Comparing Linear and Nonlinear Models for Load Profile Data Using ANOVA, AIC, and BIC by Ilir Keka, Betim Çiço

“…In this paper the aim is to find the best model that gives the best forecast of the values for the line of best fit, or to find the model, which is mostly approximated to the real model. …”
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The Stochastic Evolution of Financial Asset Prices by Ioannis Paraskevopoulos, Alvaro Santos

“…We validate our theoretical framework through empirical analysis of an extensive dataset comprising daily prices from the S&P500, 10-year US Treasury bonds, the EUR/USD exchange rate, Brent oil, and Bitcoin from 1 January 2002 to 1 February 2024. …”
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Strategy for developing human resources potential of Russian Railways by S. V. Lyukhanova, A. I. Solokhina

“…The authors have conducted a terminological analysis of the concept and considered its components such as spiritual, intellectual (mental), and physical (material) resources. …”
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Meteorological Patterns Associated with Intense Saharan Dust Outbreaks over Greece in Winter by P. T. Nastos

“…The ground based particulate matter concentrations in Athens were excessively increased on the dusty days (PM10: 150–560 μg/m3), while significant dry and wet deposition occurred as forecasted by DREAM model.…”
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Intensification of Mid‐Latitude Cyclone by Aerosol‐Radiation Interaction Increases Transport of Canadian Wildfire Smoke to Northeastern US by Zilin Wang, Xin Huang, Lian Xue, Ke Ding, Sijia Lou, Anbao Zhu, Aijun Ding

“…Based on measurement and modeling analysis, the impact of wildfire smoke on the development of a mid‐latitude cyclone was revealed for Canadian wildfires in early June of 2023. …”
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A novel hybrid CLARA and fuzzy time series Markov chain model for predicting air pollution in Jakarta by Nurtiti Sunusi, Ankaz As Sikib, Sumanta Pasari

“…Poor air quality increases risks of respiratory inflammation, tuberculosis, asthma, chronic obstructive pulmonary disease (COPD), pneumoconiosis, and lung cancer.In this context, developing reliable air pollution forecasting models is imperative for guiding effective mitigation strategies and policy interventions. …”
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Enhanced AdaBoostM1 with Multilayer Perceptron for Stock Price Prediction by Rebwar Mala Nabi, Soran AB. Saeed, Habibollah Haron

“…This study addresses these limitations by introducing an enhanced version of AdaBoostM1 (ADA), implemented on the Waikato Environment for Knowledge Analysis (WEKA) platform, to forecast stock prices using historical data. …”
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Distinct Modulations of Northwest Pacific Tropical Cyclone Precipitation by Atlantic Multidecadal Oscillation and Interdecadal Pacific Oscillation by Jiuwei Zhao, Ruifen Zhan, Daehyun Kim, Jong‐Seong Kug, Jingchao Long, Leying Zhang, Xiaofan Ma

“…These findings shed light on improving near‐term TCP forecast and its regional influence on East Asia.…”
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Shale Gas Transition in China: Evidence Based on System Dynamics Model for Production Prediction by Yingchao Chen, Yang Zhang

“…Subsequently, a causal loop diagram is constructed using the VENSIM software(VENSIM PLE 9.3.5 x64), a set of representative variables is selected, and the logical relationships among these variables are established through a multivariate statistical analysis, culminating in the development of a production forecasting model for China’s shale gas (stock and flow diagram). …”
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Prediction of suspended sediment concentration in fluvial flows using novel hybrid deep learning model by Sadra Shadkani, Yousef Hemmatzadeh, Amirreza Pak, Soroush Abolfathi

“…Six input scenarios incorporating lagged parameters were evaluated using performance metrics, including the correlation coefficient (CC), Nash–Sutcliffe efficiency (NSE), scatter index (SI), and Willmott’s index (WI). Sensitivity analysis identified SSCt-1 (i.e., one day before) as the most influential predictor for short-term forecasting. …”
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Earthquakes in Turkey and Syria in 2023 and geodynamics of the Caucasus-Anatolian region by V. B. Svalova

“…The formation and evolution processes of geological structures in complex geodynamic settings, as well as the forecasting and prognosis of natural hazards, required an analysis of all available geological and geophysical data. …”
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MODELING COOKING OIL PRODUCTION WITH CRUDE PALM OIL (CPO) PRICE USING TRANSFER FUNCTION by Gusmi Kholijah, Corry Sormin, Gusmanely.Z Gusmanely.Z

“…The stages of analysis are forming an ARIMA model, processing input time series whitening, and output time series whitening. …”
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Study protocol for a randomised, phase II, double-blind, experimental medicine study of obinutuzumab versus rituximab in ANCA-associated vasculitis: ObiVas by Simon Bond, Rachel B Jones, Rona M Smith, Kim Mynard, David R Jayne, Matthew Coates, Dominic Paul McGovern, Mark E McClure, Marcos Martinez Del Pero, Jacinta Lee, Menna Ruth Clatworthy

