An evolutionary-based optimization algorithm for truss sizing design by Pham Hoang Anh

“…Here, the constraints and objective function are treated separately so that both function and constraint evaluations can be saved. …”
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Optimum Design of RC Beams Strengthened with Externally Bonded FRP Using Pattern Search by Noor Mohammed Sheet, Baraa J. M. AL-Eliwi, Rabi M. Najem

“…The design process involved an objective function that represents the cost function of the optimum solution and design variables that define the optimum dimensions of the beam and FRP material, such as beam width, effective beam depth, FRP strip thickness, FRP strips spacing, and FRP strip width, according to the design constraints of the ACI 440-2R-17 code. …”
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Replacing GRACE/GRACE‐FO C30 With Satellite Laser Ranging: Impacts on Antarctic Ice Sheet Mass Change by Bryant D. Loomis, Kenneth E. Rachlin, David N. Wiese, Felix W. Landerer, Scott B. Luthcke

“…The C30 coefficient, which has a large impact on the recovered Antarctic Ice Sheet mass changes, is shown here to be poorly observed by GRACE/GRACE‐FO when either mission is operating without two fully functional accelerometers. …”
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The Effect of Rural Guide Plan on Objective Quality of Life among Rural Communities in Fariman County by Aliakbar Anabestani, Hamdollah Sojasi Qeidari, Fahime Jafari

“…According to the results of Pearson's correlation tests, the findings of present study showed a significant and strong correlation between implementation of rural guide plan and the mental facet of life quality by a 0.75 correlation coefficient, so that rural guide plan explained 57% of the variation of dependent variable, and among guide plan dimensions the changing environmental rural affected the objective improvement of life quality of villagers by 29 percent. …”
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定中心距齿轮参数优化设计 by 李云鹏, 张科, 邓晓丽

“…Under the constant center distance conditions,according to the use of the transmission system requirements,selection of the appropriate design variables,constraint conditions and the objective function and using the complex method,the tooth parameters optimization design is carried out.Through the program,the optimized tooth parameter is calculated,the design efficiency is improved.…”
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A robust deep learning approach for photovoltaic power forecasting based on feature selection and variational mode decomposition by Mokhtar Ali, Abdelkerim Souahlia, Abdelhalim Rabehi, Mawloud Guermoui, Ali Teta, Imad Eddine Tibermacine, Abdelaziz Rabehi, Mohamed Benghanem

“…To further enhance model inputs, Variational Mode Decomposition (VMD) is applied to extract informative Intrinsic Mode Functions (IMFs) from the selected features. A comparative evaluation of the models indicates that recurrent neural networks, particularly GRU and LSTM, deliver superior performance across various metrics, including RMSE, MAE, nRMSE, nMAE, R², and the correlation coefficient. …”
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Model of the Connecting Optimal Number of Heat Consumers by Sergey M. Terekhov, Vladimir A. Nemtinov, Kirill S. Kornilov

“…The economic status of all participants in the heat supply process depends on the efficiency of the functioning of the heat supply systems. …”
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Impact of Low-dose Imaging on PET Quantitative Accuracy and Image Quality by SU Xuesong, GENG Jianhua, ZHENG Rong, WANG Xuejuan

“…Subsequently, the recovery coefficient (RC), contrast recovery coefficient (CRC), contrast-to-noise ratio (CNR), percent background variability (PBV), background coefficient of variation (BCV), and residual error (RE) of the lung insert at different image planes were calculated within the phantom. …”

DC Performance Variations of SOI FinFETs with Different Silicide Thickness by Jun-Sik Yoon

“…DC parameters including threshold voltage, low-field-mobility-related coefficient, and parasitic resistance are extracted from Y-function method for the comparison of DC performance and variability, and the correlation analysis. …”
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UNFOLDING FACTORS INFLUENCING PINEAPPLE PRODUCTION: EMPIRICAL EVIDENCE FROM BAGAMOYO IN TANZANIA by Isaka Kasyupa, Bahati Ilembo

“…The coefficient of determination 𝑅 ଶ = 0.81 showed that the explanatory variables were fit for the model as 81% of the variation in the production of pineapples is explained by the selected seven factors. …”
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Active RIS-NOMA Uplink in URLLC, Jamming Mitigation via Surrogate and Deep Learning by Ghazal Asemian, Mohammadreza Amini, Burak Kantarci

