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Academic literature on the topic 'SARIMA model'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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Journal articles on the topic "SARIMA model"

Ibrahim, A., and A. O. Musa. "ON THE PERFORMANCE OF SARIMA AND SARIMAX MODEL IN FORECASTING MONTHLY AVERAGE RAINFALL IN KOGI STATE, NIGERIA." FUDMA JOURNAL OF SCIENCES 7, no. 6 (2023): 24–31. http://dx.doi.org/10.33003/fjs-2023-0706-2095.

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Forecasting monthly rainfall is very important in Kogi state for better approach to flood management and also plays a pivotal role in agriculture which remains a significant factor in Nigeria’s economy. Advanced time series univariate models such as Seasonal Autoregressive Integrated Moving Average (SARIMA) models are usually employed in modelling and forecasting rainfall in Nigeria due to their non-linear pattern and spatiotemporal variation. Few studies have attempted to investigate the influence of other climatic factors in modelling and prediction of rainfall pattern. This study examines t

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Permata, Regita Putri, and Ananda Taqhsya Dwiyana. "Comparison of NAIVE, SARIMA, and SARIMAX Models in Short-Term and Long-Term Forecasting of Google Search Trends." International Journal of Scientific Research in Computer Science and Engineering 13, no. 2 (2025): 21–29. https://doi.org/10.26438/ijsrcse.v13i2.665.

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This study examines forecasting methods—Naïve, SARIMA, and SARIMAX—to enhance the accuracy of Google search trend predictions in the fitness industry, specifically for the keyword "Gym." The Naïve method serves as a baseline comparison, SARIMA incorporates seasonal, autoregressive, and moving average components for improved trend detection, while SARIMAX extends SARIMA by integrating exogenous variables. Historical Google search data from 2005 to 2015 is used for model evaluation, with performance assessed using MAE, RMSE, and MAPE metrics. The findings indicate that SARIMAX, which accounts fo

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Woro Tri Handayani, Nandia Rani, Martinus Maslim, and Paulus Mudjihartono. "Forecasting of Catfish Sales by Time Series Using the SARIMA method." Jurnal Buana Informatika 11, no. 2 (2020): 83. http://dx.doi.org/10.24002/jbi.v11i2.3535.

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Abstrak. Sistem informasi yang mengotomatiskan proses bisnis, terutama dengan persyaratan khusus masih relevan saat ini. Clarias Makmur, sebuah usaha mikro di Indonesia yang membiakkan dan menjual ikan lele menggunakan sistem informasi ini untuk menjalankan penjualan, pengeluaran, modal, dan pelaporan mereka. Penjualan ikan lele sebagai makhluk hidup memiliki ciri khas tersendiri yang menunjukkan pola musiman yang unik. Sebuah model bernama SARIMA (Seasonal Autoregressive Integrated Moving Average) kemudian diusulkan untuk memprediksi penjualan. Lebih lanjut, sistem yang disebut SITRAN dibuat

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Costa, Gabriela Emiliana de Melo e., Frederico Carlos M. de Menezes Filho, Fausto A. Canales, Maria Clara Fava, Abderraman R. Amorim Brandão, and Rafael Pedrollo de Paes. "Assessment of Time Series Models for Mean Discharge Modeling and Forecasting in a Sub-Basin of the Paranaíba River, Brazil." Hydrology 10, no. 11 (2023): 208. http://dx.doi.org/10.3390/hydrology10110208.

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Stochastic modeling to forecast hydrological variables under changing climatic conditions is essential for water resource management and adaptation planning. This study explores the applicability of stochastic models, specifically SARIMA and SARIMAX, to forecast monthly average river discharge in a sub-basin of the Paranaíba River near Patos de Minas, MG, Brazil. The Paranaíba River is a vital water source for the Alto Paranaíba region, serving industrial supply, drinking water effluent dilution for urban communities, agriculture, fishing, and tourism. The study evaluates the performance of SA

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Permatasari, Novia. "Penggunaan Indeks Google Trend Dalam Peramalan Jumlah Pengunjung Taman Rekreasi Selecta Tahun 2020." Seminar Nasional Official Statistics 2021, no. 1 (2021): 1019–24. http://dx.doi.org/10.34123/semnasoffstat.v2021i1.993.

