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85 articles for “Artificial Neural Network (BP-ANN)”
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Research ArticleOpen accessIn the abstractSoftware Development Effort Estimation Using Relational Database and Optimized Learning MechanismRavi Kumar B. N., Yeresime SureshAccurately estimating the cost of software development is crucial for effective project planning and resource allocation. However, traditional cost estimation methods rely heavily on expert judgment and historical data, which can be time consuming and prone to errors. This study suggests a learning-based cost estimation model that leverages relational databases to improve accuracy. The proposed approach estimates project cost based … …Journal of Computer Science, Vol. 19, Issue 4 · 7 Apr 2023 · 6,313 accessesView PDFCite
Review ArticleOpen accessIn the abstractArtificial Intelligence in COVID-19 Management: A Systematic ReviewSamaneh Mohammadi, SeyedAhmad SeyedAlinaghi et al.With the development of modern technologies in the field of healthcare, the use of Artificial Intelligence (AI) in disease management is increasing. AI methods may assist healthcare providers in the COVID-19 era. The current study aimed to observe the efficacy and importance of AI for managing the COVID-19 pandemic. An organized search was conducted, utilizing PubMed, Web of Science, Scopus, … …Journal of Computer Science, Vol. 19, Issue 5 · 30 Mar 2023 · 8,052 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Backward Regressed Capsule Neural Network for Plant Leaf Disease DetectionJennifer Jepkoech, Benson Kipkemboi Kenduiywo, David Muchangi Mugo, Edna Chebet ToolThis study investigated the introduction ofbackward regression coupled with DenseNet features in a Capsule Neural Network(CapsNet) for plant leaf disease classification. Plant diseases are consideredone of the main factors influencing food production and therefore fast cropdisease detection and recognition are important in enhancing food securityinterventions. CapsNets have successfully been adopted for plant leaf diseaseclassification however, backpropagation of signals to preceding … …Journal of Computer Science, Vol. 18, Issue 9 · 8 Sep 2022 · 5,718 accessesView PDFCite
Research ArticleOpen accessIn the abstractPhonocardiogram Classification Based on Machine Learning with Multiple Sound FeaturesKhalid M.O. Nahar, Obaida M. Al-Hazaimeh, Ashraf Abu-Ein, Nasr GharaibehIn this study the heartbeat sound signals were tackled by classifying them into heart disease categories such as normal, artifact, murmur and extrahals in an attempt for early detection of heart defects. Phonocardiogram (i.e., PCG) is used to obtain the digital recording dataset of the heart sounds using an electronic stethoscope or mobile device. Multiple features are extracted from the … …Journal of Computer Science, Vol. 16, Issue 11 · 26 Nov 2020 · 8,259 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrediction of Data Traffic in Telecom Networks based on Deep Neural NetworksQuang Hung Do, Thi Thanh Hang Doan, Thi Van Anh Nguyen et al.Accurate prediction of data traffic in telecom network is a challenging task for a better network management. It advances dynamic resource allocation and power management. This study employs deep neural networks including Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) techniques to one-hour-ahead forecast the volume of expected traffic and compares this approach to other methods including Adaptive Neuro-Fuzzy … …Journal of Computer Science, Vol. 16, Issue 9 · 30 Sep 2020 · 8,059 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Attendance System Using Artificial Neural Network Based on Students’ BackgroundDaban Abdulsalam Abdullah, Karzan Wakil, Shwan H.H. AlshatriDetermining the rate of student attendance is an important task in determining the completion of the courses. Despite the success of the technology, it is unfortunate that in many academic institutions, the current systems used to detect student absences. Furthermore, one of the crucial problems in the attendance system does not count student background for continuing in the courses. In … …Journal of Computer Science, Vol. 16, Issue 7 · 21 Jul 2020 · 6,764 accessesView PDFCite
Review ArticleOpen accessIn the abstractAI-Based Techniques for DDoS Attack Detection in WSN: A Systematic Literature ReviewMohammed Al-Naeem, Mohammed Ashikur Rahman, Adamu AbuBakar Ibrahim, M.M. Hafizur RahmanWireless Sensor Networks (WSNs) are currently being used in various industries such as healthcare, engineering, the environment and so on. Security is a significant issue for WSN due to its infrastructure and limited physical security. Distributed Denial of Service (DDoS) is one of the most vulnerable attacks that can be defined as attacks launched from multiple ends into a set … …Journal of Computer Science, Vol. 16, Issue 6 · 29 Jun 2020 · 8,375 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparison of Linear and Non-Linear Regression Models for Non-Invasive Blood Glucose MeasurementDorsaf Ghozzi, Yassine Manai, Khaled NouriThis paper deals with a new approach of non-invasive glucose monitoring based on near infrared spectroscopy. The proposed approach is coupled with a regression analysis in order to improve the predictive capacity of the designed device. Basic spectral data is a comparison that has been established between linear and non-linear machine learning regression algorithms. The experimental results show that feed … …Journal of Computer Science, Vol. 15, Issue 11 · 13 Nov 2019 · 7,864 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficiency of Hybrid MPPT Techniques Based on ANN and PSO for Photovoltaic Systems under Partially Shading ConditionsMax Tatsuhiko Mitsuya, Anderson Alvarenga de Moura MenesesHybrid Maximum Power Point Tracking (MPPT) algorithms have been investigated as an alternative to improve the performance of conventional MPPT, such as Perturb and Observe (P&O), Incremental Conductance (InC) and Hill Climbing (HC) in Photovoltaic (PV) systems under Partially Shading Co+ndition (PSC). In the present article, Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) hybridized with P&O algorithm for … …American Journal of Engineering and Applied Sciences, Vol. 12, Issue 4 · 3 Oct 2019 · 8,888 accessesView PDFCite
Research ArticleOpen accessIn the abstractDesign and Implementation of Myoelectric Controlled ArmTariq M. Younes, Mohammad A. AlKhedher, Abdel-Hamid Soliman, Aiman Al AlawinIn this study a discrimination system, using a neural network for Electromyogram (EMG) externally controlled Arm is proposed. In this system, the Artificial Neural Network (ANN) is used to learn the relation between the power spectrum of EMG signal analysed by Fast Fourier Transform (FFT) and the performance desired by handicapped people. The Neural Network can discriminate 4 performances of … …Journal of Mechatronics and Robotics, Vol. 3, Issue 1 · 16 Sep 2019 · 6,281 accessesView PDFCite