Intelligent Computing Paradigm: Recent Trends

2020 ◽  
Keyword(s):  
Intelligent Computing ◽  
Computing Paradigm ◽  
Recent Trends

Intelligent computing for the dynamics of entropy optimized nanofluidic system under impacts of MHD along thick surface

2021 ◽  
pp. 2150269
Author(s):  
M. Asif Zahoor Raja ◽  
M. Shoaib ◽  
Rafia Tabassum ◽  
M. Ijaz Khan ◽  
R. J. Punith Gowda ◽  
...  
Keyword(s):  
Mean Squared Error ◽  
Fluid Motion ◽  
Lewis Number ◽  
Index Formula ◽  
Brownian Diffusion ◽  
Intelligent Computing ◽  
Similarity Transformations ◽  
Computing Paradigm ◽  
Numerical Solver ◽  
Nanofluidic System

This article examines entropy production (EP) of magneto-hydrodynamics viscous fluid flow model (MHD-VFFM) subject to a variable thickness surface with heat sink/source effect by utilizing the intelligent computing paradigm via artificial Levenberg–Marquardt back propagated neural networks (ALM-BPNNs). The governing partial differential equations (PDEs) of MHD-VFFM are transformed into ODEs by applying suitable similarity transformations. The reference dataset is obtained from Adam numerical solver by the variation of Hartmann number (Ha), thickness parameter [Formula: see text], power index ([Formula: see text], thermophoresis parameter (Nt), Brinkman number (Br), Lewis number (Le) and Brownian diffusion parameter (Nb) for all scenarios of proposed ALM-BPNN. The reference data samples arbitrary selected for training/testing/validation are used to find and analyze the approximated solutions of proposed ALM-BPNNs as well as comparison with reference results. The excellent performance of ALM-BPNN is consistently endorsed by Mean Squared Error (MSE) convergence curves, regression index and error histogram analysis. Intelligent computing based investigation suggests that the rise in values of Ha declines the velocity of the fluid motion but converse trend is seen for growing values of [Formula: see text]. The rising values of Ha, Nt and Br improve the heat transfer but converse trend is seen for growing values of [Formula: see text]. The inclining values of Nt incline the mass transfer but it shows reverse behavior for escalating values of Le. The inclining values of Br incline the EP.

Neural Networks

2012 ◽  
pp. 450-498 ◽  
Author(s):  
Siddhartha Bhattacharyya
Keyword(s):  
Neural Networks ◽  
Data Networks ◽  
Input Output ◽  
Training Set ◽  
Topology Preservation ◽  
Functional Characteristics ◽  
Output Data ◽  
Computing Paradigm ◽  
Mode Of Operation ◽  
Recent Trends

These networks generally operate in two different modes, viz., supervised and unsupervised modes. The supervised mode of operation requires a supervisor to train the network with a training set of data. Networks operating in unsupervised mode apply topology preservation techniques so as to learn inputs. Representative examples of networks following either of these two modes are presented with reference to their topologies, configurations, types of input-output data and functional characteristics. Recent trends in this computing paradigm are also reported with due regards to the application perspectives.

Integrated intelligent computing paradigm for nonlinear multi-singular third-order Emden–Fowler equation

2020 ◽  
Author(s):  
Zulqurnain Sabir ◽  
Muhammad Umar ◽  
Juan L. G. Guirao ◽  
Muhammad Shoaib ◽  
Muhammad Asif Zahoor Raja
Keyword(s):  
Third Order ◽  
Intelligent Computing ◽  
Computing Paradigm ◽  
Fowler Equation

Neuro-swarm intelligent computing paradigm for nonlinear HIV infection model with CD4+ T-cells

2021 ◽  
Author(s):  
Muhammad Umar ◽  
Zulqurnain Sabir ◽  
Muhammad Asif Zahoor Raja ◽  
J.F. Gómez Aguilar ◽  
Fazli Amin ◽  
...  
Keyword(s):  
T Cells ◽  
Hiv Infection ◽  
Cd4 T Cells ◽  
Infection Model ◽  
Intelligent Computing ◽  
Computing Paradigm ◽  
Hiv Infection Model

Ohmic heating effects and entropy generation for nanofluidic system of Ree-Eyring fluid: Intelligent computing paradigm

2021 ◽  
Vol 129 ◽  
pp. 105683
Author(s):  
Muhammad Shoaib ◽  
Ghania Zubair ◽  
Kottakkaran Sooppy Nisar ◽  
Muhammad Asif Zahoor Raja ◽  
Muhammad Ijaz Khan ◽  
...  
Keyword(s):  
Entropy Generation ◽  
Ohmic Heating ◽  
Intelligent Computing ◽  
Computing Paradigm ◽  
Heating Effects ◽  
Nanofluidic System

scholarly journals Cloud-Based Autonomic Computing Framework for Securing SCADA Systems

2020 ◽  
pp. 276-297
Author(s):  
Sajid Nazir ◽  
Shushma Patel ◽  
Dilip Patel
Keyword(s):  
Cyber Security ◽  
Autonomic Computing ◽  
Distribution Networks ◽  
Intelligent Computing ◽  
Cyber Threats ◽  
Computing Paradigm ◽  
Scada Systems ◽  
Computing Framework ◽  
Cloud Infrastructures ◽  
Isolated Systems

This chapter proposes an autonomic computing security framework for protecting cloud-based supervisory control and data acquisition (SCADA) systems against cyber threats. Autonomic computing paradigm is based on intelligent computing that can autonomously take actions under given conditions. These technologies have been successfully applied to many problem domains requiring autonomous operations. One such area of national interest is SCADA systems that monitor critical infrastructures such as transportation networks, large manufacturing, business and health facilities, power generation, and distribution networks. The SCADA systems have evolved from isolated systems into a complex, highly connected systems requiring constant availability. The migration of such systems from in-house to cloud infrastructures has gradually gained prominence. The deployments over cloud infrastructures have brought new cyber security threats, challenges, and mitigation opportunities. SCADA deployment to cloud makes it imperative to adopt newer architectures and measures that can proactively and autonomously react to an impending threat.

scholarly journals Autonomic Computing Architecture for SCADA Cyber Security

2020 ◽  
pp. 543-557
Author(s):  
Sajid Nazir ◽  
Shushma Patel ◽  
Dilip Patel
Keyword(s):  
Cyber Security ◽  
Autonomic Computing ◽  
Distribution Networks ◽  
High Availability ◽  
Computing Systems ◽  
Intelligent Computing ◽  
Autonomous Operation ◽  
Computing Paradigm ◽  
Scada System ◽  
Scada Systems

Autonomic computing paradigm is based on intelligent computing systems that can autonomously take actions under given conditions. These technologies have been successfully applied to many problem domains requiring autonomous operation. One such area of national interest is SCADA systems that monitor critical infrastructures such as transportation networks, large manufacturing, business and health facilities, power generation, and distribution networks. The SCADA systems have evolved into a complex, highly connected system requiring high availability. On the other hand, cyber threats to these infrastructures have increasingly become more sophisticated, extensive and numerous. This highlights the need for newer measures that can proactively and autonomously react to an impending threat. This article proposes a SCADA system framework to leverage autonomic computing elements in the architecture for coping with the current challenges and threats of cyber security.

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