Statistical mechanics of dynamical system identification by Andrei A. Klishin, Joseph Bakarji, J. Nathan Kutz, Krithika Manohar

“…To establish this analogy, we define the hyperparameter optimization procedure as a two-level Bayesian inference problem that separates variable selection from coefficient inference and enables the computation of the posterior parameter distribution in closed form. …”
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Spatial dependencies between large-scale brain networks. by Robert Leech, Gregory Scott, Robin Carhart-Harris, Federico Turkheimer, Simon D Taylor-Robinson, David J Sharp

“…Many studies show a temporal relationship between task positive and task negative networks that is important for efficient cognitive functioning. Here we provide evidence for a spatial relationship between task positive and negative networks. …”
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Economics production buffalo breeding farms in the province of Nineveh (Badush area a case stady) by Salim AL- Nuaimy, Zwaid, F. Abd, Mahasen, M, Sultan

“…Results of the estimation showed that the double logarithmic formula is the best formula for the representation of production function and that the function and all the explanatory variables are statistically significant except for green feed and veterinary services.The most significant effect of the employment variable was on the production process، with  elasticity of 0.277 and  positive indication، and the results of the cost function estimate the best formulas to represent the relationship. …”
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Landing scheduling for carrier aircraft fleet considering bolting probability and aerial refueling by Genlai Zhang, Lei Wang, Zhilong Deng, Xuanbo Liu, Xichao Su, Haixu Li, Chen Lu, Kai Liu, Xinwei Wang

“…Then, taking the landing sequencing as decision variables, a combinatorial optimization model with a compound objective function is formulated. …”
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Physics-augmented deep learning models for improving evapotranspiration estimation in global land regions by Binrui Liu, Xinguang He, Wenkai Lyu, Lizhi Tao

“…A Physics-Data Learning (PDL) model is first formed by adding a complementary physical variable generated by Penman–Monteith (PM) equation to a deep learning (DL) model along with driving variables to regress latent heat flux. …”
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Hybrid Approach of Finite Element Method, Kigring Metamodel, and Multiobjective Genetic Algorithm for Computational Optimization of a Flexure Elbow Joint for Upper-Limb Assistive D... by Duc Nam Nguyen, Thanh-Phong Dao, Ngoc Le Chau, Van Anh Dang

“…The optimization problem considers three design variables and two objective functions. An efficient hybrid optimization approach of central composite design (CDD), finite element method (FEM), Kigring metamodel, and multiobjective genetic algorithm (MOGA) is developed. …”
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Adaptive Fractional-Order Nonsingular Fast Terminal Sliding Mode Control for Manipulators by Xin Zhang, Ran Shi

“…Secondly, in view of the problems of large chattering and slow convergence speed in the reaching stage, this paper designs a variable exponential power-reaching law (VEPRL), which has the ability to change the exponential coefficients according to the system state adaptively. …”
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Analyzing the influence of TOE factors on e-auditing adoption in audit firms: The moderating effect of trust by Reem Al-Araj

“…Data show that trust functions as a supportive variable for the relationship between TOE and e-auditing but provides minimal strength. …”
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Model Transportasi Jalur Laut untuk Distribusi Semen Curah by Jenny Andres Yunirman

“…The objective function of this model is the minimization of transport costs to meet demand in each of the packing plant. …”
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An algorithm for independent component analysis using a general class of copula-based dependence criteria by Fatemeh Asadi, Hamzeh Torabi, Hossein Nadeb

“…The efficiency of Independent Component Analysis ($\rm ICA$) algorithms relies heavily on the choice of objective function and optimization algorithms. …”
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Random First-Order Linear Discrete Models and Their Probabilistic Solution: A Comprehensive Study by M.-C. Casabán, J.-C. Cortés, J.-V. Romero, M.-D. Roselló

“…The study is based on Random Variable Transformation method. The obtained results are given in terms of the probability density functions of the data, namely, initial condition, forcing term, and diffusion coefficient. …”
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Using Fuzzy Feed-Forward Neural Network for Linguistic Processing by AbdulRahim K. Rah, Sozan S. Haydar

