Preferred Language
Articles
/
xxfvQo8BVTCNdQwCeGfO
ON THE GREEDY RADIAL BASIS FUNCTION NEURAL NETWORKS FOR APPROXIMATION MULTIDIMENSIONAL FUNCTIONS
...Show More Authors

The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Sun Jan 27 2019
Journal Name
Civil Engineering Journal
Prediction of Sediment Accumulation Model for Trunk Sewer Using Multiple Linear Regression and Neural Network Techniques
...Show More Authors

Sewer sediment deposition is an important aspect as it relates to several operational and environmental problems. It concerns municipalities as it affects the sewer system and contributes to sewer failure which has a catastrophic effect if happened in trunks or interceptors. Sewer rehabilitation is a costly process and complex in terms of choosing the method of rehabilitation and individual sewers to be rehabilitated.  For such a complex process, inspection techniques assist in the decision-making process; though, it may add to the total expenditure of the project as it requires special tools and trained personnel. For developing countries, Inspection could prohibit the rehabilitation proceeds. In this study, the researchers propos

... Show More
View Publication
Scopus (18)
Crossref (14)
Scopus Clarivate Crossref
Publication Date
Sun Mar 02 2008
Journal Name
Baghdad Science Journal
Orthogonal Functions Solving Linear functional Differential EquationsUsing Chebyshev Polynomial
...Show More Authors

A method for Approximated evaluation of linear functional differential equations is described. where a function approximation as a linear combination of a set of orthogonal basis functions which are chebyshev functions .The coefficients of the approximation are determined by (least square and Galerkin’s) methods. The property of chebyshev polynomials leads to good results , which are demonstrated with examples.

View Publication Preview PDF
Crossref (4)
Crossref
Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Engineering
Mathematical Modeling of Compaction Curve Using Normal Distribution Functions
...Show More Authors

Compaction curves are widely used in civil engineering especially for road constructions, embankments, etc. Obtaining the precise amount of Optimum Moisture Content (OMC) that gives the Maximum Dry Unit weight gdmax. is very important, where the desired soil strength can be achieved in addition to economic aspects.

In this paper, three peak functions were used to obtain the OMC and gdmax. through curve fitting for the values obtained from Standard Proctor Test. Another surface fitting was also used to model the Ohio’s compaction curves that represent the very large variation of compacted soil types.

The results showed very good correlation between the values obtained from some publ

... Show More
View Publication Preview PDF
Publication Date
Sun Mar 01 2020
Journal Name
Computer Networks
An improved multi-objective evolutionary algorithm for detecting communities in complex networks with graphlet measure
...Show More Authors

View Publication
Scopus (8)
Crossref (5)
Scopus Clarivate Crossref
Publication Date
Mon Jan 28 2019
Journal Name
Soft Computing
Bio-inspired multi-objective algorithms for connected set K-covers problem in wireless sensor networks
...Show More Authors

Scopus (13)
Crossref (12)
Scopus Clarivate Crossref
Publication Date
Fri Dec 01 2017
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Performance Evaluation of UDP, DCCP, SCTP and TFRC for Different Traffic Flow in Wired Networks
...Show More Authors

<p>The demand for internet applications has increased rapidly.  Providing quality of service (QoS) requirements for varied internet application is a challenging task. One important factor that is significantly affected on the QoS service is the transport layer. The transport layer provides end-to-end data transmission across a network. Currently, the most common transport protocols used by internet application are TCP (Transmission Control Protocol) and UDP (User Datagram Protocol). Also, there are recent transport protocols such as DCCP (data congestion control protocol), SCTP (stream congestion transmission protocol), and TFRC (TCP-friendly rate control), which are in the standardization process of Internet Engineering Task

... Show More
View Publication Preview PDF
Crossref (2)
Crossref
Publication Date
Sun Aug 24 2014
Journal Name
Wireless Personal Communications
Multi-layer Genetic Algorithm for Maximum Disjoint Reliable Set Covers Problem in Wireless Sensor Networks
...Show More Authors

View Publication
Scopus (22)
Crossref (14)
Scopus Clarivate Crossref
Publication Date
Sat Apr 01 2023
Journal Name
Digital Communications And Networks
Dynamic channel estimation-aware routing protocol in mobile cognitive radio networks for smart IIoT applications
...Show More Authors

View Publication
Scopus (15)
Crossref (11)
Scopus Clarivate Crossref
Publication Date
Sat Dec 01 2018
Journal Name
Applied Soft Computing
A new evolutionary algorithm with locally assisted heuristic for complex detection in protein interaction networks
...Show More Authors

View Publication
Scopus (15)
Crossref (9)
Scopus Clarivate Crossref
Publication Date
Thu Jan 30 2020
Journal Name
Telecommunication Systems
Nature-inspired optimization algorithms for community detection in complex networks: a review and future trends
...Show More Authors

View Publication
Scopus (30)
Crossref (26)
Scopus Clarivate Crossref