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743 articles for “Network Model”
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The Formulation of Neural Network Model
Abstract: Mathematically, a neural network model is presented in this paper. This formulation is efficient and secure to apply to design any network model for information, data analysis, decision, prediction etc. The compact formula is defined over the set of polynomials. The finiteness & discreteness allows this formation efficient and feasibility &isomorphism provides the security. These advantages are carried this formulation. Probability is also applied to transform the result for analyzing …
Published in Recent Trends in Electronics Communication Systems · Vol. 6, Issue 2, 2019 · pp. 26–32 Read article
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Fast Fuzzy Network Model
Abstract: Fuzzy is applied to design a network model for performing efficiently in this paper. The probability theory is applied to analyze the existed network model and the advantages transformed into the proposed fast fuzzy network model. Various analysis techniques and formulations are presented in this paper. The resultant is the fast fuzzy network with minimized error and maximized the security over the standard computational complexity.
Published in Recent Trends in Electronics Communication Systems · Vol. 6, Issue 2, 2019 · pp. 33–38 Read article
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BREAKDOWN VOLTAGE TEST OF DIFFERENT SOLID INSULATING MATERIALS USING ARTIFICIAL NEURAL NETWORK MODEL
Abstract: In this paper we are presenting Artificial Neural Network (MFNN) model which has different possible inputs affecting the breakdown voltage that are working temperature, the insulating material thickness, dielectric strength of insulating material, volume resistivity of materials, dissipation factor, conductivity of materials, and the materials relative permittivity that also predicts the breakdown voltage as a function of all these inputs parameters. It is important to train the Artificial Neural Network …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 6, Issue 2, 2018 · pp. 22–29 Read article
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Convolution Neural Network Model for Intrusion Detection in Network
Abstract: The evolution of the internet has made protecting information a necessity. Network intrusion and prevention plays an integral role in network-based security. The Intrusion technologies primarily used in today’s world deploy various machine learning algorithms and train models based on them resulting in effectively low detection rates. A technical advancement from machine learning, Deep Learning employs complex mechanisms to extract features from samples. As observed that conventional intrusion detection systems …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 8, Issue 1, 2021 · pp. 7–13 Read article
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An Offline Space Division Multiplexing Based Elastic Optical Network Model with Switching and Modulation Format Adaptation for Flexible Spectrum and Spatial Assignment
Abstract: Abstract: The Space Division Multiplexing (SDM) based Elastic Optical Networks (EONs) (SDM-bEONs) is the proposed solution to both, the required upgradation of the network’s capacity constrained by the non-linear Shannon’s limit and the provisioning needed for the future diverse Internet traffic’s required capacity. With SDM providing ‘space’ as an additional freedom degree, the assignment of resource (i.e., spectrum and space) in the SDM-b-EONs translates into the Routing, Modulation Format, Space, …
Published in Trends in Opto-electro & Optical Communication · Vol. 9, Issue 1, 2019 · pp. 1–23 Read article
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Prediction of Excitation Current of Synchronous Machines Based on Neural Network Model
Abstract: There are several difficulties found to estimate the excitation current & and optimum input parameters of synchronous motors. Heuristic methods are frequently used to weightt the problem's parameters or optimum coefficients. As a result, a neural network model is modified in this study to explore the best parameters and estimate the excitation current of a synchronous motor with minimal prediction errors for both the testing dataset and cross validation. Excitation …
Published in Recent Trends in Electronics Communication Systems · Vol. 10, Issue 1, 2023 · pp. 28–33 Read article
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Real-world Pothole Detection Using Image Processing and Deep Learning Convolutional Neural Network Model
Abstract: Potholes are a major problem of concern in many parts of the cities across the country. Road accidents are one of the causes that significantly affect humanity and result in damage to vehicles and road surface. Potholes are dangerous for pedestrians who walk along the road and vehicular traffic on busy roads. Road accidents are caused due to improper maintenance of roads, and it is imperative to attend to such …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 95–103 Read article
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Network Models: TCP/Internet Protocol vs. OSI
Abstract: Networking your computer dramatically enhances their ability to communicate and most computer are used more for communication than computation. The positive impact of computers grows in direct proportion to the number and type of computers that participate in network. One of the greatest benefits of TCP/IP is that it provides interoperable communication between all types of hardware and operating system. TCP/IP is an abbreviation for transmission control protocol/internet protocol. TCP/IP …
Published in Journal of Advances in Shell Programming Read article
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Artificial Neural Network Modelling to Optimize Micro-Drilling Parameters of ECDM of Developed Novel Zn/(Ag+Fe)-MMC
Abstract: Several engineering fields have increased their use of metal matrix composites (MMCs) in the past few years. Due to the increase in composites, the demand for accurate machining has also become important. Specifically, pertaining to biomaterial applications, accuracy factor with desired surface finish is critical. While the near-net shape manufacturing process has advanced, MMCs frequently require post-mould machining to achieve surface quality, and dimensional tolerances. In the present study, a …
Published in Journal of Polymer & Composites · Vol. 11, Issue 1, 2023 · pp. 01–13 Read article
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Development and Evaluation of Neural Network Model for Incident Detection on Urban Arterials using Simulated Database
Abstract: Incident detection in urban arterial situation is more difficult than the similar job in freeway situation because of the presence of traffic signals and other intersections with associated recurrent queue. Most of the earlier automatic incident detection algorithms address mainly freeway situation. This study aims at development, calibration, validation and testing of an ANN model for incident detection in Kuala Lumpur (KL) arterials using simulated incident database. Database for the …
