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150 articles for “Time Series Data”
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Research ArticleOpen accessIn the abstractForecasting Model of Corn Commodity Production in Indonesia: Production and Operation Management-Quantitative Method (POM-QM) SoftwareAsriani, Dhian Herdhiansyah, Wa Embe, LM Fid AksaraFood is essential for humans. In addition to being consumed, it can also be a valuable commodity for economic purposes through the production of food crops. Therefore, this study aims to model the forecasting of maize production in Indonesia using Production and Operations Management-Quantitative Method (POM-QM) software. The uniqueness of this research lies in its innovative approach to predicting corn … …Journal of Computer Science, Vol. 20, Issue 4 · 20 Feb 2024 · 6,153 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn 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 · 1,754 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Models for Predicting Stock Closing Prices in the Saudi Stock MarketAreej Alhumaidi, Hoda A. AbdelhafezFinancial time series data are inherently volatile and nonlinear, presenting considerable challenges in accurately forecasting stock market trends. This study aims to predict the closing prices of companies listed on the Saudi stock market by analyzing historical data spanning from 2013 to 2023. To this end, four deep learning models were employed-Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), Gated Recurrent … …Journal of Computer Science, Vol. 22, Issue 4 · 22 Apr 2026 · 1,363 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting of Multistep Multivariate Financial Data Through GSO Algorithm Infused Vanilla LSTM ModelNikhitha Pai, Ilango Velchamy, Nithya B RameshPredicting time series in the financial domain requires using models that can do sequence processing tasks. One such model is the LSTM model which belongs to the family of deep learning networks. The performance measure of LSTM in a regression task is to bring down the error in the predicted values. In this study, a novel fused LSTM model integrating … …Journal of Computer Science, Vol. 19, Issue 7 · 10 Jul 2023 · 6,077 accessesView PDFCite
Research ArticleOpen accessIn the abstractDiscrete to Continuous Algorithm for Optimal Channel Selection to Detect Alcoholism through EEG RecordingsHayat Sedrati, Wajih Rhalem et al.Alcoholism is a serious public health issue, and early diagnosis of this brain disease can be performed by analyzing Electroencephalogram (EEG) signals. However, the high dimensionality of EEG datasets requires significant computational time and resources for the automatic processing of EEG signals. This study proposes a novel method to reduce EEG dataset dimensionality using a Discrete to Continuous algorithm (DtC) … …Journal of Computer Science, Vol. 19, Issue 1 · 17 Jan 2023 · 5,908 accessesView PDFCite
Review ArticleOpen accessIn the abstractRRDTool: A Round Robin Database for Network MonitoringManmohan Singh, Sweta Dargada, Hemant Mewada et al.RRDtool is a circular database that stores time series data. RRD tool assumes time-variable data inintervals of a certain length. An interval is named as a step, and specifiedupon creation of an RRD file which cannot be changed afterward. Because datamay not always come at just the right time, RRD tool will automaticallyinterpolate any submitted data. This is done to … …Journal of Computer Science, Vol. 18, Issue 8 · 27 Aug 2022 · 8,361 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Fuzzy Clustering Based Method for the Spatio-Temporal Data AnalysisAnahita Zolghadr, Afsaneh JalalianSpatiotemporal data is a type of data that is collected by the sensors. This type of data has two spatial and temporal dimensions. There are many challenges in analyzing spatiotemporal big data. Common evaluation metrics of clustering methods are not appropriate for spatiotemporal data. Previous clustering methods and the conventional evaluation metrics are efficient for data like time series with … …Journal of Computer Science, Vol. 18, Issue 6 · 13 Jun 2022 · 5,641 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Synergy: CNNs and Transformers for Epidemic Outbreak ForecastingAlexander R., Shakthi Priya V., Sumathi G. et al.An Accurate prediction of outbreaks is extremely crucial for taking proactive public health interventions, distributing limited resources, and controlling a disease. This paper assesses and also compares the performances of the available deep learning models, namely, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) networks, and Bidirectional Long Short-Term Memory (BiLSTM) networks, in predicting. CNNs are best for feature extraction … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,120 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 · 6,921 accessesView PDFCite
Research ArticleOpen accessIn the abstractDynamic Relationship Between Rupee-Dollar Exchange Rate and Major Economic IndicatorsAbhinandan Kulal, Deepak Kallige Vishwanath, Sanath Kumar KanthilaIt is very likely that dollar to rupee exchange rate has an influence on the major economic indicators of India like the GDP of India, the NIFTY 50 index, gold prices in India, import prices in India, and crude oil prices in India. The quarterly time series data of the seven variables have been used. The time considered for the … …American Journal of Economics and Business Administration, Vol. 15, Issue 1 · 17 Aug 2023 · 6,454 accessesView PDFCite