RADIONUCLIDE METHODS IN THE DETECTION AND FORECAST OF ANTHRACYCLINE-INDUCED CARDIOTOXICITY IN BREAST CANCER PATIENTS by V. I. Chernov, T. L. Kravchuk, R. V. Zel’chan, V. E. Gol’dberg, N. O. Popova, E. I. Simolina, V. V. Vysockaja, Ju. V. Belevich, I. G. Sinilkin, A. А. Medvedeva, O. D. Bragina

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Application of the Delphi methodology to forecast competencies oriented towards AI-driven disinformation detection in an expanded DigComp framework by Cristina M. Arribas, Rubén Arcos, Manuel Gertrudix

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Forecasting Eruptions at Steamboat Geyser: Time Scales, Differentiability, and Detectability of Seismic Precursors Through Data‐Driven Methods by Alberto Ardid, Anna Barth, David Dempsey, Michael Manga, Shane J. Cronin

“…We applied isotonic regression, a method that converts raw model outputs into calibrated probabilities, to improve the interpretability of eruption forecasting outputs. …”
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Short-Term Wind Speed Forecasting Using Decomposition-Based Neural Networks Combining Abnormal Detection Method by Xuejun Chen, Jing Zhao, Wenchao Hu, Yufeng Yang

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Short and Medium-Term Power Load Anomaly Detection Method Based on Convolutional Neural Network and EL-DCC by Zhipeng Li, Shaobo Liu, Yang Zhang, Zhaowei Wang, Lu Wang, Lu Huang

“…The proposed method provides an efficient anomaly detection and forecasting scheme for the power system and improves the intelligent management level of the power grid.…”
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Workload Forecasting Methods in Cloud Environments: An Overview by Samah Aziz, Manar Kashmoola

“…We also examine the particular difficulties and factors involved in LSTM-based workload forecasting implementation in cloud systems. We also examine previous research and methods that have employed LSTM networks to forecast workload in cloud systems. …”
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A Deep Learning Method for Improving Community Multiscale Air Quality Forecast: Bias Correction, Event Detection, and Temporal Pattern Alignment by Ioannis Stergiou, Nektaria Traka, Dimitrios Melas, Efthimios Tagaris, Rafaella-Eleni P. Sotiropoulou

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High-Speed Robust Dynamic Positioning and Tracking Method Based on Visual Visible Light Communication Using Optical Flow Detection and Bayesian Forecast by Weipeng Guan, Xin Chen, Mouxiao Huang, Zixuan Liu, Yuxiang Wu, Yingcong Chen

“…Therefore, we propose a novel VLP algorithm based on image sensor (as positioning terminal), exploiting optical flow detection and Bayesian forecast. The proposed optical flow method is used for real-time detection, and solves the problem of blur effect caused by the fast relative movement between the LED and positioning terminal, which would result in location failure in the traditional VLP system with pixel intensity detection. …”
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Sensor Fusion Enhances Anomaly Detection in a Flood Forecasting System by Andrew Ma, Abhir Karande, Natalie Dahlquist, Fabien Ferrero, N. Rich Nguyen

“…Our method uses time-series anomaly detection to identify incorrect readings. …”
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Analytical Methods for Assessing and Forecasting Financial Standing of Credit Institutions by Y. M. Beketnova

“…The objective of the article is to propose a new approach to assessing and forecasting fnancial condition of credit institutions and to early detection of those that have high risks of license revocation. …”
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A Traffic Information Detection Method at Single Intersection Based on Wi-Fi Data by Qingmiao Wang, Jinghe Feng, Shuguang Li

Subjects: “…traffic information detection method…”
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Two-Stage Systematic Forecasting of Earthquakes by Valery Gitis, Alexander Derendyaev

“…Consequently, the seismic process requires regular monitoring and systematic forecasting of strong earthquakes. This study introduces an enhanced iteration of the method of the minimum area of alarm (MMAA), refined to advance earthquake forecasting technology closer to its practical application. …”
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AI-Driven Insect Detection, Real-Time Monitoring, and Population Forecasting in Greenhouses by Dimitrios Kapetas, Panagiotis Christakakis, Sofia Faliagka, Nikolaos Katsoulas, Eleftheria Maria Pechlivani

“…This widespread reliance on chemical insecticides has substantial economic, environmental, and human health consequences, highlighting the urgent need for sustainable pest management strategies. Early detection, insect monitoring, and population forecasting through Artificial Intelligence (AI)-based methods, can enable swift responsiveness, allowing for reduced but more effective insecticide use, mitigating traditional labor-intensive and error prone solutions. …”
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Applying forecasting methods to accrual-based and cash-based ratio analysis by Alexey Litvinenko, Anna Litvinenko, Samuli Saarinen

“…Research Questions: Which of the forecasting methods (SMA, ARIMA, ES) is the most informative? …”
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Cloud Detection Challenge-Methods and Results by Alessio Barbaro Chisari, Luca Guarnera, Alessandro Ortis, Wladimiro Carlo Patatu, Bruno Casella, Luca Naso, Giuseppe Puglisi, Vincenzo del Zoppo, Mario Valerio Giuffrida, Sebastiano Battiato

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A Novel Multi-Step Forecasting-Based Approach for Enhanced Burst Detection in Water Distribution Systems by Xi Wan, Raziyeh Farmani, Edward Keedwell, Xiao Zhou

“…For an online burst detection method based on flow time series data, the challenge arises in the variability of anomaly definitions across different datasets, rendering a one-size-fits-all anomaly detection algorithm impossible. …”
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Trend Detection and Forecasting of LST in Tabriz City using the Non-parametric Mann-Kendall and NNAR by Mohammad Ali Koushesh Vatan, Akbar Asghari Zamani, Shahrivar Rostaei

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The usage of power system multi-model forecasting aided state estimation for cyber attack detection by I. A. Lukicheva, A. L. Kulikov

“…The aim of the research was to develop a state estimation algorithm, which is able to work in the presence of cyber-attack with high accuracy.METHODS. The authors propose a Multi-Model Forecasting-Aided State Estimation method based on multi-model discrete tracking parameter estimation by the Kalman filter. …”
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Modeling and forecasting of egg production in india using time series models by Abdullah Mohammad Ghazi Al Khatib, Harun Yonar, Mostafa Abotaleb, Pradeep Mishra, Aynur Yonar, Kadir Karakaya, Amr Badr, Vinti Dhaka

“…<p> <b>Results: </b>It is detected that Holt's Linear Trend Model is the best fit model for forecasting. …”
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CESNET-TimeSeries24: Time Series Dataset for Network Traffic Anomaly Detection and Forecasting by Josef Koumar, Karel Hynek, Tomáš Čejka, Pavel Šiška

“…Most approaches to anomaly detection use methods based on forecasting. Extensive real-world network datasets for forecasting and anomaly detection techniques are missing, potentially causing overestimation of anomaly detection algorithm performance and fabricating the illusion of progress. …”
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