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Kota Batu merupakan salah satu daerah potensi pariwisata di Indonesia, dengan salah satu tujuan pariwisata andalan adalah Taman Rekreasi Selecta. Sejak tahun 2016 hingga 2019, Taman Rekreasi Selecta secara konsisten menjadi tempat wisata dengan jumlah pengunjung terbanyak di Kota Batu. Publikasi data kunjungan wisatawan yang hanya dilakukan sekali dalam satu tahun menunjukkan adanya selang waktu antara pengumpulan dan publikasi data, sehingga pemanfaatan data kunjungan wisatawan tersebut kurang maksimal. Permasalahan tersebut dapat diatasi dengan memanfaatkan real-tima data, yaitu big data. Pa

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Rochayati, Isti, Utami Dyah Syafitri, I. Made Sumertajaya, and Indonesian Journal of Statistics and Its Applications IJSA. "KAJIAN MODEL PERAMALAN KUNJUNGAN WISATAWAN MANCANEGARA DI BANDARA KUALANAMU MEDAN TANPA DAN DENGAN KOVARIAT." Indonesian Journal of Statistics and Its Applications 3, no. 1 (2019): 18–32. http://dx.doi.org/10.29244/ijsa.v3i1.171.

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Foreign tourist arrivals could be considered as time series data. Modelling these data could make use of internal and external factors. The techniques employed here to model these time series data are SARIMA, SARIMAX, VARIMA, and VARIMAX. SARIMA is a model for seasonal data and VARIMA is a model for multivariate time series data. If some explanatory variables are incorporated and have significant influence on the response, the former two models become SARIMAX and VARIMAX respectively. Three stages of creating the model are model identification, parameter estimation, and model diagnostics. The

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Amelia, Ririn, Elyas Kustiawan, Ineu Sulistiana, and Desy Yuliana Dalimunthe. "FORECASTING RAINFALL IN PANGKALPINANG CITY USING SEASONAL AUTOREGRESSIVE INTEGRATED MOVING AVERAGE WITH EXOGENOUS (SARIMAX)." BAREKENG: Jurnal Ilmu Matematika dan Terapan 16, no. 1 (2022): 137–46. http://dx.doi.org/10.30598/barekengvol16iss1pp137-146.

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Changes in extreme rainfall can cause disasters or losses for the wider community, so information about future rainfall is also needed. Rainfall is included in the category of time series data. One of the time series methods that can be used is Autoregressive Integrated Moving Average (ARIMA) or Seasonal ARIMA (SARIMA). However, this model only involves one variable without involving its dependence on other variables. One of the factors that can affect rainfall is wind speed which can affect the formation of convective clouds. In this study, the ARIMA model was expanded by adding eXogen variab

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Chutiman, Nipaporn, Pannarat Guayjarernpanishk, Monchaya Chiangpradit, Piyapatr Busababodhin, Saowanee Rattanawan, and Butsakorn Kong-Led. "The Forecasting Model with Climate Variables of the Re-emerging Disease Rate in Elderly Patients." WSEAS TRANSACTIONS ON ENVIRONMENT AND DEVELOPMENT 17 (August 4, 2021): 866–75. http://dx.doi.org/10.37394/232015.2021.17.81.

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This research forecasted the incidence rate per 100,000 elderly population with food poisoning, pneumonia, and fever of unknown origin in Khon Kaen Province and Roi Et Province in the northeastern part of Thailand. In the study, the time series forecasting with Box-Jenkins Method (SARIMA model) and Box-Jenkins Method with climate variables, i.e total monthly rainfall, maximum average monthly temperature, average relative humidity, minimum average monthly temperature and average temperature (SARIMAX model) was performed. The study results revealed that the forecasting accuracy was closely simil

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Kadek, Jemmy Waciko, and B. Ismail. "SARIMA-ELM Hybrid Model for Forecasting Tourist in Nepal." RESEARCH REVIEW International Journal of Multidisciplinary 03, no. 07 (2018): 343–49. https://doi.org/10.5281/zenodo.1318551.

