and the Bayesian and a comparison between these methods by using the standard comparison of average squares of error (MSE), where the two methods were applied to real da

... Show More
View Publication Preview PDF
Crossref
Publication Date
Mon Jul 01 2024
Journal Name
Alexandria Engineering Journal
Comparison of some Bayesian estimation methods for type-I generalized extreme value distribution with simulation
...Show More Authors

The Weibull distribution is considered one of the Type-I Generalized Extreme Value (GEV) distribution, and it plays a crucial role in modeling extreme events in various fields, such as hydrology, finance, and environmental sciences. Bayesian methods play a strong, decisive role in estimating the parameters of the GEV distribution due to their ability to incorporate prior knowledge and handle small sample sizes effectively. In this research, we compare several shrinkage Bayesian estimation methods based on the squared error and the linear exponential loss functions. They were adopted and compared by the Monte Carlo simulation method. The performance of these methods is assessed based on their accuracy and computational efficiency in estimati

... Show More
View Publication
Scopus (2)
Scopus Clarivate Crossref
Publication Date
Tue Jan 03 2023
Journal Name
College Of Islamic Sciences
Ruling on selling big data (Authentical Fiqh Study): Ruling on selling big data (Authentical Fiqh Study)
...Show More Authors

Abstract:

Research Topic: Ruling on the sale of big data

Its objectives: a statement of what it is, importance, source and governance.

The methodology of the curriculum is inductive, comparative and critical

One of the most important results: it is not permissible to attack it and it is a valuable money, and it is permissible to sell big data as long as it does not contain data to users who are not satisfied with selling it

 Recommendation: Follow-up of studies dealing with the provisions of the issue

Subject Terms

Judgment, Sale, Data, Mega, Sayings, Jurists

 

View Publication Preview PDF
Publication Date
Sat Apr 15 2023
Journal Name
Iraqi Journal Of Science
Poly (N, N-dimethyl aniline) Coating for Stainless Steel, Synthesis, Characterization and Corrosion Protection in Sea Water 3.5% NaCl Solution
...Show More Authors

This research involves the synthesis of conductive polymer includes: poly (N, Ndimethyl
aniline) on metal surface which is stainless steel 316 by using
electrochemical polymerization technique. Parameters of this research are voltage
rang, scan rate, number of cycles. The tests for corrosion protection of the polymer
coated and uncoated stainless steel substrate was investigated in artificial sea water
of 3.5% NaCl solution by tafel and potentiodynamic procedures. Fourier Transform
Infrared Spectroscopy (FTIR), UV-Visible absorption spectroscopy, Scanning
Electron Microscope (SEM) and Atomic Force Microscope (AFM) were used to
diagnose and describe the structure and morphology of the coating. Parameters of
corr

... Show More
View Publication Preview PDF
Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Multi-level model of the factors that affect the escalation of dust in Iraq
...Show More Authors

In this research The study of Multi-level  model (partial pooling model) we consider The partial pooling model which is one Multi-level  models and one of  the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly  among the stations in Iraq. We use Akaik′s Informa

... Show More
View Publication Preview PDF
Crossref
Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Multi-level model of the factors that affect the escalation of dust in Iraq
...Show More Authors

In this research The study of Multi-level  model (partial pooling model) we consider The partial pooling model which is one Multi-level  models and one of  the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly  among the stations in Iraq. We use Akaik′s Informa

... Show More
View Publication Preview PDF
Crossref
Publication Date
Fri Jun 29 2018
Journal Name
Journal Of The College Of Education For Women
THE PROBLEM RELATED TO WORKING IN KINDERGARTEN FROM THE POINT OF VIEW OF TEACHERS
...Show More Authors

           kindergarten teacher is one of the fundamental pillars upon which the kindergarten environment so that exposure to a number of problems that could affect its functioning in addition to any deficiencies in this environment leads to deprive a child of some activities and acquisition of concepts so the researcher studying the problems of working in kindergartens from the perspective of the parameters, so the researcher based measuring instrument for labour problems of (30) search sample was paragraph (50) parameter that was chosen at random and have been extracted Sincerity and strength tool researcher used statistical methods and discriminatory (Pearson correlation coefficient, t

... Show More
View Publication Preview PDF
Publication Date
Wed Apr 01 2015
Journal Name
Mathematical Methods In The Applied Sciences
An inverse problem of finding the time-dependent diffusion coefficient from an integral condition
...Show More Authors

View Publication
Scopus (28)
Crossref (21)
Scopus Clarivate Crossref
Publication Date
Mon Apr 01 2019
Journal Name
2019 International Conference On Automation, Computational And Technology Management (icactm)
Multi-Resolution Hierarchical Structure for Efficient Data Aggregation and Mining of Big Data
...Show More Authors

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

... Show More
View Publication
Scopus (3)
Crossref (2)
Scopus Crossref
Publication Date
Tue Jan 01 2019
Journal Name
Abu Dhabi International Petroleum Exhibition & Conference
Influence of pressure and temperature on CO2-nanofluid interfacial tension: Implication for enhanced oil recovery and carbon geosequestration
...Show More Authors

Nanoparticles (NPs) based techniques have shown great promises in all fields of science and industry. Nanofluid-flooding, as a replacement for water-flooding, has been suggested as an applicable application for enhanced oil recovery (EOR). The subsequent presence of these NPs and its potential aggregations in the porous media; however, can dramatically intensify the complexity of subsequent CO2 storage projects in the depleted hydrocarbon reservoir. Typically, CO2 from major emitters is injected into the low-productivity oil reservoir for storage and incremental oil recovery, as the last EOR stage. In this work, An extensive serious of experiments have been conducted using a high-pressure temperature vessel to apply a wide range of CO2-pres

... Show More