Study on cutting force in laser-assisted ultrasonic elliptical vibration machining (LUEVM) of high volume SiCp/Al composites by Peicheng Peng, Tian Tian, Heshuai Yu, Daohui Xiang, Ke Niu, Wei Gao, Yanqin Li, Zhaojie Yuan, Guofu Gao

“…The results show that the predicted value matches the experimental value well, and the maximum error is 18.2 %. …”
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A Hybrid Model Based on Ensemble Empirical Mode Decomposition and Fruit Fly Optimization Algorithm for Wind Speed Forecasting by Zongxi Qu, Kequan Zhang, Jianzhou Wang, Wenyu Zhang, Wennan Leng

“…In this model, the original wind speed data is firstly divided into a finite set of signal components by ensemble empirical mode decomposition, and then each signal is predicted by several artificial intelligence models with optimized parameters by using the fruit fly optimization algorithm and the final prediction values were obtained by reconstructing the refined series. …”
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COMPARISON OF WEIGHTED MARKOV CHAIN AND FUZZY TIME SERIES-MARKOV CHAIN METHODS IN AIR TEMPERATURE PREDICTION IN BANDA ACEH CITY by Siti Rusdiana, Diana Febriana, Ikhsan Maulidi, Vina Apriliani

“…The prediction results of air temperature in Banda Aceh city using the FTS-MC method for the next three weeks obtained predicted values of 26,66℃ for the 105th week, 26,79℃ for the 106th week, and 26,83℃ for the 107th week. …”
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Optimizing Concrete Mix Design for Cost and Carbon Reduction Using Machine Learning by Angga T. Yudhistira, Arief S. B. Nugroho, Iman Satyarno, Tantri N. Handayani, Malindu Sandanayake, Rimba Erlangga, Jonathan Lianto, Alfa Rosyid Ernanto

“…The research findings indicate that the ML model provides satisfactory prediction values with an R2 value of 0.9043, root mean square error of 48.5147 and mean absolute percentage error of 0.0484. …”
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Methodology Based on BERT (Bidirectional Encoder Representations from Transformers) to Improve Solar Irradiance Prediction of Deep Learning Models Trained with Time Series of Spati... by Llinet Benavides-Cesar, Miguel-Ángel Manso-Callejo, Calimanut-Ionut Cira

“…In this study, we propose a novel end-to-end methodology for solar irradiance forecasting that starts with the search for the data and all of the preprocessing operations involved in obtaining a quality dataset, continuing by imputing missing data with the BERT (Bidirectional Encoder Representations from Transformers) model, and ending with obtaining and evaluating the predicted values. This novel methodology is based on three phases; namely, Phase_1, related to the acquisition and preparation of the data, Phase_2, related to the proposed imputation with a BERT model, and Phase_3, related to the training and prediction with new models based on deep learning. …”
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ST-GAT Resident OD Prediction Model Based on Mobile Signaling Data by Xianguang Jia, Weijie Fang, Yingying Lyu, Jinke Zhang, Mengyi Guo, Dong Li, Jie Qu, Fengxiang Guo

“…In this paper, this model is compared with the existing ST-GCN, DMS, GMM, PSAM-CNN, ST-Transformer, and COMD models, and the experimental results show that the predicted values of the ST-GAT model have a significant improvement in the prediction accuracy compared to other models. …”
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Investigating Engine Performance and Emission Characteristics during Testing of Diesel-Biodiesel Mixed Fuels Obtained from Vegetable Oils and their Modeling by S. R. Mousavi Seyedi, M. Askari, S. M. R. Miri

“…However, ANFIS demonstrated a much higher correlation between actual and predicted values, with R² exceeding 0.98 for both performance parameters and emissions, compared to R² values below 0.47 for linear regression and below 0.92 for non-linear regression. …”
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Experiment of Pullout Expansion Anchor in Installation Cast in Place and Post Installed with Concrete Breakout Failure by Amirul Huda, Henry Apriyatno

“…The result of the study is the predicted value of the anchor pullout capacity with the failure of concrete breakout due to the theoretical pullout, namely 42,223 N, anchor pullout test results with cast in place method of 40,574 N and post installed method by 37,494 N. …”
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Financial Interrelations of scenario Indicators of budget Forecasting with Indicators of the Federal budget of Russia by M. E. Kosov, E. K. Voronkova, A. Yu. Chalova

“…The study is based on an abstract-logical method, including a critical analysis of the predictive values of macro-indicators adopted as the basis for the parameters of the federal budget of the Russian Federation in 2023 and the planned period of 2024 and 2025 (using the level of consumer prices and the exchange rate of the ruble as an example), establishing causal relationships between the reliability of projected budget parameters at the federal level and the state of the Russian economy, identifying possible directions for the development of approaches to forecasting initial indicators for the preparation of the federal budget. …”
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Design and analysis of parameter optimization on development of corn straw fiber composition by ultrasound with alkalization pretreatment by SHEN Weizheng, QU Tengyu, WEI Xiaoli, MU Yingxin

“…The relative errors of actual values and predicted values were less than 13%, 12% and 14%, respectively. …”
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Evaluation of Short-Term Use of Positive and Oscillating Positive Expiratory Pressure in Bronchial Drainage in Cystic Fibrosis Patients During an Exacerbation of The Disease by Jarosław Prusak, Katarzyna Warzeszak, Piotr Kurzeja