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In this study a novel hybrid model has been developed to forecasting tourist arrivals. The main concept is to combine two different forecasting techniques such as SARIMA and Extreme Learning Machine models to produce a new SARIMA-ELM hybrid Model, so as to achieve accuracy in forecasting. Forecasting accuracy for SARIMA, Triple Exponential Smoothing (The Holt-Winter’s), Multi Layer Perceptron-Neural Networks (MLP-NN), Extreme Learning Machine (ELM) and SARIMA-ELM hybrid models are computed and compared using criteria like RMSE, MAE, and MAPE. Empirical analysis found that SARIMA-ELM hybr

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Yadav, Baikunth Kumar, Sunil Kumar Srivastava, Ponnusamy Thillai Arasu, and Pranveer Singh. "Time Series Modeling of Tuberculosis Cases in India from 2017 to 2022 Based on the SARIMA-NNAR Hybrid Model." Canadian Journal of Infectious Diseases and Medical Microbiology 2023 (December 16, 2023): 1–9. http://dx.doi.org/10.1155/2023/5934552.

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Tuberculosis (TB) is still one of the severe progressive threats in developing countries. There are some limitations to social and economic development among developing nations. The present study forecasts the notified prevalence of TB based on seasonality and trend by applying the SARIMA-NNAR hybrid model. The NIKSHAY database repository provides monthly informed TB cases (2017 to 2022) in India. A time series model was constructed based on the seasonal autoregressive integrated moving averages (SARIMA), neural network autoregressive (NNAR), and, SARIM-NNAR hybrid models. These models were es

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Dissertations / Theses on the topic "SARIMA model"

Li, Yangyang M. Eng Massachusetts Institute of Technology. "New product forecasting of appliance and consumables : SARIMA model." Thesis, Massachusetts Institute of Technology, 2018. https://hdl.handle.net/1721.1/132738.

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Thesis: M. Eng. in Advanced Manufacturing and Design, Massachusetts Institute of Technology, Department of Mechanical Engineering, September, 2018 Cataloged from the PDF version of thesis. Includes bibliographical references (pages 43-44). Drinkworks is a joint venture between Anheuser-Busch InBev and Keurig Green Mountain, with a focus on developing an in-home alcohol system that can prepare different alcoholic beverages. The goal of this project is to forecast the demand for their new product, consisting of appliance and pods, without historical data. For appliance forecast, this pa

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Nikolaisen, Sävås Fredrik. "Forecast Comparison of Models Based on SARIMA and the Kalman Filter for Inflation." Thesis, Uppsala universitet, Statistiska institutionen, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-202204.

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Inflation is one of the most important macroeconomic variables. It is vital that policy makers receive accurate forecasts of inflation so that they can adjust their monetary policy to attain stability in the economy which has been shown to lead to economic growth. The purpose of this study is to model inflation and evaluate if applying the Kalman filter to SARIMA models lead to higher forecast accuracy compared to just using the SARIMA model. The Box-Jenkins approach to SARIMA modelling is used to obtain well-fitted SARIMA models and then to use a subset of observations to estimate a SARIMA mo

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Jantoš, Milan. "Modelovanie a predpovedanie sezónnych časových radov." Master's thesis, Vysoká škola ekonomická v Praze, 2016. http://www.nusl.cz/ntk/nusl-264619.