Published in Trends in Transport Engineering and Applications · Vol. 1, Issue 2, 2014 · pp. 1–14 Read article
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Artificial Neural Network Model for Stock Market Forecasting
Abstract: AbstractIn recent years, many attempts have been made to predict the behavior of bonds, currencies, stocks or stock markets. Neural networks, as an intelligent data mining method, have been used in many different challenging pattern recognition problems such as stock market prediction. The aim of this paper is to predict stock market using artificial neural networks (ANNs). The authors used feed forward neural network trained by back-propagation algorithm to make …
Published in Journal of Computer Technology & Applications · Vol. 5, Issue 1, 2014 · pp. 7–12 Read article
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An Advance Model for Network Security System Using NIDS and HIDS
Abstract: important role. As use of internet is increasing fear of losing the data is also increased. In this paper a mechanism to secure the data is discussed which is known as intrusion detection system (IDS). This system’s major task is to detect the abnormal activities or attacks done by intrusion over network or host. With the help of this security system, we can maintain the security of data over the …
Published in Journal of Electronic Design Technology · Vol. 10, Issue 3, 2019 · pp. 42–52 Read article
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Modeling of Sintering Process for the Preparation of Magnetic Abrasives by RSM and ANN Models
Abstract: In this study, a modeling has been done for the prediction of the sintering process, as sintering process is one of the best processes to prepare magnetic abrasives. The sintering process is modelled by using RSM and ANN techniques. The ANN model has been developed using a multilayer feed-forward neural network and trained with the help of an error backpropagation learning algorithm based on the generalized delta rule. The indication …
Published in Journal of Experimental & Applied Mechanics · Vol. 10, Issue 3, 2019 · pp. 5–12 Read article
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Nonlinear Semiconductor Device Modeling using Neural Networks
Abstract: This paper describes the nonlinear semiconductor (transistor) of small and large signal modeling using a single neural network. Multilayer perceptron (MLP) with back-propagation (BP) learning is adopted in this work to model the drain current (ID) and the transconductance (gm) of the transistor. MLP modeling performance in terms of mean square error (MSE) and complexity of the network are illustrated briefly. Artificial neural network (ANN) model outcome for nonlinear function …
Published in Journal of VLSI Design Tools and Technology · Vol. 4, Issue 3, 2014 · pp. 1–6 Read article
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Study of an Improved Quantum Particle Swarm Optimization-Based Framework for Neural Network Optimization in Modelling of Polymer Data
Abstract: The accurate forecasting of polymer viscosity at various physicochemical conditions has been quite critical due to the nonlinear interactions and interrelations between the variables. This paper suggests a better hybrid modelling framework, which involves the use of Artificial Neural Networks (ANN) and more advanced versions of Quantum Particle Swarm Optimization (QPSO) to better predict polymer viscosity. The input parameters taken are, namely, log (shear rate), polymer concentration, NaCl concentration, Ca …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 282–297 Read article
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A Novel Approach Integrated Dc To Dc Fast Charging Module
Abstract: This paper presents a wide variation of input dc voltage. It is a “step-up” inverter, meaning that only one power stage works at high frequency in order to achieve minimum switching loss. When input dc voltage is lower than the magnitude of the ac voltage, it is a voltage-source inverter, and on it is current-source inverter in the other mode. The leakage current caused by the capacitance can be reduced …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 9, Issue 2, 2022 · pp. 26–32 Read article
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Performance Evaluation of Adaptive MIMO-OFDM System Model for Wireless Networks
Abstract: Enormous growth of wireless technologies and research trends in networking has developed many useful applications. Wireless networks with various protocols and standards are huge in demand because of the expansion of internet of things (IoT). All wireless networks demand for high data rate, low energy consumption, higher throughput, more reliability, better quality of services (QoS) and quality of information (QoI). This paper presents multiple in multiple out (MIMO) orthogonal frequency …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 4, Issue 1, 2017 · pp. 17–23 Read article
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Computational Approaches to Understanding Cellular Signaling Pathways
Abstract: Cellular signaling pathways are fundamental in regulating vital processes, such as cell growth, differentiation, and apoptosis. The intricate and interconnected nature of these signaling networks requires sophisticated methods for their analysis. Computational approaches, including mathematical modeling, network analysis, and machine learning, have revolutionized the way researchers analyze and simulate cellular signaling. This article provides a comprehensive overview of computational strategies employed to model signaling pathways, with a focus on integrating …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 8–13 Read article
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Modelling Electronic Diode Networks with PSPICE Simulation
Abstract: The dual of Thevenin, Norton equivalent circuit is used in place of any circuit/network of linear sources and immittances at at a given frequency. Both Thevenin with Norton theorem is useful for analyses and modification of circuits, to study /obtain network’s steady state response and initial condition. Methods to represent different circuits with Thevenin/Norton impedances connected at desired nodes are given using Spice/Pspice. The Thevenin/Norton impedances connected are of other …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 2, 2024 · pp. 17–37 Read article
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Evaluation of Effect of Seeds and Downloaders on the Performance of BitTorrent Network using Markov Chain Modeling
Abstract: AbstractIn this paper, we are using existing Markov chain model to study the effect of count of seeds and downloaders on transition rates, which is an important parameter in Markov chain modeling. As of now, many analytical modeling techniques are used to evaluate the performance of BitTorrent network and Markov chain model is found to be an effective, accurate and extendible one. Many researchers have studied BitTorrent networks to evaluate …
Published in Journal of Communication Engineering & Systems · Vol. 6, Issue 1, 2016 · pp. 30–37 Read article