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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
Mon Dec 29 2025
Journal Name
Journal Of Physical Education
The Effect of Daily Timing Variation on some Motor Abilities and Anaerobic Ability among Sabers
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Publication Date
Fri Dec 03 2021
Journal Name
2021 4th International Conference On Advanced Communication Technologies And Networking (commnet)
Methodology for Predicting the Optimum Design of Radio-Electronic Devices
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Publication Date
Tue Feb 19 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Suggested Model to Audit the Health Institutions to Achieve Sustainable Development: Suggested Model to Audit the Health Institutions to Achieve Sustainable Development
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Sustainable development is longer that meet the needs of the present generation without compromising the ability of future generations to meet their own needs as it seeks to harmonize economic, social, Why research aims to check the availability of a proposed program takes into account the evidence and scrutiny of financial commitment and performance audit in accordance with the dimensions of sustainable development (economic, environmental, social and institutional) to measure the extent of the province on the needs of current and future generations, The problem with research that there is no audit program ensures the audit of financial statements, commitment and performance of health services in order to achieve sustainable development

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Publication Date
Wed Apr 01 2009
Journal Name
International Journal Of Applied Environmental Sciences
An expert System for Predicting the Effects of Noise Pollution on Grass Trimming Task Using Fuzzy Modeling
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Grass trimming operation is widely done in Malaysia for the purpose of maintaining highways. Large number of operators engaged in this work encounters high level of noise generated by back pack type grass trimmer used for this purpose. High level of noise exposure gives different kinds of ill effect on human operators. Exact nature of deteriorated work performance is not known. For predicting the work efficiency deterioration, fuzzy tool has been used in present research. It has been established that a fuzzy computing system will help in identification and analysis of fuzzy models fuzzy system offers a convenient way of representing the relationships between the inputs and outputs of a system in the form of IF-THEN rules. The paper presents

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of The Association Of Arab Universities For Basic And Applied Sciences
Semi-analytical method for solving Fokker-Planck’s equations
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Publication Date
Fri Jan 01 2016
Journal Name
Mathematical Problems In Engineering
Enhanced Simulated Annealing for Solving Aggregate Production Planning
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Simulated annealing (SA) has been an effective means that can address difficulties related to optimization problems. is now a common discipline for research with several productive applications such as production planning. Due to the fact that aggregate production planning (APP) is one of the most considerable problems in production planning, in this paper, we present multi-objective linear programming model for APP and optimized by . During the course of optimizing for the APP problem, it uncovered that the capability of was inadequate and its performance was substandard, particularly for a sizable controlled problem with many decision variables and plenty of constraints. Since this algorithm works sequentially then the current state wi

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Publication Date
Fri May 01 2020
Journal Name
Journal Of Physics: Conference Series
New Approach for Solving Two Dimensional Spaces PDE
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Abstract<p>In this paper, new approach based on coupled Laplace transformation with decomposition method is proposed to solve type of partial differential equation. Then it’s used to find the accurate solution for heat equation with initial conditions. Four examples introduced to illustrate the accuracy, efficiency of suggested method. The practical results show the importance of suggested method for solve differential equations with high accuracy and easy implemented.</p>
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Publication Date
Mon Aug 14 2017
Journal Name
International Journal Of Intelligent Computing And Cybernetics
Two efficient methods for solving Schlömilch’s integral equation
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Purpose

In this paper, the exact solutions of the Schlömilch’s integral equation and its linear and non-linear generalized formulas with application are solved by using two efficient iterative methods. The Schlömilch’s integral equations have many applications in atmospheric, terrestrial physics and ionospheric problems. They describe the density profile of electrons from the ionospheric for awry occurrence of the quasi-transverse approximations. The paper aims to discuss these issues.

Design/methodology/approach

First, the authors apply a regularization meth

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
Study the effect of a new nikel (II) Complex and anticancer drug (cp) on Liver enzyme activity (GPT,GOT) and Creatinine level in Kidney of femal mice
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This study involved the effect of anew nickel (II) complexs with formla [NiL2(H2O)2].2.5ETOH where L=Bis[5-(p-nitrophenyL)-4-phenyL-1,2,4-traizole-3-dithocarbamato hydrazide] diaqua. nickel(II). Ethanol(2.5).and anti-cancer drug cyclophosphamide on specific actifity of two Liver enzymes (GOT,GPT) in the (Liver,kidney) tissues and on the creatinine Level in the kidney byUtilizing an invivosystem in femalmice.The result showed that inhibition in the activity of GPT and GOT enzymes in theLiver and in both nickel (II) complex and cyclophosphamide drug (CP) . mice weretreated with three doses (90,180,320) µg/mouse for three days for each group.The Liver show's the highest rate of GPT inhibition was about 97.43% at180µg/mouse regarding the ki

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Classification of Arabic Alphabets Using a Combination of a Convolutional Neural Network and the Morphological Gradient Method
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The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet

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