Multi-objective optimization of sustainable cement-zeolite improved sand based on life cycle assessment and artificial intelligence [version 1; peer review: 1 approved, 2 approved... by Hossein MolaAbasi, Satinder Kaur Brar, Amin Tanhadoust, Sepideh Nasrollahpour, Omolbanin Ataee, Moncef L. Nehdi

“…This study proposes a multi-objective optimization approach using back-propagation neural network (BPNN) to predict the mechanical strength, along with an adaptive geometry estimation-based multi-objective evolutionary algorithm (AGE-MOEA) to identify the best parameters for cement-zeolite-improved sand, filling a long-lasting research gap. …”
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Increasing Systemic Resilience to Socioeconomic Challenges: Modeling the Dynamics of Liquidity Flows and Systemic Risks Using Navier–Stokes Equations by Davit Gondauri, Nino Chedia, Vakhtang Tsintsadze

“…In addition, the cyclical components obtained by Fourier analysis are harmoniously related to economic cycles and increase the accuracy of the model's predictions. The scientific significance of the study lies in the fact that it creates a mathematically balanced framework for a multifactorial analysis of the behavior of the financial system, which makes it possible not only to predict crises, but also to plan countercyclical policies and increase systemic stability. …”
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Cer(d18:1/16:0) as a biomarkers for acute coronary syndrome in Chinese populations by Liang Zhang, Yang Zhang, YaoDong Ding, Tong Jin, Yi Song, Lin Li, XiaoFang Wang, Yong Zeng

“…The objective of this study was to investigate the association between serum ceramide levels and Acute coronary syndrome, as well as evaluate their potential for predicting ACS in Chinese population. Data of 1327 patients with suspected or known coronary artery disease from Beijing anzhen Hospital and Handan First hospital were collected. …”
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Individual patient variability with the application of the kidney failure risk equation in advanced chronic kidney disease. by Christopher McCudden, Ayub Akbari, Christine A White, Mohan Biyani, Swapnil Hiremath, Pierre Antoine Brown, Navdeep Tangri, Scott Brimble, Greg Knoll, Peter G Blake, Manish M Sood

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Numerical Simulation of Earthquake Impacts on Marine Structures: A Comprehensive Review by Adel Kabi, Jersson X. Leon-Medina, Francesc Pozo

“…Furthermore, integrating laboratory and field data into unified frameworks will significantly improve the precision and practicality of these models, offering robust tools for predicting earthquake and wave impacts on marine environments.…”
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Quantum machine learning regression optimisation for full-scale sewage sludge anaerobic digestion by Yomna Mohamed, Ahmed Elghadban, Hei I Lei, Amelie Andrea Shih, Po-Heng Lee

“…Combining a variational quantum circuit with a classical optimiser, this approach predicts biogas production from operational data of 18 full-scale mesophilic AD sites in the UK. …”
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The Use of General Inverse Problem Platform (GRIPP) as a Robust Backtracking Solution by Nikolas Gomes Silveira de Souza, Jader Lugon, Alexandre Macedo Fernandes, Ramiro Joaquim de Jesus Neves, Antônio José da Silva Neto

“…The optimization yielded a solution with a mean error of 0.019 degrees between predicted and observed tracer locations. This demonstrates the potential of GRIPP and GenSA for solving practical environmental problems in coastal regions. …”
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Machine learning-based multiphysics model for corrosion fatigue crack propagation in aluminum alloy by Hongkun Wang, Zhenshuang Wu, Dongmei Jiang, Haitao Wang, En-Hou Han

“…The present study predicted the corrosion fatigue crack growth rate of 7075-T7651 aluminum alloy under cyclic sinusoidal loading in an aqueous solution. …”
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Robust Representation Learning Based on Deep Mutual Information for Scene Classification Against Adversarial Perturbations by Linjuan Li, Gang Xie, Haoxue Zhang, Xinlin Xie, Heng Li

“…However, deep learning models used for scene classification are highly vulnerable to adversarial samples, resulting in incorrect predictions and posing significant risks. While most current methods focus on improving adversarial robustness, they face a trade-off that compromises accuracy on clean, unperturbed images. …”
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Application of a GA-BP Neural Network in Accurately Characterizing the Diffusion Range of Groundwater Pollutants by Jiayun JI, Xiao XIAO, Pinlu YANG, Yang LIU, Yahong ZHOU