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In this Master Thesis there are summarized basic methods for modelling time series, such as linear regression with seasonal dummy variables, exponential smoothing and SARIMA processes. The thesis is aimed on modelling and forecasting seasonal time series using these methods. Goals of the Thesis are to introduce and compare these methods using a set of 2184 seasonal time series followed by evaluation their prediction abilities. The main benefit of this Master Thesis is understanding of different aspects of forecasting time series and empirical verification of advantages and disadvantages these

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AIDOO, ERIC. "Forecast Performance Between SARIMA and SETAR Models: An Application to Ghana Inflation Rate." Thesis, Uppsala universitet, Statistiska institutionen, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-154339.

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In recent years, many research works such as Tiao and Tsay (1994), Stock and Watson (1999), Chen et al. (2001), Clements and Jeremy (2001), Marcellino (2002), Laurini and Vieira (2005) and others have described the dynamic features of many macroeconomic variables as nonlinear. Using the approach of Keenan (1985) and Tsay (1989) this study shown that Ghana inflation rates from January 1980 to December 2009 follow a threshold nonlinear process. In order to take into account the nonlinearity in the inflation rates we then apply a two regime nonlinear SETAR model to the inflation rates and then s

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AIDOO, ERIC. "MODELLING AND FORECASTING INFLATION RATES IN GHANA: AN APPLICATION OF SARIMA MODELS." Thesis, Högskolan Dalarna, Statistik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:du-4828.

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Ghana faces a macroeconomic problem of inflation for a long period of time. The problem in somehow slows the economic growth in this country. As we all know, inflation is one of the major economic challenges facing most countries in the world especially those in African including Ghana. Therefore, forecasting inflation rates in Ghana becomes very important for its government to design economic strategies or effective monetary policies to combat any unexpected high inflation in this country. This paper studies seasonal autoregressive integrated moving average model to forecast inflation rates i

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SILVA, Pollyanna Kelly de Oliveira. "Análise e previsão de curto prazo do vento através de modelagem estatística em áreas de potencial eólico no nordeste do Brasil." Universidade Federal de Campina Grande, 2017. http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/1414.

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Submitted by Maria Medeiros (maria.dilva1@ufcg.edu.br) on 2018-08-13T15:28:50Z No. of bitstreams: 1 POLLYANNA KELLY DE OLIVEIRA SILVA - TESE (PPGMet) 2017.pdf: 11004478 bytes, checksum: 0d5e098181f432beffc2fd8155027f1e (MD5) Made available in DSpace on 2018-08-13T15:28:50Z (GMT). No. of bitstreams: 1 POLLYANNA KELLY DE OLIVEIRA SILVA - TESE (PPGMet) 2017.pdf: 11004478 bytes, checksum: 0d5e098181f432beffc2fd8155027f1e (MD5) Previous issue date: 2017-08-30 CNPq O vento como fonte para geração de energia elétrica é analisado neste trabalho através de sua variabilidade e da obtenção de

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Han, Jianfeng, and 韩剑峰. "Comparing the performance of SARIMA and dynamic linear model in forecasting monthly cases of mumps in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hdl.handle.net/10722/193789.

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Background To provide a reliable forecast of a disease is one of the main purpose of public health surveillance system. Basic information obtained from data collection can provide the nature knowledge of and the history pattern of a disease. In public health surveillance system, a lot of data are time series, especially for infectious diseases. SARIMA method and DLM method are both applicable tools for time series data analysis. Hong Kong has a relative low mumps prevalence. And the prevalence followed an increasing trend until 2004and kept stable after 2006. However, outbreaks may be also

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Helman, Karel. "Statistická analýza teplotních a srážkových časových řad v České republice v období 1961 - 2008." Doctoral thesis, Vysoká škola ekonomická v Praze, 2005. http://www.nusl.cz/ntk/nusl-96401.

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The present dissertation deals with an analysis of monthly time series of average temperatures and precipitation sums recorded at 44 sites in the Czech Republic over the period of 1961--2008. The main research purpose is to acquire deeper knowledge of regularities in the climatic time series development, using an appropriate set of statistical methods. A secondary objective is to search and find correlations between the research outcomes and basic geographic coordinates (altitude, longitude and latitude) of particular measurement stations and comparing all the results achieved for the selected

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Robertson, Fredrik, and Max Wallin. "Forecasting monthly air passenger flows from Sweden : Evaluating forecast performance using the Airline model as benchmark." Thesis, Uppsala universitet, Statistiska institutionen, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-242764.

