An adaptive non-equidistant grey model with four parameters and its applications in deformation monitoring by Shuang Yang, Changchun Li, Jiao Fu, Huanqin Ma

“…Abstract The processing and analysis of deformation monitoring data, as well as the establishment of effective forecasting models, form the foundation for assessing whether deformation is within a safe range and for selecting appropriate preventive and disaster reduction measures. …”
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Estimating building height using scene classification and spatial geometry by Yonghua Jiang, Jingxin Chang, Yunming Wang, Shaodong Wei, Deren Li

“…This study introduces a novel method for estimating building height by integrating scene classification with spatial geometric relationships. Initially, raw data are processed to derive the various data types required for this approach. …”
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Biodegradable Composite of Gelatin Blend Microcrystalline Cellulose for Cd2+, Pb2+, and Cr3+ Adsorption from an Aqueous Solution by Marzia Sultana, Md. Raju Ahmmed, Md Inzamam Ul Hoque, Tanvir Ebna Mohsen, Atol Mondal, Md. Hafezur Rahaman, Moumita Yesmin, Md. Shahedur Rahman, S. M. Nur Alam

“…Different functional groups in composite adsorbent facilitated heavy metal ions adsorption. Five error analysis methods were used to evaluate the fit the goodness of the data. …”
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Comparison of artificial intelligence approaches for estimating wind energy production: A real-world case study by Mohamed Bousla, Mohamed Belfkir, Ali Haddi, Youness El Mourabit, Badre Bossoufi

“…The present work investigates several forecasting methodologies for wind energy by employing sophisticated machine learning algorithms, including Support Vector Machines and Recurrent Neural Networks. The analysis utilizes temporal data obtained at 10-minute intervals over a span of two years from a wind farm located in Morocco. …”
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Investigation of the effect of courage behaviors on endurance levels of canoe athletes by Serkan Hacıcaferoğlu, Levent Tanyeri, Orhan T. Emniyet

“…T-test and ANOVA test were used in the analysis of the data. Statistically, the error level was accepted as p<.05 and the significance level was Alpha (α). …”
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Structural time series modelling for weekly forecasting of enterovirus outpatient, inpatient, and emergency department visits. by Cathy W S Chen, Leon L Hsieh, Betty X Y Chu

“…This study utilizes Taiwan CDC databases to analyse weekly enterovirus case data from emergency departments (EDs), as well as outpatient and inpatient settings. …”
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An Improved Phase Space Reconstruction Method-Based Hybrid Model for Chaotic Traffic Flow Prediction by Yue Hou, Da Li, Di Zhang, Zhiyuan Deng

“…Traffic flow is chaotic due to nonstationary realistic factors, and revealing the internal nonlinear dynamics of chaotic data and making high-accuracy predictions is the key to traffic control and inducement. …”
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Enhancing cardiovascular monitoring: a non-linear model for characterizing RR interval fluctuations in exercise and recovery by Matías Castillo-Aguilar, Diego Mabe-Castro, David Medina, Cristian Núñez-Espinosa

“…Validation against real-world RRi data demonstrated robust model performance (R 2 = 0.868, CI95%[0.834, 0.895] and Root Mean Square Error [RMSE] = 32.6 ms, CI95%[30.01, 35.77]), accurately reflecting autonomic recovery and exercise-induced fluctuations. …”
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Improve Quality Factor by Using DWDM Technology for Long Distances and Different Power Levels by Mariam lazem, Ali Mahdi Hammadi, Ali Al-Askery

“… In optical fiber communications, data travels from the transmitter to the receiver, where it is collected and converted from optical pulses into electrical signals. …”
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LET-SE2-VINS: A Hybrid Optical Flow Framework for Robust Visual–Inertial SLAM by Wei Zhao, Hongyang Sun, Songsong Ma, Haitao Wang

“…The proposed method processes Inertial Measurement Unit (IMU) data and camera data, utilizing pre-integration and RANdom SAmple Consensus (RANSAC) for precise feature matching. …”
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Short-Term Electricity Load Forecasting Based on Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Improved Sparrow Search Algorithm–Convolutional Neural Netwo... by Han Qiu, Rong Hu, Jiaqing Chen, Zihao Yuan

