Non-Intrusive Monitoring and Detection of Mobility Loss in Older Adults Using Binary Sensors by Ioan Susnea, Emilia Pecheanu, Adina Cocu, Adrian Istrate, Catalin Anghel, Paul Iacobescu

“…Clinical mobility assessment methods, though precise, are resource-intensive and economically impractical, and most of the existing solutions for automatic detection of mobility anomalies are either obtrusive or improper for long time monitoring. …”
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Seasonal footprints on ecological time series and jumps in dynamic states of protein configurations from a nonlinear forecasting method characterization by Leonardo Reyes, Kilver Campos, Gilberto D Avendaño, Lenin González-Paz, Alejandro Vivas, Ysaías J Alvarado, Saúl Flores

“…Full plots of prediction quality as a function of dimensionality E and forecasting time T _p , the two basic parameters of the method, give fast and valuable information about complex systems dynamics. …”
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Segmentation of Energy Consumption Using K-Means: Applications in Tariffing, Outlier Detection, and Demand Prediction in Non-Smart Metering Systems by Darío Muyulema-Masaquiza, Manuel Ayala-Chauvin

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Research on real-time abnormal voltage detection and prediction method based on the linear tracking differentiator by XIAO Xiong, ZHANG Yong-jun, WANG Jing, SU Hong-yue

“…One kind of detection and prediction method for abnormal grid voltage has been designed due to the case that modern power electronic equipment is sensitive to non-stationary time-varying voltage signal. …”
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MODERN METHODS FOR BUSINESS EVALUATION by Tatiana N. Cheprakova, Natalia A. Rumachik, Hayk A. Engibaryan

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Retrospective Medium-Term Forecast of a Catastrophic Earthquake in Turkey in 2023 (02.06.2023, MW=7.7) Using the LURR Method by A. S. Zakupin, N. A. Sycheva

“…The results of calculations using the LURR method were compared with the reconstruction data using the STD method. …”
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Evaluation and Anomaly Detection Methods for Broadcast Ephemeris Time Series in the BeiDou Navigation Satellite System by Jiawei Cai, Jianwen Li, Shengda Xie, Hao Jin

“…Evaluation results show that the IF-TEA-LSTM model reduces the RMSE by up to 20.80% for orbital parameters and improves clock deviation prediction accuracy for MEO satellites by 68.37% in short-term forecasts, outperforming baseline models. This method significantly enhances anomaly detection accuracy across GEO, IGSO, and MEO satellite orbits, demonstrating its superiority in long-term data processing and its capacity to improve the reliability of satellite operations within the BDS.…”
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Intelligent Data Processing Methods for the Atypical Values Correction of Stock Quotes by T. V. Zolotova, D. A. Volkova

“…The practical implementation of the methods for detecting and eliminating outliers used in this work can be a tool for calculating more accurate indicators in any area, for example, to improve forecasting the stock price. …”
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Application of statistical methods for predicting udp-flood attacks by M. V. Tumbinskaya, V. V. Volkov, B. G. Zagidullin

“…The aim of this study was to increase the level of security of web resources by means of timely detection of anomalies in their work, detection of information security threats based on analysis and forecasting methods. …”
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Explaining the Earnings Management Prediction Model Using the Hybrid of Machine Learning Methods by Hassan Hassani, Esfandiar Malekian Kallehbasti, Yahya Kamyabi

“…Based on the obtained results, the hybrid method based on deep learning and relief feature selection has the highest prediction accuracy (89/62) among other hybrid methods for forecasting accruals earnings management, and the hybrid method based on deep learning and principal component analysis feature selection has the highest prediction accuracy (82/65) among other hybrid methods for forecasting real earnings management.The findings of this study can expedite earnings management detection for financial statement users by improving earnings management prediction accuracy. …”
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Tunnel Seismic Detection for Tunnel Boring Machine by Joint Active and Passive Source Method and Imaging Advanced Prediction by Xinglin Lu, Jun Wang, Wei Wang, Xuhua Liu, Chao Yang, Yufeng Liu, Zhihong Fu

