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49 results for “Learning algorithm and training”
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Research ArticleOpen accessIn the abstractPerformance Analysis of Deep Learning Libraries: TensorFlow and PyTorchFelipe Florencio, Thiago Valenç, Edward David Moreno, Methanias Colaço JuniorThrough the increase in deep learning study and use, in the last years there was a development of specific libraries for Deep Neural Network (DNN). Each one of these libraries has different performance results and applies different techniques to optimize the implementation of algorithms. Therefore, even though implementing the same algorithm and using different libraries, the performance of their executions … …Journal of Computer Science, Vol. 15, Issue 6 · 11 Apr 2019 · 10,293 accessesView PDFCite
Research ArticleOpen accessIn the abstractSoft Sensors for Monitoring Combustion Quality and Flue Gas Emissions in Power Station BoilersNallamilli P G Bhavani, Kesavan Sujatha, Ponmagal RajendranThis research work includes a combination of Fisher’s Linear Discriminant (FLD) analysis by merging Radial Basis Function (RBF) Network and Back Propagation Algorithm (BPA) for monitoring the combustion conditions of a coal fired boiler. The CCD Camera is used to capture the two dimensional flame images. The features such as images, average intensity, area, brightness and orientation etc., of the … …American Journal of Applied Sciences, Vol. 15, Issue 1 · 7 Feb 2018 · 7,552 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Soft Sensor Modelling of Biomass Concentration during Fermentation using Accurate Incremental Online v-Support Vector Regression Learning AlgorithmBinjie Gu, Feng PanIn order to model real fermentation process, a soft sensor modelling of biomass concentration during fermentation using accurate incremental online ν-Support Vector Regression (ν-SVR) learning algorithm was proposed. Firstly, an accurate incremental online ν-SVR learning algorithm was proposed. This algorithm solved the two complications introduced in the dual problem based on the equivalent formulation of ν-SVR. Moreover, it addressed the … …American Journal of Biochemistry and Biotechnology, Vol. 11, Issue 3 · 8 Aug 2015 · 7,327 accessesView PDFCite
EditorialOpen accessIn the abstractData Mining in Time Series: Current Study and Future TrendTan Yan, Liudmila Ulanova, Ye Ouyang, Fengyuan XuTime series represent sequences of data points where usually their order is defined by the time when they were recorded. Thus, virtually any sequential recordings can be stored as time series: Stock prices, weather conditions, physical system parameters change, product quality monitoring, etc. This leads to ubiquity of time series in all scientific and practical fields (Esling and Agon, 2012); … …Journal of Computer Science, Vol. 10, Issue 12 · 26 Jan 2015 · 8,756 accessesView PDFCite
Research ArticleOpen accessIn the abstractPARALLEL IMPLEMENTATION OF EXPECTATION-MAXIMISATION ALGORITHM FOR THE TRAINING OF GAUSSIAN MIXTURE MODELSG. F. Araújo, H. T. Macedo, M. T. Chella et al.Most machine learning algorithms need to handle large data sets. This feature often leads to limitations on processing time and memory. The Expectation-Maximization (EM) is one of such algorithms, which is used to train one of the most commonly used parametric statistical models, the Gaussian Mixture Models (GMM). All steps of the algorithm are potentially parallelizable once they iterate over … …Journal of Computer Science, Vol. 10, Issue 10 · 9 Jul 2014 · 6,937 accessesView PDFCite
Research ArticleOpen accessIn the abstractGENETIC ALGORITHM AND NEURAL NETWORK FOR OPTICAL CHARACTER RECOGNITIONHendy Yeremia, Niko Adrianus Yuwono, Pius Raymond, Widodo BudihartoComputer system has been able to recognize writing as human brain does. The method mostly used for character recognition is the backpropagation network. Backpropagation network has been known for its accuracy because it allows itself to learn and improving itself thus it can achieve higher accuracy. On the other hand, backpropagation was less to be used because of its time … …Journal of Computer Science, Vol. 9, Issue 11 · 19 Sep 2013 · 7,646 accessesView PDFCite
Research ArticleOpen accessIn the abstractSteel Plates Faults Diagnosis with Data Mining ModelsMahmoud Fakhr, Alaa M. ElsayadProblem statement: Over the last two decades, Fault Diagnosis (FD) has a major importance to enhance the quality of manufacturing and to lessen the cost of product testing. Actually, quick and correct FD system helps to keep away from product quality problems and facilitates precautionary maintenance. FD may be considered as a pattern recognition problem. It has been gaining more … …Journal of Computer Science, Vol. 8, Issue 4 · 31 Jan 2012 · 11,378 accessesView PDFCite
Research ArticleOpen accessIn the abstractArtificial Neural Networks Based Red Palm Weevil (Rynchophorus Ferrugineous, Olivier) Recognition SystemSaleh Mufleh Al-Saqer, Ghulam Mubashar HassanProblem statement: The most dangerous insect for the existence of palm trees in entire world is Red Palm Weevil (scientifically named as Rynchophorus Ferrugineous, Oliveir). The proposed research is conducted to develop an identification system for Automated Wireless Red Palm Weevil Detection and exterminated. The core idea of the proposed research is to develop software that can utilize image processing … …American Journal of Agricultural and Biological Sciences, Vol. 6, Issue 3 · 4 Aug 2011 · 9,187 accessesView PDFCite
Research ArticleOpen accessIn the abstractStatistical Analysis and Learning Method on Users' FeedbacksDoris Hooi-Ten Wong, Sureswaran RamadassProblem statement: The purpose of this study was constructing an effective algorithm in order to learn the users’ feedbacks from their displayed visualization. This is due to existing visualization tools typically involve presenting network data regardless of considering level of network data knowledge among different levels of computer users. The machine learning algorithm has been applied in order to find … …Journal of Computer Science, Vol. 7, Issue 9 · 26 Jul 2011 · 6,525 accessesView PDFCite
Research ArticleOpen accessIn the abstractFeature Subset Selection for Hot Method Prediction using Genetic Algorithm wrapped with Support Vector MachinesSandra Johnson, Valli ShanmugamProblem statement: All compilers have simple profiling-based heuristics to identify and predict program hot methods and also to make optimization decisions. The major challenge in the profile-based optimization is addressing the problem of overhead. The aim of this work is to perform feature subset selection using Genetic Algorithms (GA) to improve and refine the machine learnt static hot method predictive … …Journal of Computer Science, Vol. 7, Issue 5 · 7 May 2011 · 7,234 accessesView PDFCite