Smart material selection strategies for sustainable and cost-effective high-performance concrete production using deep learning by T. Seethalakshmi, M. Murugan, P. Maria Antony Sebastin Vimalan

“…MOAC-ADenseNet utilized Dense convolutional neural networks and ant colony optimization for complex material data analysis, which makes it easier to choose expensive and sustainable materials for high-performance concrete manufacturing operations. …”
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A Neural Network-Based Structural Parameter Assessment Method for Prefabricated Concrete Pavement by Yongsheng Tang, Yunzhen Lin, Tao Yu

“…However, as a new type of pavement structure, their structural analysis theory and actual structural performance have not been determined. …”
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Finding Reliability of Slopes by Optimization of ANFIS with GA, FFA and PSO by Jayanti Bharti, Pijush Samui

“…Some of the statistical errors such as Mean Square Error (MSE) values were 0.0148, 0.0182, 0.0159 in training and 0.1263, 0.0277 and 0.1289 in testing. …”
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High-resolution global modeling of wheat’s water footprint using a machine learning ensemble approach by Murat Emeç, Abdullah Muratoğlu, Muhammed Sungur Demir

“…The model achieved a mean absolute error (MAE) of 108.5 m3/t, mean squared error (MSE) of 239.9 m3/t, and mean absolute percentage error (MAPE) of 1.51, along with a high prediction accuracy evidenced by a test score of 98.49% and an R 2 value of 0.87. …”
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Shale volume estimation using machine learning methods from the southwestern fields of Iran by Parirokh Ebrahimi, Ali Ranjbar, Yousef Kazemzadeh, Ali Akbari

“…The models were evaluated based on performance metrics such as correlation coefficient (R2), average relative error (ARE), root mean square error (RMSE), and mean squared error (MSE). …”
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Impact of Uncertainties in Exposure Assessment on Thyroid Cancer Risk among Persons in Belarus Exposed as Children or Adolescents Due to the Chernobyl Accident. by Mark P Little, Deukwoo Kwon, Lydia B Zablotska, Alina V Brenner, Elizabeth K Cahoon, Alexander V Rozhko, Olga N Polyanskaya, Victor F Minenko, Ivan Golovanov, André Bouville, Vladimir Drozdovitch

“…Although the Belarus thyroid cancer prevalence data has been previously analyzed, no account was taken of dose measurement error.…”
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Aerodynamic model identification of supersonic aircraft using Bayesian approach-based Box–Jenkins structure by Muhammad Fawad Mazhar, Muhammad Wasim, Manzar Abbas, Imran Shafi, Jamshed Riaz, Tae-hoon Kim, Imran Ashraf

“…The proposed solution involves the construction of a discrete-time BJ model using a simulated input–output dataset generated from the Flight Dynamic Model of F-16 aircraft, followed by the reduced-order model using Bayesian information criteria and parameter optimization using Bayesian theorem. A closer analysis of results has been conducted through statistical techniques like residual analysis, best-fit percentage, fit percentage error, mean squared error, and model order. …”
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Enhanced prediction of heating value of municipal solid waste using hybrid neuro-fuzzy model and decision tree-based feature importance assessment by Oluwatobi Adeleke, Obafemi O. Olatunji, Tien-Chien Jen, Iretioluwa Olawuyi

“…Key waste properties, including ultimate analysis data, ash and moisture content were used as input variables for the model. …”
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A Preseason Training Program With the Nordic Hamstring Exercise Increases Eccentric Knee Flexor Strength and Fascicle Length in Professional Female Soccer Players by Karoline Baptista Vianna, Lívia Gonçalves Rodrigues, Nathalia Trevisol Oliveira, João Breno Ribeiro-Alvares, Bruno Manfredini Baroni

“… # Results The non-trained group’s data demonstrated that measures of strength (ICC=0.82-0.87, typical error = 12-13 N) and fascicle length (ICC=0.92-0.97; typical error = 0.19-0.38 cm) were reliable. …”
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Volatility Modelling of the Johannesburg Stock Exchange All Share Index Using the Family GARCH Model by Israel Maingo, Thakhani Ravele, Caston Sigauke

