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147 articles for “Neural networks”
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Intrusion Detection System Using Gated Recurrent Neural Network
Abstract: In the realm of cybersecurity, the constant evolution of threats demands sophisticated intrusion detection systems (IDSs) capable of discerning intricate patterns in network traffic. This study proposes an IDS leveraging the capabilities of gated recurrent neural networks (GRNNs) to enhance the detection of anomalies and potential security breaches. The GRNN architecture, employing mechanisms like long short-term memory (LSTM) and gated recurrent unit (GRU), demonstrates efficacy in capturing long-range dependencies within …
Published in International Journal of Software Computing and Testing · Vol. 10, Issue 1, 2024 · pp. 1–8 Read article
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Investigation of FSO Communication System Using Various Neural Networks
Abstract: A prospective method for high-speed data transfer via light propagation in free space, such as between buildings, satellites, or metropolitan areas, is Free Space Optics (FSO) communication. FSO systems have great promises, but their performance can be severely hampered by atmospheric disturbances. Problems like fog, rain, and turbulence cause the optical signal to be absorbed and scattered, increasing BER. To address these challenges, various Neural Network (NN) techniques such as …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 · pp. 12–20 Read article
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A Comprehensive Study On Optimization Of Neural Networks And Global Minimization
Abstract: The neural network toolbox is one of the commonly used, powerful, commercially available software tools for the constructing new networks and forms a inter linkage between each other. The software is user-friendly, permits flexibility and convenience in interfacing with other toolboxes in the same environment to develop a full application the wide range of applications and has a wide range of scope in making models with linear and non-linear functionalities …
Published in International Journal of Manufacturing and Materials Processing · Vol. 2, Issue 1, 2016 · pp. 11–18 Read article
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A Comprehensive Review of Convolutional Neural Network Architectures and Evolution
Abstract: Convolutional Neural Networks (CNNs) have become a foundational deep learning framework in computer vision because they can automatically extract layered, increasingly complex features directly from raw image data. CNNs use convolutional, pooling, and activation layers to extract spatial patterns from basic edges to intricate object components, drawing inspiration from the human visual cortex. An overview of CNNs’ basic architecture is given in this study, along with an explanation of important …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 1, 2026 · pp. 32–40 Read article
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Evaluation of the Flow Properties of Self-Compacting Fly-ash Concrete Using Artificial Neural Network
Abstract: The purpose of this study is to examine the feasibility of using artificial neural network programming for the calculation of the fresh properties of self-compacting concrete. The input parameters of the neural network were the mix composition influencing the fresh properties of self-compacting concrete namely; the cement content, the dosages of fly-ash, water, fine aggregate, coarse aggregate, and superplasticizer. The model is founded on a multilayer feed forward neural network. …
Published in International Journal of Structural Engineering and Analysis · Vol. 7, Issue 2, 2021 · pp. 35–40 Read article
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Introduction to Kinematics using Artificial Neural Network
Abstract: A neural network is a machine designed to simulate how a specific process or function ofinterest is performed by the brain. To achieve good efficiency, we use a large interconnectionof simple computer cells called "neurons" or "processing units." Therefore, a neural networkviewed as an adaptive machine can be described as a massively parallel distributedprocessor comprising simple processing units with a natural propensity to store experimentalknowledge and make it available for …
Published in International Journal of Analog Integrated Circuits · Vol. 5, Issue 2, 2019 · pp. 1–5 Read article
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Modeling of Material Removal Rate in Micro EDM Using Neural Network
Abstract: In micro-electrical discharge machining (Micro EDM) machining, material removal rate (MRR) is the particular main output parameter. Here we will discover various machining parameters get an effect on the particular MRR. For production industries, to maximize the results from Micro EDM, appropriate predictive designs for MRR must end up being constructed. This particular report utilizes neural network modeling to predict MRR over the particular machining time for assortment of cutting …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 4, Issue 1, 2018 · pp. 30–39 Read article
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Intelligence Video Surveillance Using Deep Learning
Abstract: Intelligent video surveillance powered by deep learning represents a transformative paradigm in security and surveillance. This new approach uses the power of complex neural networks to revolutionize the analysis and management of video data. Through the seamless incorporation of deep learning technologies like convolutional neural networks (CNN) and recurrent neural networks (RNN) into observation systems, automated identification, tracking, and classification of objects can be accomplished, alleviating storage constraints on the …
Published in International Journal of Software Computing and Testing · Vol. 10, Issue 1, 2024 · pp. 9–20 Read article
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Integrated PM2.5 Estimation Using Satellite Images, Pollution Station Data, Meteorological Data and Artificial Neural Network (Case Study: Tehran City)
Abstract: ABSTRACTNowadays, the use of remote sensing to monitor airborne particulates by spatial continuity is made possible by the MODIS Sensor Aerosol Optical Depth (AOD) products. In this study, a simplified aerosol estimation model (SARA) was used to estimate the aerosol optical depth. For this purpose, the MODIS sensor data as inputs to predict PM2.5 near the surface, aerosol optical depth data and meteorological data (wind speed and direction, air temperature, …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 6, Issue 2, 2020 · pp. 38–50 Read article
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Discrete Analysis of Neural Network
Abstract: Network by neural is the continuous process in the modern electronic world. This paper deals with the discrete presentation of neural network. The variables of neural networks are distributed discretely, and its probabilistic study is demonstrated as the advantage of the system of neural networking.