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In this paper two different models for forecasting the number of monthly departing passengers from Sweden to any international destination are developed and compared. The Swedish transport agency produces forecasts on a yearly basis, where net export is the only explanatory variable controlled for in the latest report. More profound studies have shown a relevance of controlling for variables such as unemployment rate, oil price and exchange rates. Due to the high seasonality within passenger flows, these forecasts are based on monthly or quarterly data. This paper shows that a seasonal autoreg

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Norambuena, Ortega Ramón Simón Andrés. "Predicción de Corto Plazo de Potencia Generada en un Aerogenerador Usando Modelo Sarima." Tesis, Universidad de Chile, 2011. http://www.repositorio.uchile.cl/handle/2250/104196.

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El aumento del aporte energético por parte de las centrales eólicas dentro de la matriz de energías renovables no convencionales de Chile, crea la imperiosa necesidad de desarrollar herramientas que ayuden a gestionar el funcionamiento de parques eólicos, y en particular de los aerogeneradores que lo componen, con el fin de hacer más eficiente la integración y manejo en el sistema interconectado. En esta línea, el propósito de este trabajo es desarrollar un modelo predictivo para la potencia generada en un aerogenerador en base a series de tiempo históricas de variables atmosféricas del lugar

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Books on the topic "SARIMA model"

Daerah, Jawa Tengah (Indonesia) Badan Koordinasi Penanaman Modal. Profil penanaman modal SDA dan sarana prasarana. Badan Penanaman Modal, Propinsi Jawa Tengah, 2003.

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Anwar, Yusuf. Pasar modal sebagai sarana pembiayaan dan investasi. Alumni, 2005.

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Sutedi, Adrian. Pasar modal syariah: Sarana investasi keuangan berdasarkan prinsip syariah. Sinar Grafika, 2011.

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Indonesia. Bagian Proyek Sistem Indikator Mutu Sekolah Dasar dan Madrasah Ibtidaiyah. Model kebutuhan sarana-prasarana sekolah dasar dan madrasah ibtidaiyah (SD-MI) nasional tahun 1995/1996. Departemen Pendidikan dan Kebudayaan, Badan Penelitian dan Pengembangan Pendidikan dan Kebudayaan, Pusat Informatika, 1995.

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Andayani, Tri Rejeki. Strategi pengembangan living values education melalui model pembelajaran nilai toleransi berbasis budaya "tepa sarira" pada anak usia sekolah dasar: Suatu alternatif pendidikan karakter : integrasi nasional dan harmoni sosial = nation integration & social harmony : laporan pelaksanaan hibah kompetitif penelitian strategis nasional. Universitas Sebelas Maret, 2010.

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BP, Mitra Usaha Indonesia, ed. Panduan pengembangan materi pembelajaran dan standar sarana dan prasarana sekolah menengah kejuruan: Madrasah aliyah, SMA/MA/SMK/MAK : dilengkapi pengembangan program muatan lokal, sistem penilaian KTSP panduan penyelenggaraan pembelajaran pengayaan, sistem penilaian KTSP panduan penyelenggaraan pembelajaran remedial, sistem penilaian KTSP panduan penyelenggaraan pembelajaran tuntas (mastery learning), pengembangan model pembelajaran tatap muka, penugasan restruktur dan tugas mandiri tidak restruktur, panduan pengembangan bahan ajar, panduan pengembangan indikator, panduan umum pengembangan silabus. Mitra Usaha Indonesia, 2008.