“…The models for volatility were fitted using five unique error distribution assumptions, including Student’s <i>t</i>, its skewed version, the generalized error and skewed generalized error distributions, and the generalized hyperbolic distribution. …”
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Emmetropia deviation in autorefraction compared to subjective refraction result in patients after corneal refractive surgery by Yuexin Wang, Zesong Wang, Yu Zhang, Yifei Yuan, Yan Liu, Shuo Yu, Ziyuan Liu, Chen Yueguo

“…Abstract Background Automatic refraction is commonly applied as a substitute for subjective refraction to evaluate residue refractive error after corneal refractive surgery. Previous research pooled the data from patients of different subgroups to calculate the difference between automatic and subjective refraction, which lacks clinical implications. …”
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ANALYZING HOW URBANIZATION IMPACTS ECONOMIC GROWTH IN NIGERIA by Ahmed Oluwatobi Adekunle

“…Essentially, the study uses unit root testing, vector error correction model (VECM) and causality method to analyze the data span over 1986-2021. …”
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Some hypotheses regarding the mobile telecommunications services marketing and consumers rights from Romania by Nicu Marcu, Georgeta-Mădălina Meghişan

“…The current research analysis consumers’ rights concerning personal data processing and confidentiality protection within the public communications sector as they are stated in the 2002/58/CE Directive of the European Parliament and Council from 12th of July 2002. …”
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FY-3C/VIRR Sea Surface Temperature Products and Quality Validation by Wang Sujuan, Cui Peng, Zhang Peng, Yang Zhongdong, Hu Xiuqing, Ran Maonong, Liu Jian, Lin Manyun, Qiu Hong

“…Causes of FY-3C/VIRR SST products anomaly is analyzed, such as L1 data abnormal (e.g., single event upset), navigation error and operational running environmental error. …”
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Development of Advanced Machine Learning Models for Predicting CO₂ Solubility in Brine by Xuejia Du, Ganesh C. Thakur

“…Among these, XGBoost demonstrated the highest overall accuracy, achieving an R² value of 0.9926, with low root mean square error (RMSE) and mean absolute error (MAE) of 0.0655 and 0.0191, respectively. …”
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A dynamic prediction model of landslide displacement based on VMD–SSO–LSTM approach by Haiying Wang, Yang Ao, Chenguang Wang, Yingzhi Zhang, Xiaofeng Zhang

“…Abstract Addressing the limitations of existing landslide displacement prediction models in capturing the dynamic characteristics of data changes, this study introduces a novel dynamic displacement prediction model for landslides. …”
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Methods and Evaluation of AI-Based Meteorological Models for Zenith Tropospheric Delay Prediction by Si Xiong, Jiamu Mei, Xinchuang Xu, Ziyu Shen, Liangke Huang

“…The findings reveal that AI-driven models, particularly Fengwu, offer higher long-term forecasting accuracy. An analysis of data from 81 stations throughout 2023 indicates that Fengwu’s 7-day ZTD forecast achieved an RMSE of 2.85 cm when compared to GNSS-derived ZTD. …”
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A DNN-based 5G MIMO system adopting a mix of tactics by Md. Matiqul Islam, Md. Ashraful Islam, Md. Firoz Ahmed

“…Simulation results indicate that the LDPC coding technique significantly outperforms polar coding across all evaluated QAM modulation orders, highlighting its effectiveness in enhancing system performance. An analysis of BER and spectral efficiency demonstrates considerable reliability and data throughput improvements, making the MIMO system particularly well-suited for the demanding requirements of 5G applications. …”
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Modelling of carbon dioxide absorption in hollow fiber membrane contactor for different flow configurations by E.L.H. Ng, K.K. Lau, S.S.M. Lock

“…The succession of states method was proposed to model the membrane module, which showed good agreement when validated against experimental data (⩽14.9 % error). Comparison between the two configurations were conducted based on varying gas and liquid flow rates, number of fibers and inlet CO2 compositions. …”
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Outdoor FSO Communications Under Fog: Attenuation Modeling and Performance Evaluation by Maged Abdullah Esmail, Habib Fathallah, Mohamed-Slim Alouini

“…Furthermore, we studied the performance of the FSO system addressing various performance metrics, including signal-to-noise ratio (SNR), bit-error rate (BER), and channel capacity. Our results show that in communication environments with frequent fog, FSO is typically a short-range data transmission technology. …”
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