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
Wed Aug 28 2019
Journal Name
Journal Of Engineering
Predicting Wetting Patterns in Soil from a Single Subsurface Drip Irrigation System
...Show More Authors

Soil wetted pattern from a subsurface drip plays great importance in the design of subsurface drip irrigation (SDI) system for delivering the required water directly to the roots of the plant. An equation to estimate the dimensions of the wetted area in soil are taking into account water uptake by roots is simulated numerically using HYDRUS (2D/3D) software. In this paper, three soil textures namely loamy sand, sandy loam, and loam soil were used with three different types of crops tomato, pepper, and cucumber, respectively, and different values of drip discharge, drip depth, and initial soil moisture content were proposed. The soil wetting patterns were obtained at every thirty minutes for a total time of irrigation equ

... Show More
View Publication Preview PDF
Crossref (10)
Crossref
Publication Date
Sun Sep 01 2019
Journal Name
Al Adab
Cognitive Stylistic Analysis of Daily Yahoo Storie
...Show More Authors

Cognitive stylistics is one discipline of applied linguistics that relies on the reader’s interpretation and inference of the meaning of the text depending on his background knowledge. It studies how the reader understands the text and mapping it with his real experiences (Jeffries and McIntyre,2010). The present study is a cognitive stylistic analysis of digital stories. Digital stories are short narratives made by a combination of different sorts of digital media such as pictures, audios and videos. These digital media are employed to tell stories about oneself, famous people, and important events. The analyzed stories are selected from “Daily Yahoo Stories” and are analyzed according to Lakoff (1993) approach, The analysis investig

... Show More
Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
CONSTRUCTION DELAY ANALYSIS USING DAILY WINDOWS TECHNIQUE
...Show More Authors

Delays occur commonly in construction projects. Assessing the impact of delay is sometimes a contentious
issue. Several delay analysis methods are available but no one method can be universally used over another in
all situations. The selection of the proper analysis method depends upon a variety of factors including
information available, time of analysis, capabilities of the methodology, and time, funds and effort allocated to the analysis. This paper presents computerized schedule analysis programmed that use daily windows analysis method as it recognized one of the most credible methods, and it is one of the few techniques much more likely to be accepted by courts than any other method. A simple case study has been implement

... Show More
View Publication Preview PDF
Crossref (2)
Crossref
Publication Date
Sun Mar 01 2020
Journal Name
Sustainable Chemistry And Pharmacy
A sustainable approach to utilize olive pips for the sorption of lead ions: Numerical modeling with aid of artificial neural network
...Show More Authors

Scopus (23)
Crossref (17)
Scopus Clarivate Crossref
Publication Date
Tue Sep 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of estimation methods for regression model parametersIn the case of the problem of linear multiplicity and abnormal values
...Show More Authors

 A simulation study is used to examine the robustness of some estimators on a multiple linear regression model with problems of multicollinearity and non-normal errors, the Ordinary least Squares (LS) ,Ridge Regression, Ridge Least Absolute Value (RLAV), Weighted Ridge (WRID), MM and a robust ridge regression estimator MM estimator, which denoted as RMM this is the modification of the Ridge regression by incorporating robust MM estimator . finialy, we show that RMM is the best among the other estimators

View Publication Preview PDF
Crossref
Publication Date
Wed Jun 01 2016
Journal Name
Nternational Journal Of Mathematics Trends And Technology (ijmtt)
Fuzzy Scheduling Problem on Two Machines
...Show More Authors

Publication Date
Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
...Show More Authors

Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

... Show More
Publication Date
Tue May 01 2018
Journal Name
Journal Of Engineering
Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq
...Show More Authors

The importance of Baghdad city as the capital of Iraq and the center of the attention of delegations because of its long history is essential to preserve its environment. This is achieved through the integrated management of municipal solid waste since this is only possible by knowing the quantities produced by the population on a daily basis. This study focused to predicate the amount of municipal solid waste generated in Karkh and Rusafa separately, in addition to the quantity produced in Baghdad, using IBM SPSS 23 software. Results that showed the average generation rates of domestic solid waste in Rusafa side was higher than that of Al-Karkh side because Rusafa side has higher population density than Al-Karkh side. T

... Show More
View Publication Preview PDF
Crossref (3)
Crossref
Publication Date
Mon Jan 01 2024
Journal Name
Itm Web Of Conferences
Embedded Neural Network like PID Water Heating Controller Implementing Cycle by Cycle Power Control Scheme
...Show More Authors

This paper experimentally investigates the heating process of a hot water supply using a neural network implementation of a self-tuning PID controller on a microcontroller system. The Particle Swarm Optimization (PSO) algorithm employed in system tuning proved very effective, as it is simple and fast optimization algorithm. The PSO method for the PID parameters is executed on the Matlab platform in order to put these parameters in the real-time digital PID controller, which was experimented with in a pilot study on a microcontroller platform. Instead of the traditional phase angle power control (PAPC) method, the Cycle by Cycle Power Control (CBCPC) method is implemented because it yields better power factor and eliminates harmonics

... Show More
View Publication
Crossref
Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Early Diagnose Alzheimer's Disease by Convolution Neural Network-based Histogram Features Extracting and Canny Edge
...Show More Authors

Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

... Show More
View Publication Preview PDF
Scopus (9)
Crossref (4)
Scopus Crossref