Climate variability and its impact on sanitation facility choice in Ethiopia by Bahre Gebru, Katarina Elofsson, Franklin Amuakwa-Mensah, George Marbuah

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The effect of macroeconomic variables on non performance financing of Islamic Banks in Indonesia by Latifah Dian Iriani, Imamudin Yuliadi

“…Research methodology used at this study is Vector Error Correction Model (VECM). Following these procedures, it applies Unit Roots Test, Augmented Dickey Fuller Test, Lag Length Criteria Test, Correlation Matrix – Johansen Julius Co-integration Test, VECM Estimation, Impulse Response and Variance Decomposition Test. …”
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The effect of macroeconomic variables on non performance financing of Islamic Banks in Indonesia by Latifah Dian Iriani, Imamudin Yuliadi

“…Research methodology used at this study is Vector Error Correction Model (VECM). Following these procedures, it applies Unit Roots Test, Augmented Dickey Fuller Test, Lag Length Criteria Test, Correlation Matrix – Johansen Julius Co-integration Test, VECM Estimation, Impulse Response and Variance Decomposition Test. …”
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Optimizing Vehicle Scheduling Based on Variable Timetable by Benders-and-Price Approach by Zekang Lan, Shiwei He, Rui Song, Sijia Hao

“…A Benders-and-Price algorithm by combining the Benders decomposition and column generation is proposed to solve the LP-relaxation of the path-based model, and a bespoke Branch-and-Price is used to obtain the integer solution. …”
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Comprehensive Analysis of the Driving Forces Behind NDVI Variability in China Under Climate Change Conditions and Future Scenario Projections by Ao Li, Shuai Yin, Nan Li, Chong Shi

“…Firstly, this study decomposed the time series data into seasonal, trend, and residual components using the Seasonal–Trend decomposition using Loess (STL) decomposition method, quantifying vegetation changes across different climate zones. …”
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Variability in the volume transport of deep overflow across the 10°S saddle on the ninetyeast ridge by Shanwu Zhang, Fuwen Qiu, Hangyu Chen, Chunsheng Jing

“…These variabilities are attributed to vertically propagating Rossby waves originating from wind stress curl-induced Ekman pumping, which is demonstrated via spectral empirical orthogonal function decomposition of numerical model outputs and by ray tracing based on the dispersion relation for baroclinic Rossby waves. …”
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Prediction of the monthly river water level by using ensemble decomposition modeling by Chaitanya Baliram Pande, Lariyah Mohd Sidek, Bijay Halder, Okan Mert Katipoğlu, Jitendra Rajput, Fahad Alshehri, Rabin Chakrabortty, Subodh Chandra Pal, Norlida Mohd Dom, Miklas Scholz

“…Similarly, in the testing phase, the best two models performances are very well as a CEEMDAN-RF (R2:0.94) and CEEMDAN-RS (R2:0.90) in second combination variables, and the first combination variables based SVM- Linear (R2:0.93) and RF (R2:0.89) models are performance higher compared with other models. …”
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An Artificial Intelligence-Based Approach With Photoplethysmogram and Heart Rate Variability for Sleep Bruxism Diagnosis by Omer Eris, Mehmet Recep Bozkurt, Seval Bulut Eris, Cahit Bilgin

“…The models were optimized and tested using unseen data. …”
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Reliability Analysis of Three-dimensional Soil Slopes Considering Spatial Variability of Soil Parameters by Wan Yukuai, Zhou Yuqi, Shao Linlan, Wang Yuke, Zhang Fei

“…To address these limitations, this study employs the covariance matrix decomposition method to generate 3D lognormal random fields for soil parameters, enabling efficient modeling of spatial variability. …”
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Multidimensional Meteorological Variables for Wind Speed Forecasting in Qinghai Region of China: A Novel Approach by He Jiang, Luo Shihua, Yao Dong

“…However, available forecasting models focus on forecasting the wind speed using historical wind speed data and ignore multidimensional meteorological variables. …”
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Eigen‐Swarm: Swarm's Thermospheric Mass Density Modeling via Eigen‐Decomposition by Charles Owolabi, Hyunju Connor, Don Hampton, Denny M. Oliveira, Andres Calabia, V. Sai Gowtam, Eftyhia Zesta