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Indonesia, BP Mitra Usaha, ed. Panduan pengembangan materi pembelajaran dan standar sarana dan prasarana sekolah menengah kejuruan: Madrasah aliyah, SMA/MA/SMK/MAK : dilengkapi pengembangan program muatan lokal, sistem penilaian KTSP panduan penyelenggaraan pembelajaran pengayaan, sistem penilaian KTSP panduan penyelenggaraan pembelajaran remedial, sistem penilaian KTSP panduan penyelenggaraan pembelajaran tuntas (mastery learning), pengembangan model pembelajaran tatap muka, penugasan restruktur dan tugas mandiri tidak restruktur, panduan pengembangan bahan ajar, panduan pengembangan indikator, panduan umum pengembangan silabus. Mitra Usaha Indonesia, 2008.

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Kartika, Septi Budi. Modul Praktikum Fisika Dasar. Umsida Press, 2016. http://dx.doi.org/10.21070/2016/978-979-3401-82-9.

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Laboratorium IPA disiapkan dan dikembangkan oleh FKIP untuk mendukung proses belajar mengajar yang berkenaan dengan mata kuliah Sains untuk Program studi Pendidikan IPA. Laboratorium yang terdiri dari laboratorium fisika, kimia, dan biologi ini, merupakan sarana penting untuk pendidikan dan penelitian yang akan menerapkan serta mengembangkan teori-teori dan konsep-konsep dasar dalam bidang fisika, kimia, dan biologi yang terkait. Laboratorium IPA digunakan untuk melaksanakan 15 mata praktikum yaitu: Fisika Dasar, Kimia Dasar, Biologi Umum, Fluida, Makhluk Hidup dan Kehidupan, Interaksi Antar F

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Studi eksperimental model pembelajaran berbasis portofolio dalam mata pelajaran PPKN sebagai sarana pendidikan demokrasi: Studi kasus di sekolah model : laporan penelitian. Fakultas Pendidikan Ilmu Pengetahuan Sosial, Universitas Pendidikan Indonesia, 2001.

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Book chapters on the topic "SARIMA model"

Tahyudin, Imam, Berlilana, and Hidetaka Nambo. "SARIMA Model of Bioelectic Potential Dataset." In Communications in Computer and Information Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96292-4_29.

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Nokeri, Tshepo Chris. "Forecasting Using ARIMA, SARIMA, and the Additive Model." In Implementing Machine Learning for Finance. Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-7110-0_2.

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Sun, Susu, Xinbo Ai, and Yanzhu Hu. "Emergency Response Technology Transaction Forecasting Based on SARIMA Model." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38460-8_62.

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Batista da Silveira, Tiago, Felipe Augusto Lara Soares, and Henrique Cota de Freitas. "Fast and Efficient Parallel Execution of SARIMA Prediction Model." In Enterprise Information Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75418-1_11.

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Zhang, Xiao. "Forecast and Analysis of China’s CPI Based on SARIMA Model." In Atlantis Highlights in Intelligent Systems. Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-030-5_135.

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Sulistiyono, Heri, Faisal Irshad Khan, Humairo Saidah, et al. "The Development of the SARIMA Model for Flood Disaster Resilience." In Proceedings of the First Mandalika International Multi-Conference on Science and Engineering 2022, MIMSE 2022 (Civil and Architecture). Atlantis Press International BV, 2022. http://dx.doi.org/10.2991/978-94-6463-088-6_21.

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Jagannathan, J., C. Divya, and M. Thanjaivadivel. "SARIMA model to predict land surface temperature for the UHI effect." In Artificial Intelligence, Blockchain, Computing and Security Volume 2. CRC Press, 2023. http://dx.doi.org/10.1201/9781032684994-46.

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Kumar, Vipin, Nitin Singh, Deepak Kumar Singh, and S. R. Mohanty. "Short-Term Electricity Price Forecasting Using Hybrid SARIMA and GJR-GARCH Model." In Networking Communication and Data Knowledge Engineering. Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-4585-1_25.

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Zheng, Chen, Yuzhou Wu, Zhigang Chen, Kun Wang, and Lizhong Zhang. "A Load Forecasting Method of Power Grid Host Based on SARIMA-GRU Model." In Communications in Computer and Information Science. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-7443-3_9.