“…To overcome this, two neural network models—GA-BP and standard BP—were applied to predict Mn2+ concentrations at unsampled locations. …”
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Optimizing PV power utilization in standalone battery systems with forecast-based charging management strategy by Utpal Kumar Das, Ashish Kumar Karmaker

“…Additionally, a support vector regression (SVR)-based forecasting model is developed to predict PV power generation precisely. The results indicate that the anticipated BCM strategy achieves an overall utilization rate of 87.47% of the PV-generated power for battery charging under various weather conditions.…”
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Thermal-Hydraulic Network Model for steady-state thermal analysis and design of power transformer magnetic cores by L.H. Medeiros, M.M. Oliveira, C.E.G. Falcão, V.C. Bender, T.B. Marchesan

“…The analytical results are compared to experimental measurement using an optical fiber sensor allocated in the core of a prototype transformer, indicating that the model can satisfactorily predict the hydraulic and thermal behaviors of magnetic cores.…”
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Traffic Capacity Assessment of the Urban Elevated Bridge after Near-Field Explosion Based on the Response Surface Method by Jinghui Jiang, Chaoyi Xia, Kunpeng Wang, He Xia, Qikai Sun

“…The established assessment method can be used to predict the probability of bridge structural damage at various levels under different types of car bombs and to provide a reference for exploring a probability-based safety assessment method of post-explosion bridges.…”
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A Method for Efficient Task Assignment Based on the Satisfaction Degree of Knowledge by Jiafu Su, Jie Wang, Sheng Liu, Na Zhang, Chi Li

“…From the knowledge-based view, the tasks’ execution time calculation component uses the BP neural network to predict tasks’ execution time according to the previous similar tasks and the Task–Knowledge–Person (TKP) network. …”
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Monte Carlo Uncertainty Quantification Using Quasi-1D SRM Ballistic Model by Davide Viganò, Adriano Annovazzi, Filippo Maggi

“…For this reason, the reliability of predictions and reproducibility of performances represent a primary goal in this field. …”
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FLAC3D Simulation of Caving Mechanism and Strata Fracture Response in Underground Mining by Mahdi Saadat, Mattin Khishvand, Andrew Seccombe

“…However, the floor heave highlights the need for the implementation of effective risk and safety measures. Goaf is predicted to form with a longwall advance rate of 25.0–30.0 m, resulting from progressive macroscopic fracturing caused by the development of cracks initiated by bedding plane and rock mass failures. …”
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The effects of linear energy density and gas environment on droplet spatter characteristics and dynamics during selective laser melting by Guang Yang, Qi Liu, Da An, Xiangming Wang, Ranliang Wu, Han Xie

“…The mechanism of droplet spatter is discussed and divided into three categories. Predicting the recoil pressure and horizontal distance of spatter. …”
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Machine Learning Analysis of Umbilic Defect Annihilation in Nematic Liquid Crystals in the Presence of Nanoparticles by Ingo Dierking, Adam Moyle, Gabriele Maria Cepparulo, Katherine Skingle, Laura Hernández, Juhan Raidal

“…It is observed that the defect annihilation scaling exponents deviate from the theoretically predicted value of α = 1/2 when nanoparticles of varying size and concentration are introduced to the system. …”
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Abstraction-based segmental simulation of reaction networks using adaptive memoization by Martin Helfrich, Roman Andriushchenko, Milan Češka, Jan Křetínský, Štefan Martiček, David Šafránek

“…Conclusion  We demonstrate that in combination with a novel fully automatic and adaptive hybrid simulation scheme, we can speed up the generation of trajectories significantly and correctly predict the transient behavior of complex stochastic systems.…”
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An Influence of Gas Explosions on Dynamic Responses of a Single Degree of Freedom Model by Ki-Yeob Kang, Kwang-Ho Choi, Jae Woong Choi, Yong Hee Ryu, Jae-Myung Lee

“…Computational fluid dynamics (CFD) simulations contribute a key part of an ERA and predict possible blast consequences in a hazardous area. …”
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