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42 articles for “single neural network”
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Achieving Multi-objectives Using a Single Neural Network
Abstract: Achieving multi-objectives using a single neural network is a research area that aims to develop techniques to optimize multiple objectives simultaneously using a single neural network. This approach can be applied in various fields, such as image and speech recognition, robotics, and natural language processing, to achieve better performance and reduce the complexity of the models. The key challenge in this area is to balance the trade-off between different objectives …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 9, Issue 3, 2022 · pp. 1–15 Read article
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Comparative Analysis of Neural Network and Linear Regression Applied to Black Friday Data
Abstract: AbstractIn this study, it compares two different types of neural networks. First is a single layer neural network and other is multiple hidden layer neural network. For just comparisons it is ensured that both uses the same activation and output functions and have the same number of nodes and parameters. The networks are trained by the gradient descent algorithm to approximate linear and quadratic functions and examine their convergence properties. …
Published in Current Trends in Signal Processing · Vol. 9, Issue 3, 2019 · pp. 1–4 Read article
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Polypyrrole-Based Conductive Polymer-Gated Single Electron Transistor with Deep Neural Network Assistance for Biomedical Energy Harvesting and Charge Detection
Abstract: The increasing demand for intelligent biomedical monitoring systems has accelerated research into ultra-low-power sensing technologies capable of operating with high sensitivity and minimal energy consumption. Conductive polymers have attracted considerable attention for biomedical and nanoelectronic applications due to their tunable electrical properties, biocompatibility, and environmental stability. Among them, Polypyrrole (PPy) is a promising functional polymer that can enhance charge transport and electrostatic coupling in nanoscale devices. In this work, a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 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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Stock Market Prediction with LSTM-based Neural Networks: An Empirical Analysis
Abstract: A stock market is a composite of markets and exchanges where the buying and selling of publicly traded company stocks occur on a regular basis. It serves as a marketplace for the stocks of corporations that are available to the public. Companies opt for an initial public offering (IPO) on the primary market as a means to generate capital. People buy stocks primarily in the hope that they may rise …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 1, 2023 · pp. 9–14 Read article
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Advance Surveillance System Integrated with Weapon Detection and Accident Detection
Abstract: Security concerns have become paramount as there is rise in crime rates in crowded events and isolated areas. Abnormal event detection and monitoring system, utilizing computer vision, are crucial for tackling these challenges. In parallel, reducing mortality rates from accidents by ensuring timely emergency response in essential. This study presents the implementation of automatic weapon detection and accident detection. In weapon detection, YOLO v4, Convolutional Neural Networks (CNN), and Faster …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 1, 2025 · pp. 47–54 Read article
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Support Vector Machine Inspired Load Forecasting of a State University in Haryana
Abstract: Estimating the possible environmental impact and determining probable capital requirements are made easier with a solid grasp of electricity demand. Beginning in the middle of the 20th century, demand forecasting for electric power networks was studied theoretically. Prior to that, the study of demand forecasting had not developed because of the small scale of power networks. With the use of statistical prediction techniques, plans for the electric power industry have …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 33–40 Read article
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Modeling and Simulation of a Hybrid Solar-Wind System with Adaptive Neural Network MPPT Control in MATLAB/SIMULINK
Abstract: Over the last ten years, there has been an increasing demand for the electrical powersupply. The installation of power generators (PGs) is expensive and time-consuming. Solar powerplants are therefore thought to be a practical substitute for supplying the present demand forelectricity. The primary challenges with solar plants, however, are output power balancing andcritical maintenance. A proper technique is needed to lessen output power balance andmaintenance issues in solar facilities. For …
Published in Journal of Power Electronics and Power Systems · Vol. 13, Issue 2, 2023 · pp. 53–61 Read article
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Predicting Software Reliability using Artificial Neural Networks: A Review
Abstract: AbstractSoftware reliability has become a major concern for all the software systems. Predicting software reliability has become a major challenge for both the software developers and the engineers. Before the software is dispensed to the market/customers, it is thoroughly checked for any errors and if errors are there, they are thereby removed. For the purpose of reliability estimation certain mathematical software reliability models have been proposed for estimating the reliability …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 6, Issue 2, 2019 · pp. 14–19 Read article
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Temperature Control System using Artificial Intelligence
Abstract: Artificial Intelligence (AI) based controller for temperature control of a water bath system. The generation of membership function is a changeling problem for fuzzy systems and the response of fuzzy systems depends mainly on the membership functions. Artificial Neural Network based input and output used to tune the membership functions in fuzzy system. Two input and single output artificial intelligence is designed to control the temperature system .Further the tuning …
Published in Journal of Control & Instrumentation · Vol. 3, Issue 1-3, 2012 · pp. 76–83 Read article
