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11 results for “BPNN”
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Research ArticleOpen accessIn the keywordsDesign an Advance Computer-Aided Tool for Image Authentication and ClassificationRozita Teymourzadeh, Amirize Alpha Laadi, Yazan Samir Algnabi et al.Over the years, advancements in the fields of digital image processing and artificial intelligence have been applied in solving many real-life problems. This could be seen in facial image recognition for security systems, identity registrations. Hence a bottleneck of identity registration is image processing. These are carried out in form of image preprocessing, image region extraction by cropping, feature extraction … …American Journal of Applied Sciences, Vol. 10, Issue 7 · 24 Jun 2013 · 6,561 accessesView PDFCite
Research ArticleOpen accessIn the keywordsNeural Networks Based Nonlinear Time Series Regression for Water Level Forecasting of Dungun RiverSiti Hajar Arbain, Antoni WibowoThe Department of Irrigation and Drainage (DID) Malaysia and Meteorological Malaysia Department (MMD) has been measured the flood characteristics benchmark which included water level, area inundation, peak inundation, peak discharge, volume of flow and duration of flooding. In terms of water levels, DID have introduced three categories of critical level stages namely normal, alert and danger levels. One of the … …Journal of Computer Science, Vol. 8, Issue 9 · 13 Aug 2012 · 7,792 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimization of α-Glucosidase Inhibitors Recovery from Rainbow Trout Hydrolysate Using GA-BP Neural NetworkYingke Chu, Yanling Dong, Qingfeng Rong et al.To enhance the value of by-products from rainbow trout processing, the inhibition rate of α-glucosidase (AGIR) is used as indicators. Optimization of rainbow trout hydrolysate extraction by comparing Response Surface Methodology (RSM) and BP Neural Network (BPNN) models. The RSM results: the AGIR is 55.02%. BPNN models predicted the optimal extraction conditions: 51℃ for temperature,1:2.3 for solid-liquid ratio, 4.15 h … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 3 · 28 Jan 2026 · 1,734 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Depression Levels using Back Propagation Neural NetworkEddy Muntina Dharma, Yaya Heryadi, Lukas et al.Depression is a mood disorder characterized by feelings of deep sadness and a sense of indifference. When depression recurs in moderate or severe intensity, it can be a serious health condition. The most effective way to deal with this problem is to predict the symptoms of depression at an early stage. In this study, a Back Propagation Neural Network (BPNN) … …Journal of Computer Science, Vol. 18, Issue 3 · 18 Mar 2022 · 6,882 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Backpropagation Neural Network for Splitting IdentifiersAhmed Sabah Ahmed AL-Jumaili, Huda Kadhim Tayyeh, Ruqaia Jawad KadhemSplitting identifiers is a task that has been addressed in the past few years in order to contribute toward improving the Feature Location task. Feature Location aims at determining the exact position of a specific feature within a source code. Several research studies have addressed the process of splitting multi-word identifiers. However, one of the endure gaps that still face … …Journal of Computer Science, Vol. 14, Issue 10 · 31 Oct 2018 · 7,227 accessesView PDFCite
Research ArticleOpen accessIn the abstractLecturer Performance Analysis using Multiple ClassifiersHawraz Ahmad, Tarik RashidLecturer performance analysis has enormous influence on the educational life of lecturers in universities. The existing system in universities in Kurdistan-Iraq is conducted conventionally, what is more, the evaluation process of performance analysis of lecturers is assessed by the managers at various branches at the university andin view of that, in some cases the outcomes of this process cause a … …Journal of Computer Science, Vol. 12, Issue 5 · 13 Jun 2016 · 7,847 accessesView PDFCite
Research ArticleOpen accessIn the abstractA TIME-DELAY CASCADING NEURAL NETWORK ARCHITECTURE FOR MODELING TIME-DEPENDENT PREDICTOR IN ONSET PREDICTIONAgus Buono, Imas Sukaesih Sitanggang, Mushthofa, Aziz KustiyoThe occurrence of rain before the real start of a rainy season often mislead farmers into thinking that rainy season has started and suggesting them to start planting immediately. In reality, rainy season has not started yet, causing the already-planted rice seed to experience dehydration. Therefore, a model that can predict the onset of rainy season is required, so that … …Journal of Computer Science, Vol. 10, Issue 6 · 29 Jan 2014 · 6,647 accessesView PDFCite
Research ArticleOpen accessIn the abstractDECISION TREE BASED OCCLUSION DETECTION IN FACE RECOGNITION AND ESTIMATION OF HUMAN AGE USING BACK PROPAGATION NEURAL NETWORKP. Karthigayani, S. SridharOcclusion detection in face verification is an essential problem that has not widely addressed. In this study the research is deals about occlusion detection in face recognition and estimation of human age using image processing. The objects hide from another object is called as occlusion. Occlusion conditions may vary from face wearing sunglasses, wearing of scarf in the eyes and … …Journal of Computer Science, Vol. 10, Issue 1 · 12 Nov 2013 · 6,770 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhanced Ensemble Prediction Algorithms for Detecting Faulty Modules in Object Oriented Systems Using Quality MetricsM. Punithavalli, C. NeelamegamThe high usage of software system poses high quality demand from users, which results in increased software complexity. To address these complexities, software quality engineering methods should be updated accordingly and enhance their quality assuring methods. Fault prediction, a sub-task of SQE, is designed to solve this issue and provide a strategy to identify faulty parts of a program, so … …Journal of Computer Science, Vol. 8, Issue 12 · 20 Dec 2012 · 6,435 accessesView PDFCite
Research ArticleOpen accessIn the abstractModeling of Piezoelectric Actuators Based on Bayesian Regularization Back Propagation Neural NetworkWen Wang, Zhu Zhu, Yanding Wei, Zichen ChenProblem statement: Piezoelectric actuator is a kind of key driving components for micropositioning stages, micropumps, micro valves, micro gripper and so on in the fields of micro/nano technology such as integrated circuit manufacturing, precision instruments, ultra precision fabrication, biomedical manipulation. It has lots of advantages including high stiffness, fast response times, less heat generating, low power consumption and large force … …Current Research in Nanotechnology, Vol. 1, Issue 1 · 15 Jun 2011 · 7,059 accessesView PDFCite