“…In the study group, a 4-day bronchial drainage cycle was used.Results: The FEV1 indicator for the whole group was 55.623% of the predicted value, and the size of the improvement, similarly to FVC and MEF25, was statistically significant (p<0.001). …”
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Nasal microbiota predictors for methicillin resistant Staphylococcus colonization in critically ill children. by Kathleen Zani, Joseph Hobeika, Yilun Sun, Christina Kohler, Anju Cherian, Trinity Fields, Qidong Jia, Li Tang, Nicholas D Hysmith, Elisa B Margolis

“…Anterior nares nasal swabs processed for MRSA culture, nasal microbiome and mecA+ qPCR were obtained within first five days after PICU admission. Predictive values of methicillin-resistant Staphylococcus carriage on symptoms of infection and for nasal microbiome attributes were calculated.…”
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Optimization of solvent evaporation method in liposomal nanocarriers loaded‐garlic essential oil (Allium sativum): Based on the encapsulation efficiency, antioxidant capacity, and... by Salar Ali Ahmed, Mahmood Fadhil Saleem, Hamed Hassanzadeh

“…The overall optimum conditions were determined by response surface methodology (RSM) as the predicted values of the studied factors (sonication time: 18.99 min, CHLR: 0.59 and content of GEO: 0.3 g/100 g) based on obtaining the highest stability and efficiency as well as strongest antioxidant and antimicrobial activity.…”
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Determination of osmotic resistance of erythrocytes using flow cytometry in patients with hereditary spherocytosis by E. F. Mitsura, Zh. N. Pugacheva, L. I. Volkova

“…Diagnostic sensitivity of the test is 93.9 %, specificity 83.3 %, positive and negative predictive values 86.1 and 92.6 %, respectively. It was found that the method with proposed reference intervals allows evaluating the osmotic resistance of erythrocytes fast and objectively, and can be used for differential diagnosis in hereditary spherocytosis.…”
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Effectiveness of two rapid influenza tests in comparison to reverse transcription-PCR for influenza A diagnosis by Ramón Zazueta-García, Adrian Canizalez-Roman, Hector Flores-Villaseñor, Javier Martínez-Garcia, Alejandro Llausas-Vargas, Nidia León-Sicairos

“…Results: The sensitivity, specificity, and positive and negative predictive values obtained for the DFA were 68.97%, 76.63%, 75.47%, and 70%, respectively, while the values obtained for the immunochromatographic assay were 58.62%, 81.82%, 77.27%, and 65.22%, respectively. …”
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Urea application to improve the efficiency of hydrochloric acid treatments of carbonate reservoirs by Roman A. Vaganov, Vladimir A. Zhigarev, Svetlana S. Kositsyna, Daniil D. Chernykh

“…They assessed the expected effect from the use of urea in hydrochloric acid treatments of carbonate reservoirs and the predicted values of the increase in oil production after hydrochloric acid treatments with urea. …”
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Estimation of micro-extraction process hippuric acid for toluene exposure monitoring in urine samples by Behnaz Sarani, Mashaallah Rahmani, Ahmad Reza Abbasian

“…The suggested model showed strong validation, evidenced by adjusted R² = 0.9888, high recovery rates, low error in confirmation runs (1.37–2.09%), and consistent predicted values. The model demonstrated satisfactory recovery rates, emphasizing its potential for analyzing urine samples as an indicator of toluene exposure. …”
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Performance analysis of advanced deep learning technics: Application to solar energy forecasting and management in several cities in Chad by Osée Mounkang, Claude Vidal Aloyem Kaze, Nzoko Tayo Dieudonné, Ghislain Junior Bangoup Ntegmi, Duclair Paul Edouard Pountounynyi, Hervice Roméo Fogno Fotso, Armel Zambou Kenfack, Germaine Kenmoe Djuidje, René Tchinda

“…Additionally, the predicted values were used to calculate the power output of a photovoltaic (PV) system, as well as its efficiency and the energy that could be stored. …”
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Morphology-based selective breeding strategy analysis for abdominal meat yield in Procambarus clarkii by Qishuai Wang, Qian Hu, Siqi Yang, Ruixue Shi, Feifei Zheng, Xiaolong Liu, Jiangfeng Huang, Yanhe Li

“…And the optimal prediction model constructed based on K value was a quadratic curve, with R2 values of 0.684 for males and 0.590 for females, and correlation coefficients of 0.827 and 0.768 between observed and predicted values for males and females, respectively. The results of the abdominal meat yield selective breeding experiment, utilizing the optimal prediction model, demonstrated that the breeding population exhibited favorable morphological variation as expected. …”
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Extraction Optimization and Antioxidant Properties of African Eggplant (Solanum macrocarpon) Leaf Polyphenols by A. A. Famuwagun, K. A. Taiwo, S. O. Gbadamosi, D. J. Oyedele, R. E. Aluko, O. C. Adebooye

“…The study concludes that the experimental values compared closely with the predicted values, which indicates suitability of the model employed for polyphenol extraction optimization from dried S. macrocarpon leaves.…”
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