“…The complexity of the optimization problem, involving numerous interacting variables, leads us to develop a deep regression model to predict optimal network configurations, providing a computationally efficient approach as well as reducing the signaling overhead. …”
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Prox-STA-LSTM: A Sparse Representation for the Attention-Based LSTM Networks for Industrial Soft Sensor Development by Yurun Wang, Yi Huang, Dongsheng Chen, Longyan Wang, Lingjian Ye, Feifan Shen

“…For deep learning based soft sensors, the spatiotemporal attention (STA)-LSTM is a newly emerged technique which provides efficient predictions for quality variables of industrial processes. …”
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Calculation and Forecast of Glacial Feeding in River Basins by V. G. Konovalov

“…Index δ for the upper reaches of the Rhone River turned out to be not only a representative characteristic of changes in the vegetation period and annual runoff of the river, but also an efficient argument for the super-long-range prediction of these variables for 2025–2054 years.…”
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Numerical Investigation and Optimization of Transpiration Cooling Plate Structures with Combined Particle Diameter by Dan Wang, Yaxin Liu, Xiang Zhang, Mingliang Kong, Hanchao Liu

“…An optimization analysis of CPD−PS is conducted using response surface methodology (RSM), and the influence of design variables on the objective function (<i>η</i>_ave and <i>p</i>) is analyzed. …”
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Comparative Analysis of ANFIS and State-ANFIS for Forecasting Cooking Oil Prices Based on Processed Palm Oil Yield (Crude Palm Oil) by Brodjol Sutijo Suprih Ulama, Fausania Hibatullah, Mochammad Reza Habibi, null Makkulau

“…Our analysis underscores S-ANFIS’s superiority over ANFIS, particularly with Gaussian membership functions, as it reduces RMSE and MAPE values by half while requiring fewer nodes, thereby improving computational efficiency. …”
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Research on the Combined Load-Bearing Mechanism of Deeply Buried Pressure Pipelines Under High Internal Water Pressure by LIU Yijie, ZHANG Xuhui, HUANG Bensheng, YANG Fengjie, YUAN Mingdao, XU Yunqian

“…To enhance the surrounding rock’s contribution, reinforcement measures such as grouting may be necessary.ConclusionsAiming at the calculation problem of load transfer and distribution in deep-buried pressure pipelines under high internal water pressure conditions, a power series solution method based on complex variable functions was proposed. By solving the potential functions for the steel liner and surrounding rock as well as the contact stress between the bearing bodies, the stress, deformation at any position of the bearing structure and surrounding rock sharing rate can be accurately determined. …”
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Intelligent wearable devices with audio collection capabilities to assess chronic obstructive pulmonary disease severity by Chunbo Zhang, Kunyao Yu, Zhe Jin, Yingcong Bao, Cheng Zhang, Jiping Liao, Guangfa Wang

“…A logistic regression model using the RR and blowing sounds as key predictors achieved accuracies of 0.77–0.89 in determining the GOLD grade, with a Cohen's kappa coefficient of 0.6757. Conclusions Audio data were more strongly correlated with lung function in COPD patients than were physiological parameters. …”
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Fractional Dynamics of Laser-Induced Heat Transfer in Metallic Thin Films: Analytical Approach by M. A. I. Essawy, Reham A. Rezk, Ayman M. Mostafa

“…Dynamic profiles demonstrate the responsiveness of heat transfer to thermal and optical variables. The innovation resides in the meticulous analytical formulation utilizing a realistic laser source, the clear significance of the absorption parameter that enhances the temperature amplitude, the incorporation of the Mittag–Leffler function, and a comprehensive investigation of fractional photothermal effects in metallic nano-systems. …”
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Application of artificial neural network in deoxygenation of water by glucoseoxidase immobilized in calcium alginate/MnO2 composite by A. Abdi, M.Sh Izadkhah, A. Karimi, M. Razzaghi, H. Moradkhani

“…The linear regression between the network outputs and the corresponding targets were proven to be satisfactory with a correlation coefficient of 0.995 for three model variables used in this study.…”
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A Predictive Model for Estimating Reservoir Impounding Time Based on the Net Inflow and Storage Volume by Harimukti Rosita R., Pitojo T. Juwono, Lily M. Limantara, Emma Yuliani

“…By using the base equation of linear regression: Ln(D)=m×Ln(S)+n×Ln(Inet) and based on the analysis result of 28 combinations, there is selected the combination with the best determination coefficient (R2) that is 0.99 with m = 1.047 and n = -1.08807. …”
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