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Dedovic, M. Muftic, Samir Avdaković, Adnan Mujezinović, and N. Dautbasic. "The Hybrid EMD-SARIMA Model for Air Quality Index Prediction, Case of Canton Sarajevo." In Advanced Technologies, Systems, and Applications V. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-54765-3_9.

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Conference papers on the topic "SARIMA model"

Pratama, Rian Putra, Hanif Fakhurroja, Harry Bangkit, and Dita Pramesti. "Prediction of NPK Fertilizer in Chili Plants Using SARIMA Model." In 2024 International Conference on ICT for Smart Society (ICISS). IEEE, 2024. http://dx.doi.org/10.1109/iciss62896.2024.10751445.

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Gandhi, Herry Kartika. "Applying Hybrid Forecasting Model SARIMA-SVR for Daily Energy Consumption Data." In 2024 IEEE 3rd Conference on Information Technology and Data Science (CITDS). IEEE, 2024. https://doi.org/10.1109/citds62610.2024.10791394.

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Cheng, Tong. "Research on the road traffic accident prediction based on SARIMA-LSTM model." In Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024), edited by Xiantao Xiao and Jia Yao. SPIE, 2024. https://doi.org/10.1117/12.3054553.

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Williams, Ashton T., and Soon M. Chung. "Enhanced Multi-SARIMA Model for Anomaly Detection in Multi-Seasonal Time Series Data." In 2024 IEEE International Conference on Data and Software Engineering (ICoDSE). IEEE, 2024. https://doi.org/10.1109/icodse63307.2024.10829881.

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Verma, Rupal, Sudhakar Pandey, and Suvendu Rup. "Traffic Flow Prediction Using LSTM, ARIMA & SARIMA Model for Intelligent Transportation System." In 2024 International Conference on Intelligent Computing and Sustainable Innovations in Technology (IC-SIT). IEEE, 2024. https://doi.org/10.1109/ic-sit63503.2024.10862828.

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Wen, Youdong, Ruonan Yang, Ting Huang, Haipeng Xiong, and Guangcheng Wang. "A Study on Highway Traffic Volume Forecasting Based on the SARIMA-GCN-LSTM Model." In 2024 IEEE 2nd International Conference on Sensors, Electronics and Computer Engineering (ICSECE). IEEE, 2024. http://dx.doi.org/10.1109/icsece61636.2024.10729447.

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Song, Dawei. "Research on SARIMA-LSTM Crime Prediction Model Based on Nonlinear Combination of RBF Neural Network." In 2024 Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC). IEEE, 2024. http://dx.doi.org/10.1109/ipec61310.2024.00079.

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Wenjie, HOU, DENG Xudong, LI Yingli, and PENG Kunkun. "A Study on a Regional Logistics Demand Forecasting Method Based on STL-SARIMA-Informer Model." In The 14th International Conference on Logistics and Systems Engineering. Aussino Academic Publishing House, 2025. https://doi.org/10.52202/078960-0050.

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Shi, Muhao, Yilong Huang, Lejian Zhang, Zetong Jin, and Yuhan Zhang. "Wordle User Prediction and Analysis Based on SARIMA Algorithm, LSTM Recurrent Neural Network, and XGBoost Model." In 2024 2nd International Conference on Mechatronics, IoT and Industrial Informatics (ICMIII). IEEE, 2024. http://dx.doi.org/10.1109/icmiii62623.2024.00121.

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Fariz, Khairunnisa Norfaeza Mohamed Khairul, Mohd Fuad Abdul Latip, and Norliza Zaini. "Real-Time Data Forecasting On Missing Energy Data Using Seasonal Autoregressive Integrated Moving Average (SARIMA) Model." In 2024 14th International Conference on System Engineering and Technology (ICSET). IEEE, 2024. https://doi.org/10.1109/icset63729.2024.10774909.

