IMPLEMENTATION OF CROSS-VALIDATION ON HANG SENG INDEX FORECASTING USING HOLT’S EXPONENTIAL SMOOTHING AND AUTO-ARIMA METHOD by Christy Sheldy Sucipto, Winita Sulandari, Yuliana Susanti

“…This study applies a rolling window cross-validation to evaluate the multi-step forecasts instead of using the traditional single split for Hang Sheng Index (HSI) forecasting. The forecasting methods discussed in this study are Holt's Exponential Smoothing and auto ARIMA, chosen because of their ability to model trend data as in the daily HSI. …”
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Comparative Forecasting Demand For Robusta Ground Coffee Product in SME SL Malang Regency Using Holt-Winters Exponential Smoothing and Seasonal ARIMA Method by Annisa Zahara Lutfi, Heptari Elita Dewi, Djoko Koestiono, Ajeng Rizqya Shabrina, Aleisha Julia Deme Anak Julin

“…The data used is ground coffee demand data for the period January 2015 to August 2022. The forecasting methods used is Holt-Winters Exponential Smoothing and SARIMA. …”
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Comparison of Single Exponential Smoothing and Double Moving Average Algorithms to Forecast Beef Production by Tundo, Rachmat Hidayat Insani, Rasiban, Untung Suropati

“…After that, in 2021, production reached 16,381.81 tons and continued to increase in 2022 and 2023. A precise method is required to forecast beef production. One way to predict beef production in Jakarta is using the Single Exponential Smoothing and Double Moving Average methods. …”
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Method for Selecting Pulsed Signals by Their Duration in Fading Channels by M. V. Buhaiov, S. V. Zakirov

“…Pulse durations that are not related to signals are subjected to an exponential distribution. The input data for the proposed method is only a sample of measured pulse durations. …”
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Impact of COVID-19 pandemic in the Brazilian maternal mortality ratio: A comparative analysis of Neural Networks Autoregression, Holt-Winters exponential smoothing, and Autoregress... by Mayara Carolina Cañedo, Thiago Inácio Barros Lopes, Luana Rossato, Isadora Batista Nunes, Izadora Dillis Faccin, Túlio Máximo Salomé, Simone Simionatto

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Formation of Instantaneous Differential and Restraining Cur-rents for Differential Protection of Busbar Assemblies by V. S. Kachenya, M. S. Loman

“…In this mode, protection for instantaneous values is more susceptible to false positives than for active ones. The method of exponential smoothing of the restraining current was considered and investigated. …”
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Constructing a New Exponentiated Family Distribution with Reliability Estimation by Shurooq Ahmed Al-Sultany

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Effects of missing data imputation methods on univariate blood pressure time series data analysis and forecasting with ARIMA and LSTM by Nicholas Niako, Jesus D. Melgarejo, Gladys E. Maestre, Kristina P. Vatcheva

“…In our small sample, ARIMA tended to perform better on data with higher autocorrelation. …”
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Exploring different modelling approaches to forecast the community acute respiratory infections burden in children: an Italian epidemiological time series study by Riccardo Boracchini, Benedetta Canova, Pietro Ferrara, Elisa Barbieri, Pietro Giorgio Lovaglio, Antonio Scamarcia, Giovanni Corrao, Daniele Donà, Carlo Giaquinto, Costanza Di Chiara, Anna Cantarutti

“…Overall, our findings suggest that exponential smoothing models as ETS (MAPE = 6.85) and TBATS (MAPE = 6.87) were most effective in predicting future trends in monthly ARIs’ burden compared to other methods (i.e., UCM MAPE = 11.08, and SARIMA MAPE = 25.33). …”
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Forecasting the Sales of Console Games for the Italian Market by Renato Rossetti

“…In particular two univariate techniques were evaluated, exponential smoothing and the SARIMA technique. The aim is to exploit the capabilities of these statistical methods in order to have a comparison of the results and to choose the most accurate model through an ex-post evaluation. …”
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Structural time series modelling for weekly forecasting of enterovirus outpatient, inpatient, and emergency department visits. by Cathy W S Chen, Leon L Hsieh, Betty X Y Chu

“…This approach enhances the reliability of predictions, supporting timely and effective surveillance and early detection of significant case surges.<h4>Methods</h4>This study divides the time series data into an in-sample period (2016-2023) and an out-of-sample period covering weeks 1 to 27 in 2024. …”
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Multi-source data fusion-based knowledge transfer for unmanned aerial vehicle flight data anomaly detection and recovery by Lei Yang, Shaobo Li, Liya Yu, Caichao Zhu, Congbao Wang

“…Then, the model is fine-tuned using limited training samples in the target domain through model-based transfer learning method and is evaluated using test data of the target domain. …”
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Random Finite Element Analysis and Random Factor response Mechanism for Geocell-reinforced Soil Retaining Walls by ZHANG Bingbing, SONG Fei

“…For this reason, a finite element analysis method based on random field theory is proposed in this paper, which can more realistically reflect the non-homogeneous characteristics of the reinforced soil retaining wall system by introducing a spatial random distribution model of the soil parameters and the mechanical properties of the geocells, so as to more accurately assess the influence of the spatial variability of the material parameters on the deformation behavior and stability of the retaining wall.MethodsFirstly, in parameter random field modeling, an innovative combination of Latin Hypercube Sampling (LHS) and exponential autocorrelation function is used to construct parameter random fields. …”
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Three-Dimensional Path Planning for Unmanned Aerial Vehicles Based on Hybrid Multi-Strategy Dung Beetle Optimization Algorithm by Hongmei Fei, Ruru Liu, Leilei Dong, Zhaohui Du, Xuening Liu, Tao Luo, Jie Zhou

“…This paper proposes a novel UAV path planning method based on the Hybrid Multi-Strategy Dung Beetle Optimization Algorithm (HMSDBO), which effectively reduces path length and improves path smoothness. …”
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