“…To determine the costs associated with fuzzy calculations and fuzzy objectives, developed a cost function. At that point, created a learning algorithm from the cost capacity to align the four variables of each trapezoidal fuzzy weight. …”
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AngleCam: Predicting the temporal variation of leaf angle distributions from image series with deep learning by Teja Kattenborn, Ronny Richter, Claudia Guimarães‐Steinicke, Hannes Feilhauer, Christian Wirth

“…The plausibility of the predicted leaf angle time series was underlined by its close relationship with environmental variables related to transpiration. The evaluations confirm that AngleCam is a robust and efficient method to track leaf angles under field conditions. …”
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Optimization of fermentation conditions for enhanced acetylcholine and biomass production of Lactiplantibacillus plantarum AM2 using the Taguchi approach by Walid A. Lotfy, Amira M. Ali, Heba M. Abdou, Khaled M. Ghanem

“…Abstract This study aimed to optimize the fermentation conditions and medium composition for maximum acetylcholine (ACh) and biomass production by Lactiplantibacillus plantarum AM2 using the Taguchi array design, which enables efficient identification of influential variables through minimal experimental runs. …”
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Machine learning projection of climate and technology impacts on crops key to food security by Dan Li, Vassili Kitsios, David Newth, Terence John O’Kane

“…Our model is designed to capture the relationships between technology, climate variables and the annual growth rate in crop yield across the world’s producing regions. …”
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On the Modular Design Application for the Gas Turbine Sector: A Performance Optimization Approach in the Context of Industry 4.0 by Lucas Chavanel-Precloux, Roland Maranzana, Lucas A. Hof

“…Indeed, this study presents the functioning of the novel application, the different deployed components and their variables, such as the compressor efficiency, heat exchangers, or turbine stages, and the decision variable, e.g., the costs of generated energy. …”
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Sap flow simulation of Cunninghamia lanceolata in degraded red soil region based on back propagation neural network by Tu Jie, Liu Qijing, Wei Jun, Hu Liang

“…Therefore, quantitative research on tree water consumption characteristics by transpiration has become a hot issue in the field of tree physiological ecology in recent years.Taking the C. lanceolata plantation in degraded red soil of Jiangxi Province as the research object, the log-sigmoid type function (tansig) of MATLAB toolbox was selected as the transmission function for the role of neurons. …”
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Evaluation of the Wind-Resistant Performance of Long-Span Cable-Stayed Bridge Using the Monitoring Correlation between the Static Cross Wind and Its Displacement Response by Gaoxin Wang, Youliang Ding, Dongming Feng, Jihong Ye

“…Third, considering that the traditional function cannot match the monitoring correlation very well, some new fitting functions are thoroughly studied to determine the best function for fitting the monitoring correlation. …”
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ANALYSIS AND OPTIMIZATION OF QUICK-RETURN CHARACTERISTICS OF THE BEATING⁃UP SLEY BASED ON MULTIVARIABLE DESIGN by QIU HaiFei

“…For improving the quick‑return characteristics of the sley movement,an optimal mathematical model for maximum curve displacement Sm of the connectingarm pin was proposed through beating‑up principle analysis and mechanism deduction.A multivariable design space was constructed by use of the component length(lc,lh,lr,lf)and crankangleα.The parametric functional model development of the four‑bar beating‑up with short connecting rod was realized,and its kinematic posture and centroid trajectory were analyzed and verified through mechanism simulation.The results of the case study indicate that the variable lc andαhave more greater influence on the sensitivity of the objective function F(X),and multivariable(DV_1,DV_2,DV_3)coupling can effectively enhance the design plasticity of the quick‑return characteristics of the sley.When the maximum curve displacement Sm of the connectingarm pin increases to 71.41 mm,the extreme position angleθand the travel speed ratio coefficient K are increased by 10.96°and 0.131 respectively,and the quick-return motion effect of the sley is obviously improved.The optimization results accord with the conditions of rod length and mechanism transmission requirement,which are conductive to the design innovation and performance improvement of the four‑bar beating‑up system.…”
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Faktor-Faktor Yang Mempengaruhi Pertumbuhan Ekonomi Di Jawa Timur Dengan Pendekatan Spatial Regression by Rendra Erdkhadifa

“…The research results show that the weighting function used is fixed gaussian, and the spatial model has a coefficient of determination of 92.97%. …”
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