8 articles for “Prediction Intervals”

Set a search alert

Research ArticleOpen accessPhrase 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 PDF Cite

Research ArticleOpen accessPhrase in the titlePrediction Intervals for Future Observations Based on Samples of Random SizesMohammad Z. Raqab, Haroon M. BarakatOn the basis of failure times of an informative sample (X-sample) of random size M of iid continuous random variables, we consider the prediction problem of failure times of another independent future sample (Y-sample) of random size N of iid variables from the same distribution. In this paper, we derive various exact prediction intervals for future failure times from the … …Journal of Mathematics and Statistics, Vol. 14, Issue 1 · 2 Jan 2018 · 7,902 accessesView PDF Cite

Research ArticleOpen accessIn the abstractDynamic Knowledge Driven Multi-Scale Spatiotemporal Fusion Framework for Reliable Multi-Horizon Traffic Flow ForecastingDeepika M S, P. Deepa Shenoy, Venugopal K RAccurate traffic flow forecasting remains a core challenge in intelligent transportation systems. Urban traffic patterns are characterised by complex spatiotemporal dependencies and inherent uncertainties, which complicate traffic forecasting. This study proposes a Dynamic Knowledge-Driven Spatiotemporal Fusion (DKDMSF) architecture to extract features of Multi-Scale traffic dynamics across various temporal traffic horizons. DKDMSF integrates Dynamic Spatial Attention (DSA) and Adaptive Graph Learning … …Journal of Computer Science, Vol. 22, Issue 9 · 30 Sep 2026 · 413 accessesView PDF Cite

Research ArticleOpen accessIn the abstractStatistical Tool for Testing Agreement Level on Continuous DatasetsBasavarajaiah Mariyappa Doddagangavadi, B. Narasimha Murthy, Netra RajpurohitVarious analytical studies explored the new innovation for testing agreement level in medical and life sciences which can be simulated by Cohen ‘κ’ based on the practical applications. From the past medical literature, many authors suggested that, there is some disproportion research gaps that exists in the statistical methods for measuring the agreements between two or more observers from ‘Cohen … …Current Research in Biostatistics, Vol. 11, Issue 1 · 19 May 2021 · 11,780 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAn Adaptive Assessment and Prediction Mechanism in Network Security Situation AwarenessYu-Beng Leau, Ali Abdulrazzaq Khudher, Selvakumar Manickam, Samer Al-SalemNetwork intrusion attempts have reached an alarming level. Cisco's 2014 Security Report indicated that 50,000 network intrusions were detected and 80 million suspicious web requests were blocked daily. Hence, Intrusion Prevention System (IPS) had been chosen as a defence mechanism in many organizations. However, the University of South Wales reported that seven big-brand IPS had failed to detect and block … …Journal of Computer Science, Vol. 13, Issue 5 · 22 May 2017 · 8,349 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordAn Intelligent Hybrid Machine Learning Model for Paddy Disease DetectionS. Hrushikesava Raju, S. Adinarayna, U. Sesadri et al.Most countries rely on paddy/rice as a preferred staple crop due to its desirable agronomic characteristics. However, during the growth cycle, undetected or delayed identification of diseases can significantly reduce crop yield. To address this, machine learning approaches are increasingly employed for early-stage disease detection. Traditional Recurrent Neural Networks (RNNs), while useful for sequential data, suffer from limitations such as … …Journal of Computer Science, Vol. 22, Issue 4 · 29 Apr 2026 · 1,747 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordStatistical Inferences of the Rest Lifetimes of Ball Bearings' Residual Lifetimes Based on Rayleigh Residual Type II Censored DataGhassan K. Abufoudeh, Omar M. Bdair, Raed R. Abu AwwadIn this study, we consider statistical inference problems for the residual life data that come from the Rayleigh model based on type II censored data. Maximum likelihood and Bayesian approaches are used to estimate the scale and location parameters for the Rayleigh model, the Gibbs sampling procedure is used to draw Markov Chain Monte Carlo (MCMC) samples and MCMC samples … …Journal of Mathematics and Statistics, Vol. 12, Issue 3 · 1 Aug 2016 · 7,161 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordSurface Roughness Prediction Model in Machining of Carbon Steel by PCD Coated Cutting ToolsYusuf Sahin, A. Riza MotorcuThe surface roughness model in the turning of AISI 1040 carbon steel was developed in terms of cutting speed, feed rate and depth of cut using response surface methodology. Machining tests were carried out using PVD-coated tools under different cutting conditions. The surface roughness equations of cutting tools when machining the carbon steels were achieved by using the experimental data. … …American Journal of Applied Sciences, Vol. 1, Issue 1 · 31 Mar 2004 · 7,964 accessesView PDF Cite