Jacobian-Free Newton Krylov Methods for Steady and Transient Neutron Transport Models by ZHANG Yangyi, ZHANG Tiancheng, ZHOU Xiafeng

“…To further improve computational efficiency of comeSn_JFNK, in the JFNK solution, neutron scalar fluxes instead of neutron angular fluxes were chosen as the global solution variables. …”

Estimation of Stochastic Frontier Models with Fixed Effects through Monte Carlo Maximum Likelihood by Grigorios Emvalomatis, Spiro E. Stefanou, Alfons Oude Lansink

“…This paper proposes a procedure for choosing appropriate densities for integrating the incidental parameters from the likelihood function in a general context. The densities are based on priors that are updated using information from the data and are robust to possible correlation of the group-specific constant terms with the explanatory variables. …”
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A Study of Some Properties of Fuzzy Laplace Transform with Their Applications in Solving the Second-Order Fuzzy Linear Partial Differential Equations by Elhassan Eljaoui, Said Melliani

“…Then, some properties dealing with the partial derivatives of fuzzy Laplace transform for a fuzzy function of two real variables have been proved. Afterwards, an algorithm of fuzzy Laplace transform for solving second-order fuzzy partial differential equations has been proposed. …”
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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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Impact of adopting improved Arabica varieties on the livelihood of organic coffee producers’ of Ethiopia: Continuous treatment approach by Negussie Zeray Gebru, Tasew Tadesse, Wajana Wae

“…The technique proved efficient in elucidating non-linear causal links between adoption intensities, dosages, and outcome variables. …”
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A Bayesian-Weighted Inverse Gaussian Regression Model with Application to Seismological Data by Ehsan Mesdaghi, Afshin Fallah, Rahman Farnoosh, Gholam Hossein Yari

“…In the proposed model, the complementary reciprocal of the location parameter of response variable is considered to be a linear function of the explanatory variables. …”
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Revolutionizing proton exchange membrane fuel cell modeling through hybrid aquila optimizer and arithmetic algorithm optimization by Manish Kumar Singla, S. A. Muhammed Ali, Ramesh Kumar, Pradeep Jangir, Mohammad Khishe, G. Gulothungan, Haitham A. Mahmoud

“…These parameters function as decision variables, and the objective function aimed for minimization is the sum square error (SSE) between the predicted and actual measured cell voltages. …”
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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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Trajectory Planning Based on Screw Theory with Consideration of the Optimal Berth Position for a Space Robot by Yong Wang, Ying Liao, Kejie Gong

“…First, the berth position is transformed into the desired position of the end-effector, and its constraints are described. Joint variables are parameterized using a sinusoidal function combined with a five-order polynomial function. …”
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Analysis the Impact of Covid-19 on Green Accounting and Its Implications on Profitability by Reschiwati Reschiwati, Fran Sayekti, Tasia Veronica

“…The next difference is that the Performance and Environmental Disclosure variables function as both Y variables and X variables (intervening). …”
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Sensory profiles in older adults with orthopedic conditions during quiet stance: a cross-sectional study by Marine Brika, France Mourey, Alexandre Kubicki

“…Methods Fifty-one older adults (76.9 ± 7.6 years) were divided into 2 Functional Groups (FG-/FG+) according to a composite score that included 3 variables (gait speed, grip strength and fear of falling). …”
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Research on Constraint Processing Method of High-dimensional Optimization Operation Problem of Cascade Reservoirs by Zhongzheng HE, Shuliang LI, Wei HUANG, Feng YAN, Jisi FU, bin XIONG

“…The intelligent optimization algorithm is a multidimensional linkage random search, which boasts a vast optimization space but suffers from low optimization efficiency. Therefore, this study introduces a constraint processing approach that integrates a penalty function with nested DPSA–POA and intelligent algorithms and applies it to the optimal flood control operation problem of cascade reservoirs in the middle reaches of the Ganjiang River, with decision variables extending to 2196 dimensions. …”
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APPLICATION AND PERFORMANCE COMPARISON OF MULTI-OUTPUT MACHINE LEARNING FOR NUMERICAL-NUMERICAL AND NUMERICAL-CATEGORICAL OUTPUTS by Karin Joan, Robyn Irawan, Benny Yong

“…Multi-Output Machine Learning is an advancement of traditional machine learning, designed to predict multiple output variables simultaneously while considering the relationships between these output variables. …”
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Investigation, Optimization of Energy Consumption and Yield Modeling of Two Paddy Cultivars with Genetic-Artificial Bee Colony Algorithm by S. Sharifi, N. Hafezi, M. H. Aghkhani

“…IntroductionEfficient use of energy in paddy production can lower greenhouse gas emissions, safeguard agricultural ecosystems, and promote the growth of sustainable agriculture. …”
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Underactuated Spatial Mechanism of Vehicle Door Latch with Force Constraint by Sulong Li, Lubin Hang, Mingyuan Wang, Xiaojie Huang

“…Aiming at less space occupation，efficient driving and high-end multi-function of the door latch release branch chain，the type synthesis of single loop spatial mechanism is carried out，and the RRRSR mechanism which could realize power release is obtained. …”
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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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A Fusion Method Based on Physical Modes and Satellite Remote Sensing for 3D Ocean State Reconstruction by Yingxiang Hong, Xuan Wang, Bin Wang, Wei Li, Guijun Han

“…This study developed an operational-oriented lightweight framework for three-dimensional ocean state reconstruction by integrating multi-source observations through a computationally efficient multivariate empirical orthogonal function (MEOF) method. …”
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带传动软启动装置蜗杆的优化设计 by 赵江平

“…By the mechanical analysis of the belt drives soft-start equipment,tow-objective function is established with the worm axial modulus and spiral angle as the independent variables.Based on self-locking constraint and fuzzy constraint conditions,constraint subset is established.Compared with the general design parameters,the rustle shows that the spiral angle is increased and the worm axial modulus is decreased.The test shows that the optimize design effectively improve the transmission efficiency,and reduce the minimum power of the speed adjustment motor.…”
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Hybrid data-driven and physics-informed regularized learning of cyclic plasticity with neural networks by Stefan Hildebrand, Sandra Klinge

“…The mean squared error is assumed as the loss function which stipulates several restrictions: deviatoric character of internal variables, compliance with the flow rule, the differentiation of elastic and plastic steps and the associativity of the flow rule. …”
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Pareto Optimal Solutions for Stochastic Dynamic Programming Problems via Monte Carlo Simulation by R. T. N. Cardoso, R. H. C. Takahashi, F. R. B. Cruz

“…Instead of using the expected values of the objective function, the randomness nature of the decision variables is kept along the process, while Pareto fronts weighted by all quantiles of the objective function are determined. …”
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