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Evolving Perspectives: Innovations in Object Detection and Identification
Abstract: One of the most important developments in computer vision has been the creation of object detection and identification systems, which have allowed robots to perceive and understand visual data similarly to humans. These systems locate each object by drawing a bounding box around it, in addition to detecting and classifying every object in an image or video. This study suggests a novel method for item identification and detection that makes …
Published in Trends in Opto-electro & Optical Communication · Vol. 13, Issue 3, 2023 · pp. 23–27 Read article
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Unsupervised Learning Techniques in Neural Network for Face Recognition
Abstract: This paper represents the review of systematic comparison between of unsupervised learning algorithms for face recognition. In neural network, different algorithms are used for face recognition. Each algorithm has different accuracy factors. Commonly these methods asset a set of base images and serve faces as linear combo of images. In our proposed review, firstly we discuss about the face detection using neural network along with the concept of digital image …
Published in Journal of Advancements in Robotics · Vol. 7, Issue 1, 2020 · pp. 25–29 Read article
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Artificial Neural Network Based Prediction of Impact Loads and Thickness in CFRP and GFRP Composite Laminates
Abstract: Recent technological advancements, particularly the integration of neural networks, have facilitated a predictive approach to complex engineering problems, especially those involving composite materials with directional properties. The scarcity of literature on predicting impact damage using experimental and ultrasonic flaw detection data motivated this study. Experimental assessment of impact damage on carbon fiber/epoxy (CFRP) and glass fiber/epoxy (GFRP) composites was conducted using low-velocity drop weight impact testing. Damage assessment employed an …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 2, Issue 1, 2024 · pp. 34–45 Read article
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Forward Collision Avoidance System in a Self-driving Remote Controlled Car: An Application of Machine Intelligence
Abstract: Abstract: The paper discusses the experimental vision-based forward collision avoidance system (FORCAS), an autonomous bot car based on machine learning using Raspberry Pi as a processing platform. Using HD camera images as a primary input, Raspberry Pi combines processes and predict path using convolutional neural network and distance estimation models. It distinguishes the stationary objects on a drivable road surface and estimates their distances from a single camera’s view. Classification …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 3, 2019 · pp. 13–18 Read article
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Regression and ANN Models in Predicting Tool Wear
Abstract: A modern machining system must be able to detect tool wear while milling in order to maintain the product's surface quality. The vibration signatures produced by a single point cutting tool during machining have been found to be good predictors of the tool's health. The current study used Artificial Neural Networks to forecast tool life by analysing vibration signatures when turning EN9 and EN24 steel alloys (ANN). Tool wear prediction …
Published in Journal of Production Research & Management · Vol. 12, Issue 1, 2022 · pp. 14–18 Read article
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Early Alzheimer's Disease Detection Using Deep Ensemble Learning and MRI Image Analysis
Abstract: Early detection of Alzheimer's disease (AD) is crucial to slowing cognitive decline and enabling timely clinical interventions. Traditional diagnostic methods, including cognitive tests and single-model classifiers, have limited sensitivity during early stages of the disease. This paper presents a deep ensemble learning approach that integrates multiple convolutional neural networks (CNNs) for accurate Alzheimer's disease detection using structural Magnetic Resonance Imaging (MRI) data. The proposed framework utilizes ResNet50, VGG16, and DenseNet121 …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 1–9 Read article
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Artificial Neural Network-Based Multifocus Image Fusion
Abstract: Fusion of multiple images is needed for combining information contained in images obtained using different imaging devices or different camera settings. Due to the physics of optical lenses present in these devices, it is difficult to capture an image that has all the relevant objects well in focus. Thus, artificial neural network (ANN)-based multifocus image fusion method in YCbCr color space is proposed. Input images are first mapped from RGB …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 3, 2018 · pp. 16–23 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 Implementation in FPGA using Multiplexer-based Weight Updating for Efficient Resource Utilization
Abstract: This paper presents a novel scheme for field-programmable gate array (FPGA) implementation of an artificial neural network (ANN). The proposed implementation is aimed at reducing resource requirement, without compromising on the speed so that a complex ANN architecture could be realized on a single chip at a lower cost. The weight updating process in different layers of the ANN has been carried using a simple MUX-based architecture. Backpropagation algorithm which …
Published in Journal of Semiconductor Devices and Circuits · Vol. 2, Issue 1, 2015 · pp. 1–5 Read article
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Rehashing State of Art Artificial Intelligence centered Career Counselling Platforms
Abstract: Significant impact due to the rapid computerization and digitization in workplaces have changed the nature of career counselling, choices and development processes. With the ever-changing occupational market, increased number of individuals are facing challenges to acquaintance with the imminent occupations and industries. Significant assistance is offered by career experts to enable people infer, acquire and appraise from these advancements while facilitating in career planning and selection. In India, the career …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 2, 2020 · pp. 28–38 Read article