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
Mon Oct 01 2018
Journal Name
Journal Of Educational And Psychological Researches
The ability of solving a mathematical problem and its relation to system thinking among fifth preparatory students
...Show More Authors

The research seeks to examine the ability of fifth preparatory students in solving a mathematical problem in relation to system thinking. To this end, the researcher chose (140) fifth preparatory students from four-different secondary schools in Kirkuk city for the academic year (2016-2017). Two tests were adopted to collect study data: a test of (5) items about skills in solving math problem designed by (Al-raihan, 2006); and a test of system thinking skills designed by the researcher himself consisted of (14) items. It was divided into four skills (analyzing the main system to subsystems, eliminating all inner gaps of system, identifying the inner connection of system, and reorganizing the system). The findings indicated a good ability

... Show More
View Publication Preview PDF
Publication Date
Sat May 02 2026
Journal Name
Modern Sport
Information Processing Styles, Problem Solving, and Their Relationship with Metamotivation and Perceived Control among Postgraduate Female Students
...Show More Authors

The demands of professional, scientific, and academic life have made it necessary to identify the various difficulties faced by postgraduate female students, which lead to problems that hinder their achievement of the required goals. This necessitates directing efforts toward finding solutions to confront and solve problems through appropriate cognitive behavior. Therefore, this study aimed to identify information processing styles and problem-solving and their relationship with metamotivation and perceived control among postgraduate female students (PhD/Master's). To achieve this aim, the descriptive approach using the survey method was adopted due to its suitability to the nature of the research problem. The population was defined

... Show More
View Publication
Crossref
Publication Date
Thu Mar 30 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Safety Profile of Single Daily Dose of Aminoglycosides in Comparison with Multiple Daily Dose
...Show More Authors

To overcome  the  problems  which  associated  with  the standard  multiple  daily  doses (MDD)

of aminoglycosides (AGs) like high incidence of toxicity(nephrotoxicity, ototoxicity)(5-25%) and high cost, an alternative approach was developed which was single daily dose (SDD).This new regimen was designed to maximize bacterial killing by optimizing the peak concentration/minimum inhibitory concentration(MIC)ratio and to reduce the potential for toxicity. The study includes 75 patients selected randomly, 50 of them received SDD regimen of age range of 17-79 years and the remaining received MDD regimen of age range of 13-71 years. The study was designed to evaluate the safety of SDD regim

... Show More
View Publication Preview PDF
Crossref
Publication Date
Thu Apr 30 2026
Journal Name
International Journal On Advanced Science Engineering Information Technology
Improving SVR Horse Herd Optimization Algorithm for Forecasting Daily Gold Prices
...Show More Authors

Accurate and correct price prediction of gold is significant to maintain the stability and fair operation of gold markets as well as the efficiency and proper functioning of financial markets related to gold trading. Gold prices have a long history of non-linear and non-stationary behavior that generates highly complex datasets which are very difficult to forecast with high accuracy and reliability. At the same time Support Vector Regression (SVR) has been utilized as a robust information for prediction not only gold prices but also overall metal price movements. First, the predictive capability of SVR is highly sensitive to hyperparameter selection which needs to be thoroughly tuned and optimized for potentially optimal performance. Theref

... Show More
View Publication Preview PDF
Scopus Crossref
Publication Date
Sun Dec 30 2012
Journal Name
Journal Of Kufa For Mathematics And Computer
On Jeffery Prior Distribution in Modified Double Stage Shrinkage-Bayesian Estimator for Exponential Mean
...Show More Authors

View Publication Preview PDF
Publication Date
Mon Jun 10 2024
Journal Name
Iraqi Journal For Computer Science And Mathematics
Solving tri-criteria: total completion time, total late work, and maximum earliness by using exact, and heuristic methods on single machine scheduling problem
...Show More Authors

The presented study investigated the scheduling regarding  jobs on a single machine. Each  job will be processed with no interruptions and becomes available for the processing at time 0. The aim is finding a processing order with regard to jobs, minimizing total completion time , total late work , and maximal tardiness  which is an NP-hard problem. In the theoretical part of the present work, the mathematical formula for the examined problem will be presented, and a sub-problem of the original problem of minimizing the multi-objective functions  is introduced. Also, then the importance regarding the dominance rule (DR) that could be applied to the problem to improve good solutions will be shown. While in the practical part, two

... Show More
View Publication
Scopus (6)
Crossref (3)
Scopus Crossref
Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
...Show More Authors

Scopus (77)
Crossref (55)
Scopus Clarivate Crossref
Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
...Show More Authors

Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte

... Show More
Scopus (81)
Crossref (58)
Scopus Clarivate Crossref
Publication Date
Tue Jun 01 2021
Journal Name
Swarm And Evolutionary Computation
A review of heuristics and metaheuristics for community detection in complex networks: Current usage, emerging development and future directions
...Show More Authors

View Publication
Scopus (81)
Crossref (58)
Scopus Clarivate Crossref
Publication Date
Mon May 11 2020
Journal Name
Baghdad Science Journal
Proposing Robust LAD-Atan Penalty of Regression Model Estimation for High Dimensional Data
...Show More Authors

         The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator

... Show More
View Publication Preview PDF
Crossref (1)
Crossref