“…The passive detection method usually produces results of low resolution and with limited forecast precision. …”
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Detection and Prediction of Wind and Solar Photovoltaic Power Ramp Events Based on Data-Driven Methods: A Critical Review by Jie Zhang, Xinchun Zhu, Yigong Xie, Guo Chen, Shuangquan Liu

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Modelling and Forecasting Energy Efficiency Impact on the Human Health by Yuliia Matvieieva, Hedy Ben Hamida

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University proceedings. Volga region. Technical sciences by D.V. Artamonov, V.M. Myskin, A.D. Semenov

“…Assuming that the amount of energy emitted by the housing obeys the Stefan-Boltzmann law, a heat balance equation was obtained taking into account the internal reflection of thermal energy, which showed that the occurrence of elementary Arnold disasters of types A1-A4 is theoretically possible. A forecasting method is proposed, using which the disaster detection time is reduced by 200 minutes, compared to the time of emergency detection by a traditional monitoring system. …”

Using Adjoint-Based Forecast Sensitivity to Observation to Evaluate a Wind Profiler Data Assimilation Strategy and the Impact of Data on Short-Term Forecasts by Cheng Wang, Xiang-Yu Huang, Min Chen, Yaodeng Chen, Jiqin Zhong, Jian Yin

“…Meanwhile, the dense profiler observations resulted in a more significant impact when radiosonde observations were not detected. The upper-level single winds monitored by profiler radars play a more important role in improving forecast skill. …”
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Predictive control method with conduction mode detection to suppress input current distortion of three‐level power factor correction by Xifeng Xie, Zeliang Shu, Rongxin Chen, Jianghong Yin, Chunxiang Ling

“…Abstract A novel predictive control method with conduction mode detection is proposed to suppress input current distortion of three‐level power factor correction (PFC) converters. …”
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Method of Diagnostics of Operation Modes of Individual Heat Supply Units, Allowing to Detect Pre-Emergency Situations at an Early Stage by Dvortsevoy A.I., Borush O.V., Khoreva V.A., Yakovina I.N.

“…This was confirmed by the "Elbow Method", which determined the optimal number, which made it possible to significantly improve the forecasting of emergency modes. …”
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Short-term prediction method of oblique sounding ionosphere MUF based on robust Kalman filter by Guojun LI, Guangfa ZHENG, Changrong YE, Yinping ZHOU

“…To improve the low accuracy of ionospheric frequency forecasting, poor HF communication connectivity, and the severe impact of observational outliers in engineering on forecast accuracy, a short-term prediction method for oblique detection ionospheric MUF based on robust Kalman filtering was proposed.By studying the variation law of the measured MUF data and the causes as well as characteristics of observation errors, and exploiting the ionospheric reference model as a priori information, the state estimation equation of the Kalman filter model was improved.The cost function mechanism was introduced to realize the measurement update of the forecast state through Huber-M estimation, which reduced the influence of the observation outliers on the forecast results and improves the robustness of the proposed method.The simulation results show that the proposed method can effectively suppress the adverse effects caused by the observation outliers and has good robustness and stability.…”
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Interval Forecasting Using GEV Regression With Stochastic Search Variable Selection: A Simulation Study and Its Application to Forecast Imported Meat Price Range by Dedy Dwi Prastyo, Ike Yuniarti, Setiawan, Santi Puteri Rahayu

“…These insights offer a robust approach for forecasting imported meat prices while detecting potential price anomalies, directly benefiting the trade industry.…”
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DAT: Deep Learning-Based Acceleration-Aware Trajectory Forecasting by Ali Asghar Sharifi, Ali Zoljodi, Masoud Daneshtalab

“…We propose a robust and innovative method for estimating ground-truth acceleration for objects, along with an object detector that predicts acceleration attributes for each detected object and a novel method for trajectory forecasting. …”
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