“…We employ the Eigen‐Decomposition technique to extract dominant spatio‐temporal modes, with the first three capturing 99.12% of the variance, forming the basis of the Swarm‐based Eigen‐Decomposition model. …”
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The relationship between the inflation rate and the unemployment rate in Poland and their long-term associations with selected macroeconomic variables by Jan Koterwa, Hubert Kycia, Anna Czapkiewicz

“…The impulse response function and forecast error variance decomposition were also used to examine the interactions between variables. …”
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Evaluation of Eight Decomposition-Hybrid Models for Short-Term Daily Reference Evapotranspiration Prediction by Yunfei Chen, Zuyu Liu, Ting Long, Xiuhua Liu, Yaowei Gao, Sibo Wang

“…Accurate reference evapotranspiration (ET_o) prediction is important for water resource management, particularly in arid regions where water availability is highly variable. However, the nonlinear and non-stationary characteristics of ET_o time series pose challenges for conventional prediction models. …”
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Numerical benchmarking of dual decomposition-based optimization algorithms for distributed model predictive control by Vassilios Yfantis, Achim Wagner, Martin Ruskowski

“…This paper presents a benchmark study of dual decomposition-based distributed optimization algorithms applied to constraint-coupled model predictive control problems. …”
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A Hybrid Model for Carbon Price Forecasting Based on Secondary Decomposition and Weight Optimization by Yongfa Chen, Yingjie Zhu, Jie Wang, Meng Li

“…Secondly, a two-stage feature-selection method is employed, in which the partial autocorrelation function (PACF) is used to select relevant lagged features, while the maximal information coefficient (MIC) is applied to identify key variables from both historical and external data. Finally, this paper introduces a dynamic integration module based on sliding windows and sequential least squares programming (SLSQP), which can not only adaptively adjust the weights of four base learners but can also effectively leverage the complementary advantages of each model and track the dynamic trends of carbon prices. …”
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Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

“…Finally, the integrated prediction combining fluctuation and random terms under condition 5 yielded R2 of 0.87 and 0.93 for the overall prediction at Ankang and Baihe stations, respectively, demonstrating excellent model performance. [Conclusions](1) The MVMD decomposition method can control the number of decomposition layers, ensuring complete signal feature extraction without overfitting while improving processing speed.(2) Pearson correlation coefficient method enhances prediction accuracy through decomposed data classification.(3) The MEA-BP can improve signal-to-noise ratio, adapt to complex environments, enhance learning efficiency and generalization ability, and reduce computational complexity.(4) The GWO-ELM algorithm integrates grey wolf optimizer with extreme learning machine, providing a fast and adaptive solution for time-series prediction with reduced overfitting and improved efficiency.(5) The overall combined model can efficiently and stably process large amount of data while ensuring high accuracy.…”
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Spatial variability and convergence of the coupled relationship between agricultural carbon emission reduction and rural revitalization in China by Hongli Yang, Kai Feng

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Enhanced thermal performance of variable cross-section solar collectors: a case study in Santiniketan, India by Pranab Kanti Roy

“…Abstract We present analytical models for variable cross-section absorber plate solar collectors, where the thermal conductivity, overall heat loss coefficient, and incident solar heat flux are power-law functions of temperature. …”
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Future methane fluxes of peatlands are controlled by management practices and fluctuations in hydrological conditions due to climatic variability by V. Tyystjärvi, T. Markkanen, L. Backman, M. Raivonen, A. Leppänen, X. Li, P. Ojanen, P. Ojanen, K. Minkkinen, R. Hautala, M. Peltoniemi, J. Anttila, R. Laiho, A. Lohila, R. Mäkipää, T. Aalto

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Assessing the impact of macroeconomic variables on environmental quality in the MENA using logarithmic mean divisia and co-integration panel by Ali Afzali, Vahid Majed

“…In the first step, the share of each macroeconomic variables was investigated by using the Logarithmic Mean Divisia Index, Which is considered one of the most widely used decomposition techniques in the short term. …”
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