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152 results for “series time data”
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Review ArticleOpen accessIn the abstractThe Impact of Di-2-Ethylhexyl Phthalate (DEHP) in Focus on the Reproductive System and Toxicity in Rat or Mammalian ModelVenkataramanaiah Poli, Srinivasulu Reddy MotireddyAbsalan, F., Saremy, S., Mansouri, E., Moghadam, M. T., Moghadam, A. R. E., & Razie, G. (2016). Effects of Mono-(2-Ethylhexyl) Phthalate and Di-(2-Ethylhexyl) Phthalate Administrations on Oocyte Meiotic Maturation, Apoptosis and Gene Quantification in Mouse Model. Cell Journal, 18(4), 503–513. https://doi.org/10.22074/cellj.2016.4717 Acevedo‐Rodriguez, A., Kauffman, A. S., Cherrington, B. D., Borges, C. S., Roepke, T. A., & Laconi, M. (2018). Emerging … …American Journal of Pharmacology and Toxicology, Vol. 19, Issue 1 · 6 Jun 2024 · 12,990 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Context-Aware Temporal Convolutional Network for Water Replacement Prediction in Catfish Biofloc Ponds With Imbalanced Event HandlingYaddarabullah, Inanpi Hidayati Sumiasih, Mutiara Dewi PuspitawatiWater replacement is a biologically critical yet under-automated decision in biofloc-based aquaculture systems. Mistimed actions can destabilize microbial ecosystems, elevate fish mortality, and compromise sustainability through excessive water usage. Traditional rule-based heuristics often fail to account for the nonlinear and multiscale dynamics of pond environments. To address this, we propose a Context-Aware Temporal Convolutional Network (CA-TCN), a rare-event classification framework … …Journal of Computer Science, Vol. 22, Issue 3 · 5 Mar 2026 · 1,664 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Empirical Investigation of the Pollution Haven-Halo Nexus in Eastern and Southern AfricaPaul KauluThis study looks into the relationship between trade and pollution in Eastern and Southern Africa from 1977 to 2016. This timeframe is particularly relevant as it was marked by rising CO₂ emissions despite major climate agreements such as the Kyoto Protocol (1997), Reducing Emissions from Deforestation and Forest Degradation (REDD+, 2007), as well as the Paris Agreement (2015). Using time-series … …American Journal of Environmental Sciences, Vol. 21, Issue 1 · 28 Jan 2026 · 2,917 accessesView PDFCite
Research ArticleOpen accessIn the abstractAssociation Between Particulate Matter (PM10) Exposure and Cardiorespiratory Hospital Admissions: A Time Series AnalysisNur Nabila Abd Rahim, Abqariyah Yahya, Wan Rozita Wan MahiyuddinThis study aimed to evaluate the association between particulate matter (PM10) exposure and cardiorespiratory hospital admissions and develop a time series model for cardiorespiratory hospital admissions in Johor, Malaysia. Retrospective time series analysis was utilised to study cardiorespiratory hospital admissions for the study period 2015-2016. Over-dispersed Poisson generalized linear models with parametric smoothing functions were used to examine the association … …American Journal of Environmental Sciences, Vol. 17, Issue 2 · 27 May 2021 · 6,917 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Support and Resistance Indicators for Stock Market with Fibonacci Sequence in Long Short-Term MemoryThambusamy Velmurugan, Thiruvalluvan IndhumathyPredictive data analytics is a branch of data analytics where models are designed that effectively interpret; anticipate outcomes by analyzing present data to make predictions about future. One of the major attributes for prediction is time and there have been a considerable number of time series analytical models that are used for forecasting. Long Short-Term Memory (LSTM) is a deep … …Journal of Computer Science, Vol. 16, Issue 10 · 28 Oct 2020 · 7,316 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative 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 accessIn the abstractA Time Series Forecasting for the Cumulative Confirmed and Critical Cases of the Covid-19 Pandemic in Saudi Arabia using Autoregressive Integrated Moving Average (ARIMA) ModelSamer H. Atawneh, Osamah A.M. Ghaleb, Ahmad MohdAziz Hussein et al.Reviews at present, different machine learning techniques and algorithms have been applied for predicting significant factors of the Coronavirus Disease-2019 (COVID-19) such as the outbreak and diagnosis. In this study, the most accurate time series forecasting model, namely, the Autoregressive Integrated Moving Average (ARIMA) model is used to forecast the expected cumulative number of confirmed and critical cases in Saudi … …Journal of Computer Science, Vol. 16, Issue 9 · 30 Sep 2020 · 7,596 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalysis 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 accessIn the abstractLand-Cover Removal and Gully Development in Southeast Nigeria: A 30-Year Analysis with Pixel and OBIA Approaches in JuxtapositionSylvanus IroIn this study a study of gully erosion in southeast Nigeria is presented. The study of gully development on a regional scale is currently undermined by the inherent costs associated with consistent field monitoring and the lack of historic measurements to perform time series analysis. As a result, there are very few studies which implement long term analyses of gullies … …American Journal of Environmental Sciences, Vol. 16, Issue 2 · 9 Jun 2020 · 7,383 accessesView PDFCite
Research ArticleOpen accessIn the abstractDoes Monetary Policy Stimulates Macroeconomic Performance during Economic Downturn in Nigeria?Bashir Adelowo Wahab, Sam-Siso Ebasi OkrinyaThis study investigated the relationship between monetary policy and macroeconomic performance in Nigeria during 1981-2018. The stochastic properties of the time series data were examined using both conventional and unit root tests with structural breaks to account for shift dummy in the series. Their results indicates that the series are combination of both I(0) and I(1) in the same specification … …Journal of Social Sciences, Vol. 16, Issue 1 · 11 Feb 2020 · 8,269 accessesView PDFCite