Monitoring and forecasting of land use/land cover (LULC) in Al-Hassa Oasis, Saudi Arabia based on the integration of the Cellular Automata (CA) and the Cellular Automata-Markov Mod... by Ashraf Abdelkarim

“…The maximum likelihood classifier (MLC) method was used as a supervised classification algorithm to super control classification coefficients. …”
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Evolution of the Seismic Forecast System Implemented for the Vrancea Area (Romania) by Victorin-Emilian Toader, Constantin Ionescu, Iren-Adelina Moldovan, Alexandru Marmureanu, Iosif Lıngvay, Andrei Mihai

“…All collected data are stored in an open-access database available in real time, geobs.infp.ro. The monitoring methods include threshold-based event detection and seismic data analysis. …”
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Forecasting Financial Crashes: Revisit to Log-Periodic Power Law by Bingcun Dai, Fan Zhang, Domenico Tarzia, Kwangwon Ahn

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Online monitoring data processing methods for railway slopes and its application: A case study of the Shuohuang Railway by Mu GU

“…Engineering applications demonstrate that the proposed methods effectively detect and correct outliers, provide robust noise suppression, and yield precise deformation trend predictions, enhancing the practical application of monitoring systems.…”
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Geomorphological and Isotope-Geochemical Methods in Assessing the Gas Potential of a Territory (Using the Example of the Angara-Lena Oil and Gas Region) by Smirnov Aleksandr Sergeevich, Nourgaliev Danis, Chernova Inna Yur'evna, Ziganshin Eduard

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Early Warning Method of Abnormal Electricity Consumption Behavior Based on Data Driven by WAN Wei, LIU Hongqi, SUN Hong-chang, ZHANG Feng, WANG Yang, SUN Wei-qing

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Multi-Means Comprehensive Forecasting Technology for Water Inrush in Long Tunnels by Jingxi Yang, Qi Ma, Huabo Xiao, Xinyuan Wei, Fei Yan, Wencong Zhang, Jingwen Chen, Zhou Xiao, Guoqing Wang

“…Finally, for water-containing bodies that are close, ground penetrating radar methods are used for detection and forecasting to achieve the purpose of close-range detection and forecasting. …”
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Limits of Solar Flare Forecasting Models and New Deep Learning Approach by G. Francisco, M. Berretti, S. Chierichini, R. Mugatwala, J. Fernandes, T. Barata, D. Del Moro

“…This study introduces a novel deep learning forecasting approach while emphasizing the need for performance evaluation methods tailored to better highlight current models’ limitations. …”
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Forecast Padding Enhances Accuracy and Robustness of EEG-Phase-Synchronized TMS by Yu-Cheng Chang, Pin-Hsuan Chao, Yan-Ming Kuan, Chiu-Jung Huang, Li-Fen Chen, Wei-Chung Mao, Tung-Ping Su, Sin-Horng Chen, Chun-Shu Wei

“…Inspired by predictive coding theory in neuroscience, we propose a novel signal padding method (forecast padding) to mitigate the filter edge effect. …”
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Forecasting Urban Sprawl Dynamics in Islamabad: A Neural Network Approach by Saddam Sarwar, Hafiz Usman Ahmed Khan, Falin Wu, Sarah Hasan, Muhammad Zohaib, Mahzabin Abbasi, Tianyang Hu

“…Utilizing a land change modeler (LCM), forecasts of the future conditions in 2025, 2030, and 2035 are predicted. …”
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Taxi Demand Prediction Based on a Combination Forecasting Model in Hotspots by Zhizhen Liu, Hong Chen, Yan Li, Qi Zhang

“…However, most taxi demand studies are based on historical taxi trajectory data. In this study, we detected hotspots and proposed three methods to predict the taxi demand in hotspots. …”
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Optimizing maize germination forecasts with random forest and data fusion techniques by Lili Wu, Yuqing Xing, Kaiwen Yang, Wenqiang Li, Guangyue Ren, Debang Zhang, Huiping Fan

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Advances in Wastewater-Based Epidemiology for Pandemic Surveillance: Methodological Frameworks and Future Perspectives by Weihe Zhu, Daxi Wang, Pengsong Li, Haohao Deng, Ziqing Deng

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Frost forecasting via weakly-supervised semantic segmentation of satellite imagery by Seokho Kang, Seon-Kyeong Seong, Eunha Sohn, Jiyoung Kim, Jaewoong Shim

“…We demonstrate the effectiveness of the proposed method for frost forecasting with varying lead times across the South Korean region using Geo-KOMPSAT-2A satellite data.…”
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Assessment of the possibility of forecasting hydrometeorological extremes using the solar activity index by Miskevich I.V., Kotova E.I.

“…The method can be used for specifying longterm hydrometeorological and ecological forecasts. …”
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PREDICTION OF THE INCIDENCE OF PROSTATE CANCER IN THE URAL ECONOMIC REGION OF THE RUSSIAN FEDERATION by K. A. Ilyin, A. V. Zamyatin, G. P. Bystray, S. A. Okhotnikov

“…Objective. To quantify and to forecast the dynamics of registered cases of prostate cancer (PC) in the Ural economic region.Material and methods. …”
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Evaluating Deep Learning Networks Versus Hybrid Network for Smart Monitoring of Hydropower Plants by Fatemeh Hajimohammadali, Emanuele Crisostomi, Mauro Tucci, Nunzia Fontana

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Autoregressive Neural Network for Cloud Concentration Forecast from Hemispheric Sky Images by Cristian Crisosto

“…Secondly, a new image-processing algorithm is suggested to optimize the cloud detection process starting with the Haze Index. Finally, the cloud concentration five minutes in advance at the IMUK is forecasted using machine learning methods. …”
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Addressing the training gaps for ASD specialists in Kazakhstan: A forecast-based approach by Ainagul Rymkhanova, Saltanat Mulikova, Alfina Sakayeva, Zhanar Akhmetzhanova, Sara Zhanibekova, Assem Bekmaganbetova

“…Additionally, mathematical modeling and forecasting methods were employed to predict the increase in the number of children with ASD, facilitating the development of targeted educational programs for training specialists at undergraduate and graduate levels and improving the qualifications of practicing professionals. …”
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An explainable Machine Learning model for Large-Scale Travelling Ionospheric Disturbances forecasting by Ventriglia Vincenzo, Guerra Marco, Cesaroni Claudio, Spogli Luca, Altadill David, Segarra Antoni, Galkin Ivan, Barta Veronika, Verhulst Tobias G.W., de Paula Víctor, Navas-Portella Víctor, Berényi Kitti A., Belehaki Anna

“…The validation procedure consists of a global-level evaluation and interpretation step, firstly, followed by an event-level validation against independent detection methods, which highlights the model’s predictive robustness and suggests its potential for real-time space weather forecasting. …”
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