“…Trial results will be disseminated to the relevant scientific, clinical and patient communities on trial closure. NALT data analysis will start before trial completion. Other analyses will be reported after trial completion. …”
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Machine Learning-Based Prediction of Summer Extended-Range Precipitation and Possible Contribution of Soil Moisture over China by Yuchen YE, Haishan CHEN, Siguang ZHU, Yinshuo DONG

“…Low accuracy of extended forecast remains an important scientific problem in the current stage， and qualified extended forecast is of great significance for disaster prevention and mitigation.In this study， the machine learning method was used to forecast the summer precipitation during the extension period （5~30 days） in China， and explore the possible contribution of soil moisture to extended forecast of precipitation.Based on the results， machine learning methods remarkably outweigh traditional linear models in terms of forecast accuracy， with Catboost， Lightgbm and Adaboost being the optimal machine learning methods.According to further analysis， the abnormal evaporation and sensible heat anomaly caused by the surface soil moisture anomaly in the Yangtze River Basin can lead to the atmospheric circulation and vertical movement anomaly， which eventually affects summer precipitation.The set of three optimal machine learning methods was applied to calculate the contribution rate of each forecasting factor in the model.It was found that the local soil moisture dominated the extended precipitation in the Yangtze River Basin from the 5th day to the 10th day， while the local soil moisture played a dominant role on previous precipitation from the 10th day to the 15th day， and the extended precipitation in the Yangtze River Basin during the period of Day 20~30 was basically controlled by large-scale circulation.Besides， the influence of non-local soil moisture on extended precipitation was evaluated， the results of which showed that the surface soil moisture in Indo-China Peninsula mainly contributed to the extended precipitation in the Yangtze River Basin from the 15th day to the 30th day.By adding the surface soil moisture of Indo-China Peninsula to the extended precipitation model in Northeast China， it was found that surface the soil moisture failed to improve the extended forecast accuracy of precipitation in this area， which verified the availability of the machine learning model.This study provides a certain reference for forecasting precipitation in the extended period and exploring the contribution rate of forecasting factors.…”
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P-V-L Deep: A Big Data Analytics Solution for Now-casting in Monetary Policy by Maryam Hajipour Sarduie, Mohammadali Afshar Kazemi, Mahmood Alborzi, Adel Azar, Ali Kermanshah

“…The development of new technologies has confronted the entire domain of science and industry with issues of big data's scalability as well as its integration with the purpose of forecasting analytics in its life cycle. In predictive analytics, the forecast of near-future and recent past - or in other words, the now-casting - is the continuous study of real-time events and constantly updated where it considers eventuality. …”
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Synoptic-Scale Precursors to Tropical Cyclone Rapid Intensification in the Atlantic Basin by Alexandria Grimes, Andrew E. Mercer

“…Forecasting rapid intensification (hereafter referred to as RI) of tropical cyclones in the Atlantic Basin is still a challenge due to a limited understanding of the meteorological processes that are necessary for predicting RI. …”
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Water quality index modelling and its application on artificial intelligence (AI) in conjunction with machine learning (ML) methodologies for mapping surface water potential zones... by Abhijeet Das

“…Subsequently, irrigation parameters showed that the model as a whole did a good job of forecasting the suitability of irrigation. Based on the outcomes of RMSE, R2, Adjusted R2, MAPE, AIC and BIC, the GB and Cat B outperformed the AB model.For the purpose to achieve consistent and favourable outcomes in irrigation forecasting with surface water suitability, the current research suggests merging modelling approaches from Cat B, GB, and AB. …”
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Genetic characterization of type 3 vaccine-derived poliovirus from a patient with hand, foot, and mouth disease in China by Wei Zhang, Dongmei Yan, Hanri Zeng, Lei Zhou, Huanying Zheng, Shuangli Zhu, Yong Zhang, Baisheng Li

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The characterization, mechanism, predictability, and impacts of the unprecedented 2023 Southeast Asia heatwave by Yang Lyu, Jingyu Wang, Xiefei Zhi, Xianfeng Wang, Hugh Zhang, Yonggang Wen, Edward Park, Joshua Lee, Xia Wan, Shoupeng Zhu, Duc Tran Dung

“…This study provides a comprehensive analysis of this event by investigating its spatiotemporal evolution, physical mechanisms, forecast performance, return period, and extensive impacts. …”
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CNN-LSTM Model Optimized by Bayesian Optimization for Predicting Single-Well Production in Water Flooding Reservoir by Lei Zhang, Hongen Dou, Kun Zhang, Ruijie Huang, Xia Lin, Shuhong Wu, Rui Zhang, Chenjun Zhang, Shaojing Zheng

“…The experiment results show that the prediction accuracy of the proposed model is over 90%, which suggests a penitential application in an extensive range of applications. Production forecasting by the developed model is simple, efficient, and accurate, which can provide a guidance for the dynamic analysis of a water flooding reservoir, and work as a good reference of the development and production of other types of reservoirs.…”
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