Search
9 articles for “neural network (NN)”
-
An Investigation of Model Predictive Control in Self-driving Vehicles
Abstract: Autonomous vehicles, which are often known as self-driving automobiles or driverless cars, are vehicles that can navigate and operate without human intervention. They require efficient controllers capable of handling complexities, with reduced computational costs, and should handle multiple inputs and outputs simultaneously. Model predictive control (MPC) possesses all these characteristics which means it can be utilized effectively for the same purpose. MPC for autonomous vehicles proposes various ways of achieving …
Published in Trends in Electrical Engineering · Vol. 14, Issue 1, 2024 · pp. 40–50 Read article
-
Adaptive Routing Protocol to Optimize the Quality of Service of MANET Using Neural Network
Abstract: A MANET is a group of mobile nodes that create a temporary network without relying on centralized administration or standard supporting devices, often functioning as a conventional network. These dynamic environments present significant challenges for traditional routing and switching protocols, particularly in delivering Quality of Service (QoS) benchmarks such as bandwidth, latency, packet delivery ratio, and robustness. This study proposes an Adaptive Routing Protocol (ARP) leveraging Neural Network (NN) techniques …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 3, 2025 · pp. 01–09 Read article
-
Neural Network Based Fractional Order PID Controller for Harmonic Mitigation of Induction Motor Drive System
Abstract: Torque produced in IM (induction Motor) is collected fundamental torque, however, due to core saturation, air gap irregularity, and winding distribution; stator and rotor slotting harmonics torque are produced. This reduces the quality of the power system, life span, and performance of the motor and the controller device. In this paper, a neural network, based fractional order proportional integral derivative (NNFOPID) controller is designed to compensate the harmonics of the …
Published in International Journal of Electrical Power and Machine Systems · Vol. 1, Issue 1, 2023 · pp. 23–41 Read article
-
A Comprehensive Analysis of Machine Learning Models for Credit Card Fraud Detection
Abstract: This paper presents an indepth comparison of various machine learning models—Logistic Regression, Support Vector Classification (SVC), and Neural Networks (NN)—in the context of credit card fraud detection. The analysis spans multiple performance metrics, including accuracy, F1 score, precision, recall, and computational efficiency. Logistic Regression demonstrates competitive performance in terms of accuracy, but its poor precision renders it unsuitable for fraud detection tasks. Conversely, the Neural Network exhibits balanced precision and …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
-
Hybrid Techniques in Mango Leaf Disease Identification: Evaluating Neural Networks and Support Vector Machines
Abstract: Mango leaf diseases pose a significant threat to mango production, impacting both yield and fruit quality. Early and accurate detection of these diseases is crucial for effective management. This paper evaluates the use of hybrid techniques, specifically the integration of neural networks (NNs) and support vector machines (SVM), in the identification and classification of mango leaf diseases. NN excel in extracting complex features from images, while SVMs are robust classifiers, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 19–27 Read article
-
FLUTTERCHAT: A Real-time Firebase Chat Application with AI-based Chatbot
Abstract: Recently, the development and deployment of chatbots have gathered significant attention from both developers and researchers. Chatbots represent AI-driven conversational systems capable of understanding and responding to human language using advanced techniques like Natural Language Processing (NLP) and Neural Networks (NN). A cutting-edge real-time chat application has been crafted using Flutter and OpenAI, seamlessly integrating an AI-powered chatbot with an innovative image generator to enrich user interaction and engagement. The …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 1, 2025 · pp. 42–51 Read article
-
Alzheimer’s Disease Detection Using ML Algorithm
Abstract: A degenerative neurological state of affairs, Alzheimer's disease (AD) gradually impairs cognitive and functional capacities, especially in people over 65. Early AD detection is crucial for efficient management and treatment prep. This study delves into novel approaches for the early detection of AD using non-invasive methods. We've implemented a blend of neuroimaging data analysis and machine learning algorithms to pinpoint markers indicative of the disease during its initial phases. Our …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 53–57 Read article
-
Deep Learning Based Detection and Classification of Brain Tumors Using MRI Images
Abstract: Brain tumor detection using magnetic resonance imaging (MRI) is a critical task in the early detection and treatment of brain tumors. Manual analysis of brain tumor detection using MRI is a tedious task that requires expertise in the field. Therefore, this study proposes a deep learning-based approach for brain tumor detection and classification using Convolutional Neural Networks (CNN). The proposed approach preprocesses the MRI image using normalization, resizing, and noise …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
-
Conceptualization of An Intelligent Decision Framework for Control Factors and Weld Quality Prediction
Abstract: To improve the robot's welding quality, control welding precision, optimize welding parameters, realize continuous welding quality database optimization, and increase welding defect detection, a fuzzy neural network-based intelligent decision-making system must be built. This study demonstrates how fuzzy control theory and BP neural networks may be used to identify welding issues and enhance process variables. The experimental findings indicate that, with seam classification accuracy close to 90%, enhancing welding parameters …
Published in Journal of Polymer & Composites · Vol. 11, Issue 6, 2023 · pp. 10–19 Read article