Published in International Journal of Digital Communication and Analog Signals · Vol. 3, Issue 2, 2017 · pp. 15–17 Read article
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An Evaluative Analysis of the Utilization of Artificial Neural Networks in Forecasting Soil Engineering Characteristics: An Overview Study
Abstract: The primary objective of utilizing synthetic neural networks was to emulate the problem-solving approach akin to the human brain. This approach of employing artificial neural networks gained extensive traction within the realm of geotechnical engineering, where the engineering properties of soil play a pivotal role in ensuring the stability of various engineering structures. The primary concern revolves around the strength and deformation characteristics exhibited by soil masses. The focus lies …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 9, Issue 1, 2023 · pp. 55–63 Read article
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AI-Driven Hybrid Neural Network Architecture for Medical Image Segmentation: A Novel Approach for Early Disease Detection
Abstract: One of the key factors in detecting early diseases is medical image segmentation. Medical image segmentation can be very complex due to the differences in image quality, noise, and specific anatomical structures of individual patients. A novel approach for a hybrid neural network structure that combines the power of convolutional neural networks, and the transformer-based models is described here for improved accuracy and robustness of medical image segmentation. Unlike traditional …
Published in International Journal of Microwave Engineering and Technology · Vol. 11, Issue 1, 2025 · pp. 1–7 Read article
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Convolutional Neural Network Algorithm for Stress Field Approximation for a Uniaxially Loaded Plate with Holes
Abstract: ABSTRACTKnowing the high stress concentration and its location around a hole is of practical importance in designing engineering structures, effective parameters can be selected in order to achieve minimum stress concentration around the hole(s). The visualisation of the stress distribution is done experimentally or numerically using finite element analysis (FEA). This study involved the approximation of the von Mises stress field distribution around regular holes in finite metallic plates, based …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 6, Issue 2, 2020 · pp. 1–12 Read article
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Artificial Neural Network Model to Predict Reservoir Storage
Abstract: The rapid growth in population increases water demand thus resulting in scarcity of water which is due to improper management rather than lack of resources. Reservoir is the most important source for surface water. So, reservoir storage plays a crucial role in efficient reservoir management. Artificial neural network (ANN) is capable of simulating reservoir storage capacity. So, in present work cascade forward back propagation and feed forward back propagation network …
Published in International Journal of Water Resources Engineering · Vol. 4, Issue 1, 2018 · pp. 1–8 Read article
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Character Recognition with Neural Network
Abstract: In this project artificial neural network has been called for its application as characters recognizing network. The network is made to learn as per the requirement by training them with some specific patterns that corresponds to the character. The number of input and output layer neurons is chosen. The training patterns and testing patterns are designed using matrices 0’s and 1’s.The weights in the network are adjusted using back propagation …
Published in International Journal of Software Computing and Testing · Vol. 3, Issue 2, 2017 · pp. 32–37 Read article
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DC Voltage Regulation of UPFC Using Artificial Neural Network Controller
Abstract: A feed forward Artificial Neural Network (ANN) with back propagation control is proposed to remove the peak over shoot of the DC capacitor voltage used in Unified Power Flow Controller (UPFC). Proposed ANN controller is tested for the UPFC with wind energy conversion system connected to grid using MATLAB/SIMULINK and the results are compared with the PI controller. From the results, it is clear that ANN controller helps to regulate …
Published in International Journal of Digital Communication and Analog Signals · Vol. 2, Issue 1, 2016 · pp. 13–20 Read article
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Topological Analysis of Artificial Neural Network
Abstract: ABSTRACT This paper analyzes the Artificial Neural Network (ANN) over the metric. The dimension, curvature and mappings are the three characteristics of analysis. The impact of ANN in finite and infinite space is also considered. The Euclidean metric is the limit of generalization. The structure of neuron and its mapping are presented over the finite dimension. The discrete and continuous structure of neurons is studied mathematically and its formulation is …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 5, Issue 1, 2019 · pp. 17–21 Read article
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Direction to Diagnosis by Artificial Neural Network
Abstract: ABSTRACT The diagnosis is presented by the Artificial Neural Network (ANN) in this paper. The method of diagnosis from the data over the ANN is discussed in this paper. The structure of ANN is classified by the coding and probability. Each neuron is set over the data for the diagnosis under the context of minimization of error and maximization of efficiency. Thus, the direction is presented over the mathematical analysis …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 5, Issue 1, 2019 · pp. 1–5 Read article
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Recognition of Vehicle Number Plate Using Mathematical Morphology and Neural Networks
Abstract: This paper presents a method for recognition of the vehicle number plate from the image using neural networks and mathematical morphology. The main theme is to use different morphological operations in such a way so that the number plate of the vehicle can be extracted efficiently. The technique makes the extraction of the plate independent of color, location and size of number plate. The proposed approach can be divided into …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 3, Issue 2, 2017 · pp. 1–4 Read article
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NEURAL NETWORK APPROACH FOR PROCESSING SUBSTATION ALARMS
Abstract: This paper studies the method of processing of alarms in an electric substation using artificial neural networks (ANN) as a tool. Whenever there is a fault in the power system, or there is a significant change in the network, alarms are issued to the substation operators, with each alarm being associated with a message. This is the driving force for research and experiments regarding innovations of more sophisticated methods of …
Published in International Journal of Power Electronics Controllers and Converters · Vol. 1, Issue 1, 2015 · pp. 21–28 Read article