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Intelligent Traffic Management and Load Balance Based on Spike ISDN-IoT
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An intelligent software defined network (ISDN) based on an intelligent controller can manage and control the network in a remarkable way. In this article, a methodology is proposed to estimate the packet flow at the sensing plane in the software defined network-Internet of Things based on a partial recurrent spike neural network (PRSNN) congestion controller, to predict the next step ahead of packet flow and thus, reduce the congestion that may occur. That is, the proposed model (spike ISDN-IoT) is enhanced with a congestion controller. This controller works as a proactive controller in the proposed model. In addition, we propose another intelligent clustering controller based on an artificial neural network, which operates as a reactive controller, to manage the clustering in the sensing area of the spike ISDN-IoT. Hence, an intelligent queuing model is introduced to manage the flow table buffer capacity of the spike ISDN-IoT network, such that the quality of service (QoS) of the whole network is improved. A modified training algorithm is introduced to train the PRSNN to adjust its weight and threshold. The simulation results demonstrate that the QoS is improved by (14.36%) when using the proposed model as compared with a convolutional neural network.

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Publication Date
Fri May 31 2019
Journal Name
Journal Of Engineering
A Comparative Study of Various Intelligent Algorithms based Path Planning for Mobile Robots
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In general, path-planning problem is one of most important task in the field of robotics. This paper describes the path-planning problem of mobile robot based on various metaheuristic algorithms. The suitable collision free path of a robot must satisfies certain optimization criteria such as feasibility, minimum path length, safety and smoothness and so on. In this research, various three approaches namely, PSO, Firefly and proposed hybrid FFCPSO are applied in static, known environment to solve the global path-planning problem in three cases. The first case used single mobile robot, the second case used three independent mobile robots and the third case applied three follow up mobile robot.  Simulation results, whi

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Publication Date
Tue Jan 01 2019
Journal Name
Advances On Computational Intelligence In Energy
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
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Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

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Publication Date
Sun Jun 30 2024
Journal Name
International Journal Of Intelligent Engineering And Systems
Development of Intelligent Control Strategy for an Anesthesia System Based on Radial Basis Function Neural Network Like PID Controller
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Publication Date
Sat Oct 25 2025
Journal Name
Iet Networks
An Effective Technique of Zero‐Day Attack Detection in the Internet of Things Network Based on the Conventional Spike Neural Network Learning Method
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ABSTRACT<p>The fast evolution of cyberattacks in the Internet of Things (IoT) area, presents new security challenges concerning Zero Day (ZD) attacks, due to the growth of both numbers and the diversity of new cyberattacks. Furthermore, Intrusion Detection System (IDSs) relying on a dataset of historical or signature‐based datasets often perform poorly in ZD detection. A new technique for detecting zero‐day (ZD) attacks in IoT‐based Conventional Spiking Neural Networks (CSNN), termed ZD‐CSNN, is proposed. The model comprises three key levels: (1) Data Pre‐processing, in this level a thorough cleaning process is applied to the CIC IoT Dataset 2023, which contains both malicious and t</p> ... Show More
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Publication Date
Sun Jan 01 2012
Journal Name
International Journal Of Reasoning-based Intelligent Systems
SLMS: a smart library management system based on an RFID technology
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Publication Date
Tue Jan 14 2025
Journal Name
South Eastern European Journal Of Public Health
Deep learning-based threat Intelligence system for IoT Network in Compliance With IEEE Standard
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

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Publication Date
Thu Dec 01 2022
Journal Name
Civil Engineering Journal
Effect of Vehicular Stream Characteristics on Traffic Noise
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Human health can be negatively impacted by exposure to loud noise, which can harm the auditory system. Traffic noise is the leading cause of noise pollution. This paper studies the problem of noise pollution on the roads in Baghdad, Iraq. Due to the increase in vehicle numbers and road network modifications in Baghdad, noise levels became a serious topic to be studied. The aim of the paper was thus to study traffic noise levels and the effect of the traffic stream on noise levels and to formulate a prediction model that identified the guidelines used for designing or developing future roads in the city. Then, the noise levels were measured based on five variables: the functional classification of roads, traffic flow, vehicle speed,

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Effect of Surface Pavement Type on Traffic Noise
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This paper investigates the issue of surface-type effects on traffic noise in Baghdad. Since the raw materials for both flexible and rigid paving are available from local sources, the decision on selecting the type of paving which depends on the budget of the project and the road's importance and function. Knowing that for high traffic volumes and a high percentage of heavy vehicles, rigid pavement is more suitable compared to flexible pavement. In Baghdad, some highways consist of flexible pavement and others of combined pavement (flexible segments and rigid segments), so the study of the effect of surface type on traffic noise becomes an important matter. This study selected three highways: one with flexible pavement and two with combined

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Publication Date
Sat Apr 01 2023
Journal Name
Journal Of Engineering
Effect of Surface Pavement Type on Traffic Noise
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This paper investigates the issue of surface-type effects on traffic noise in Baghdad. Since the raw materials for both flexible and rigid paving are available from local sources, the decision on selecting the type of paving which depends on the budget of the project and the road's importance and function. Knowing that for high traffic volumes and a high percentage of heavy vehicles, rigid pavement is more suitable compared to flexible pavement. In Baghdad, some highways consist of flexible pavement and others of combined pavement (flexible segments and rigid segments), so the study of the effect of surface type on traffic noise becomes an important matter. This study selected three highways: one with flexible pavement a

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Publication Date
Sun Apr 19 2015
Journal Name
Wireless Networks
Design and evaluation of distributed and dynamic mobility management approach based on PMIPv6 and MIH protocols
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