“…By the optimization of the ISSA to the parameters of the CNN-BiLSTM model, integrating the prediction results of the reconstructed IMFs in the sub-models can obtain the final prediction result of the data. Through the performance indexes of the designed prediction model, the application case results show that the proposed combined prediction model has a smaller prediction error and higher prediction accuracy than the eight comparison models.…”
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Comparison of Nonlinear Models for Describing the Growth Curve of Pekin Ducks by Navid Ghavi Hossein‐Zadeh

“…The overall goodness‐of‐fit for each model to a variety of data profiles was determined through the application of the adjusted coefficient of determination, root mean square error, Akaike's information criterion and Bayesian information criterion. …”
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Assessing Climate Change Impacts on Cropland and Greenhouse Gas Emissions Using Remote Sensing and Machine Learning by Nehir Uyar, Azize Uyar

“…This study investigated the impact of grassland and cropland expansion on carbon (C) and nitrous oxide (N₂O) emissions using remote sensing data and machine learning models. The research focused on agricultural land-use changes in South Sumatra from 1992 to 2018, utilizing Landsat satellite imagery and Google Earth Engine (GEE) for spatial and temporal analysis. …”
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Research on sentiment index and real estate demand forecasting based on BERT-BiLSTM and ADL-MIDAS models by Mengkai Chen, Jun Wang, Feilong Zhao, Gaopeng Jiang

“…Simultaneously, Internet Concern index is constructed using Baidu search data as a non-directional sentiment proxy variable. …”
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Spatial clustering between socioeconomic inequalities and COVID-19 mortality rate in Africa by Ropo Ebenezer Ogunsakin, Johnson Adedeji Olusola, Kemi Funlayo Akeju, Adigun Kehinde Abimbola

“…The data were analysed by applying spatial analysis, including the Moran-I index, the Local Indicator of Spatial Association (LISA), and spatial regression models, to study the spatial variations in the effects of socioeconomic indicators on COVID-19 mortality at the country level. …”
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Machine Learning-Based Prediction Performance Comparison of Marshall Stability and Flow in Asphalt Mixtures by Muhammad Farhan Zahoor, Arshad Hussain, Afaq Khattak

“…The potential of various machine learning (ML) algorithms to predict Marshall Stability (MS) and Marshall Flow (MF) was investigated in this work. We collected data from published studies in the literature encompassing 732 data points to train and evaluate ML models. …”
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Modelling the Thin-Layer Drying Kinetics of Untreated and Blanch-Osmotic Pre-treated Tomato Slices by Samuel Enahoro Agarry

“…Four semi-empirical drying models of Newton, Page, Henderson and Pabis, and Logarithmic were fitted to the drying data using non-linear regression analysis. The most appropriate model was selected using the coefficient of determination (R2) and root mean square error (RMSE). …”
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Psychological consultation apps in Saudi Arabia: A study for experts' evaluation and users' points of view. by Abdulmohsen Saud Albesher, Maymunah Faheem Alwahib

“…User reviews were collected using Heedzy, an online tool designed for extracting reviews from mobile apps. Data cleaning was performed using Python libraries, which handled missing data and removed duplicate entries. …”
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Current practices for assessing usability of novel point-of-care diagnostics for infectious diseases: a scoping review protocol by Claudia Denkinger, Sonjelle Shilton, Elena Ivanova Reipold, Seda Yerlikaya, Maria del Mar Castro, Horeya M Ismail, Carlos Alberto Montenegro-Quiñonez

“…Applying usability and human factors engineering principles can reduce the challenges related to human errors. Despite existing frameworks and tools, the practical application of usability guidelines remains variable across different settings.Methods and analysis This scoping review protocol outlines a systematic investigation of current practices in assessing the usability of novel diagnostics, particularly POC tests for infectious diseases intended for use in low-income and middle-income countries. …”
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Resistivity imaging and uncertainty assessment of volcanic covered sedimentary basins of India derived from a new strategy by Jit Varish Tiwari, Kuldeep Sarkar, Upendra K. Singh

“…Instead of selecting the global model with the lowest error, we used Bayesian posterior probability density function (PDF) to reconstruct models. …”
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