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389 results for “Prediction Model”
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Research ArticleOpen accessEvery word in the titleComparative Analysis of Deep Learning Models for Multi-Step Prediction of Financial Time SeriesSaugat Aryal, Dheynoshan Nadarajah, Prabath Lakmal Rupasinghe et al.Financial time series prediction has been a key topic of interest among researchers considering the complexity of the domain and also due to its significant impact on a wide range of applications. In contrast to one-step ahead prediction, multi-step forecasting is more desirable in the industry but the task is more challenging. In recent days, advancement in deep learning has … …Journal of Computer Science, Vol. 16, Issue 10 · 27 Oct 2020 · 6,967 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAnalysis of Artificial Neural Network Point Forecasting Models and Prediction Intervals for Solar Irradiance EstimationAntônio Fabrício Guimarães de Sousa, Helaine Cristina Moraes Furtado, Wilson Negrão Macêdo, Anderson Alvarenga de Moura MenesesAn accurate knowledge on solar irradiance prediction is particularly required for proper development and planning of Photovoltaic (PV) energy systems. The main purpose of the present research is to assess the accuracy of Artificial Neural Networks (ANN) short-term forecast of univariate solar irradiance time series, with conventional point prediction and Prediction Intervals (PIs), comparing models. The Lower Upper Bound Estimation … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 3 · 17 Jul 2020 · 7,440 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePrediction of Covid-19 Outbreak in India by Employing Epidemiological ModelsSudheer Reddy K, Anji Reddy V, Mamatha K, Santhosh Kumar CThe novel Corona virus (Covid-19) pandemic has frightened an unprecedented challenge to continents. The Covid-19 pandemic is a highly contagious viral disease that has been progressing across the globe. The global thought leaders, doctors, scientists and other intellects have enforced the lockdown to reduce the spread of the pandemic. The objective is to study the impact of lockdown and to … …Journal of Computer Science, Vol. 16, Issue 7 · 10 Jul 2020 · 6,903 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleModel Comparison for the Prediction of Stock Prices in the NYSEVictoria Switlyk, Junfeng ShangThe stock market is an integral part of investments as well as the economy. The prediction of stock prices is an exciting and challenging problem that has been considered by many due to the complexity and noise within the market and to the potential profit that can be yielded from accurate predictions. We aim to construct and compare models used … …Journal of Mathematics and Statistics, Vol. 15, Issue 1 · 26 Sep 2019 · 7,475 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleIntegrated Multiple Linear Regression-One Rule Classification Model for the Prediction of Stock Price TrendLock Siew Han, Md Jan NordinOne of the main problems of predicting stock price with regression approach is overfitting a model. An overfit model becomes tailored to fit the random noise in the dataset rather than reflecting the overall population. For this it is necessary to construct an integrated regression-classification model to approximate the true model for the entire population in the dataset. The proposed … …Journal of Computer Science, Vol. 13, Issue 9 · 18 May 2017 · 7,422 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePerformance of Hybrid GANN in Comparison with Other Standalone Models on Dengue Outbreak PredictionNor Azura Husin, Norwati Mustapha, Md. Nasir Sulaiman et al.Early prediction of diseases especially dengue fever in the case of Malaysia, is very crucial to enable health authorities to develop response strategies and context preventive intervention programs such as awareness campaigns for the high risk population before an outbreak occurs. Some of the deficiencies in dengue epidemiology are insufficient awareness on the parameter as well as the combination among … …Journal of Computer Science, Vol. 12, Issue 6 · 2 Jul 2016 · 8,162 accessesView PDFCite
InvestigationOpen accessEvery word in the titleBackpropagation Vs. Radial Basis Function Neural Model: Rainfall Intensity Classification For Flood Prediction Using Meteorology DataSoo See Chai, Wei Keat Wong, Kok Luong GohRainfall is one of the important weather variables that vary in space and time. High mean daily rainfall (>30 mm) has a high possibility of resulting in flood. Accurate prediction of this variable would save human lives and properties. Soft computing methods have been widely applied in this field. Among the various soft computing methods, Artificial Neural Network (ANN) is … …Journal of Computer Science, Vol. 12, Issue 4 · 15 Apr 2016 · 8,705 accessesView PDFCite
Research ArticleOpen accessEvery word in the titlePrediction of the Daily Mean PM10 Concentrations Using Linear ModelsJ. C.M. Pires, F. G. Martins, S. I.V. Sousa et al.The performance of five linear models to predict the daily mean PM10 concentrations was compared. The linear models proposed were: (i) multiple linear regression; (ii) principal component regression; (iii) independent component regression; (iv) quantile regression; and (v) partial least squares regression. The study was based on data from an urban site in Oporto Metropolitan Area and the analysed period was … …American Journal of Environmental Sciences, Vol. 4, Issue 5 · 31 Oct 2008 · 7,132 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEarth-To-Space Improved Model for Rain Attenuation Prediction at Ku-BandMandeep Singh Jit Singh, S. S.I. Hassan, M. F. Ain et al.A model for predicting rain attenuation on earth-to-space was developed by using the measurement data obtained from tropical and equatorial region. The proposed rain attenuation model uses the complete rainfall rate cumulative distribution as input data. It was shown that significant improvements in terms of prediction error over existing attenuation model obtained. …American Journal of Applied Sciences, Vol. 3, Issue 8 · 31 Aug 2006 · 6,725 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHybrid Hot Strip Rolling Force Prediction using a Bayesian Trained Artificial Neural Network and Analytical ModelsAbdelkrim Moussaoui, Yacine Selaimia, Hadj A. AbbassiThe authors discuss the combination of an Artificial Neural Network (ANN) with analytical models to improve the performance of the prediction model of finishing rolling force in hot strip rolling mill process. The suggested model was implemented using Bayesian Evidence based training algorithm. It was found that the Bayesian Evidence based approach provided a superior and smoother fit to the … …American Journal of Applied Sciences, Vol. 3, Issue 6 · 30 Jun 2006 · 7,135 accessesView PDFCite