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Reports on the topic "SARIMA model"

Roldán-Ferrín, Felipe, and Julián A. Parra-Polania. ENHANCING INFLATION NOWCASTING WITH ONLINE SEARCH DATA: A RANDOM FOREST APPLICATION FOR COLOMBIA. Banco de la República, 2025. https://doi.org/10.32468/be.1318.

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This paper evaluates the predictive capacity of a machine learning model based on Random Forests (RF), combined with Google Trends (GT) data, for nowcasting monthly inflation in Colombia. The proposed RF-GT model is trained using historical inflation data, macroeconomic indicators, and internet search activity. After optimizing the model’s hyperparameters through time series cross-validation, we assess its out-of-sample performance over the period 2023–2024. The results are benchmarked against traditional approaches, including SARIMA, Ridge, and Lasso regressions, as well as professional forec

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Akbari, Chirag, Ninad Gore, and Srinivas Pulugurtha. Understanding the Effect of Pervasive Events on Vehicle Travel Time Patterns. Mineta Transportation Institute, 2023. http://dx.doi.org/10.31979/mti.2023.2319.

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The COVID-19 pandemic has disrupted daily activities and travel patterns, affecting personal and commercial trips. This study investigates the effect of different stages of the pandemic on travel time patterns. Eighty-six geographically distributed links (sections of road) in Mecklenburg County and Buncombe County, North Carolina, were selected for analysis. The selected links accounted for the variation in road geometry, land use, and speed limit. Travel time data for three years (i.e., 2019, 2020, and 2021) were extracted from a private data source at 5-min intervals. Travel time reliability

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Sarkissian, Angie. Comparison between the Tap Model and Sara-2d Results. Defense Technical Information Center, 1997. http://dx.doi.org/10.21236/ada329259.

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Rueda, Diana, and Eylla Laire Gutierrez. Gender, Microentrepreneurship, Human Flourishing: Exploring the Experiences of Women Sari-sari Store Owners toward Inclusive Growth. Philippine Institute for Development Studies, 2025. https://doi.org/10.62986/dp2024.50.

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For years, women’s involvement in entrepreneurial activities has been widely advocated as part of economic development agendas. This is evidenced by numerous initiatives, projects, and roadmaps that promote women's integration into economic activities through entrepreneurship. Underpinning these efforts is the assumption that women's active participation in economic activities leads to improved well-being and empowerment. While this is an essential step toward improving women’s conditions, the realities are more complex. Beyond the economic contributions of such entrepreneurial activities, oth

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Gregory, M. V. Technical bases of the second generation SARIS core model (Task Number: 90-008-0). Office of Scientific and Technical Information (OSTI), 1991. http://dx.doi.org/10.2172/10165492.

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Cadena, J. Graph-Based Modeling for the Detection and Tracking of Sarin-Surrogate-Induced Neurotoxicity Using a Human-Relevant, In-Vitro Brain Model. Office of Scientific and Technical Information (OSTI), 2024. http://dx.doi.org/10.2172/2475547.

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Anderson, B. Technical Review Report for the "Justification for Small Gram Quantity Contents" Safety Analysis Report for Packaging Model 9977-96, Addendum 3, S-SARA-G-00006, Revision 4. Office of Scientific and Technical Information (OSTI), 2010. http://dx.doi.org/10.2172/1124840.

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Studsrød, Ingunn, Ragnhild Gjerstad Sørensen, Brita Gjerstad, Patrycja Sosnowska-Buxton, and Kathrine Skoland. “It’s very complex”: Professionals’ work with domestic violence (DV): Report – FGI and interviews 2022. University of Stavanger, 2022. http://dx.doi.org/10.31265/usps.249.

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This study explores Norwegian professionals' experiences of working within partner violence (PV) prevention area, including, cross-sectoral and interdisciplinary cooperation as well as possible successful strategies and measures in this area. This report is one of the deliverables of the “Integrated System of Domestic Violence Prevention” (ISDVP) project and of the agreement with The State Treasury, the Institute of Justice in Warsaw, Poland. This study contributes to research on professionals’ experiences of interprofessional collaboration in the domestic violence prevention area – a similar

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