GWO and WOA variable step MPPT algorithms-based PV system output power optimization by Abderrahim Zemmit, Abdelouadoud Loukriz, Khaled Belhouchet, Yahya Z. Alharthi, Muhannad Alshareef, Prabhu Paramasivam, Sherif S. M. Ghoneim

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Self-optimization of Wind Turbine Variable-pitch Control Parameters Based on Adaptive Genetic Algorithm by CHANG Sheng, WAN Yubin, JIANG Tao

“…For the low parameter tuning efficiency, accuracy and adaptability of the traditional PID parameter tuning method currently adopted in the wind turbine variable-pitch system, this paper presents a method for self-optimization of wind turbine variable-pitch control parameters based on adaptive genetic algorithm, including variable-gain variable-pitch PID parameter self-optimization and tower damping parameter self-optimization. …”
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Numerical modeling for optimized sediment deflection with variable submergence over a row of submerged vanes by Vikalp Chauhan, Ellora Padhi, Gopal Das Singhal

“…This research examines the potential for improved sediment deflection efficiency through the optimisation of variable submergence. …”
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A STUDY OF THE DETERMINANTS OF THE OLIVE CROP PRODUCTION IN NINEVEH PROVINCE: BASHIQA DISTRICT AS A CASE STUDY FOR THE SEASON 2010 by Abdul Salam Hussein, Salah Fahmi Shaba

“…The Output of the olive crop was considered as the explanatory variable and the total cost in Iraqi Dinar is considered as dependant variable. …”
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Significance of dissipative flow on a second-grade nanofluid with variable thermal properties on the stretching surface by Zia Ullah, Aamir Abbas Khan, Shalan Alkarni, Abhinav Kumar, N. Beemkumar, Tushar Aggarwal, Ashwin Jacob, Jajneswar Nanda, Feyisa Edosa Merga

“…Boundary conditions are used for the analysis of heat and mass transmission. Stream functions and similarity variables are utilized to reduce the complexity of the governed PDEs (partial differential equations) and altered into ODEs (ordinary differential equations). …”
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VarProDMD: Solving Variable Projection for the Dynamic Mode Decomposition with SciPy’s optimization suite by Gerhard Reinerth, David Messmann, Jean Elsner, Ulrich Walter

“…The available Python library implements a variant of the Levenberg–Marquardt optimizer for the Variable Projection Method. The optimization procedure uses a complex residual function since the measurements can incorporate complex numbers. …”
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Sharp L2 Norm Convergence of Variable-Step BDF2 Implicit Scheme for the Extended Fisher–Kolmogorov Equation by Yang Li, Qihang Sun, Naidan Feng, Jianjun Liu

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Application of physics-informed neural networks for two-phase flow model with variable diffusion and experimental validation by Daulet Kalesh, Timur Merembayev, Sagyn Omirbekov, Yerlan Amanbek

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Improving the Minimum Free Energy Principle to the Maximum Information Efficiency Principle by Chenguang Lu

“…The G theory is based on the P-T probability framework and, therefore, allows for the use of truth, membership, similarity, and distortion functions (related to semantics) as constraints. Based on the study of the <i>R</i>(<i>G</i>) function and logical Bayesian Inference, this paper proposes the Semantic Variational Bayesian (SVB) and the Maximum Information Efficiency (MIE) principle. …”
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Efficient bit labeling in factorization machines with annealing for traveling salesman problem by Shota Koshikawa, Aruto Hosaka, Tsuyoshi Yoshida

“…Abstract To efficiently determine an optimum parameter combination in a large-scale problem, it is essential to convert the parameters into available variables in actual machines. …”
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Efficient curve fitting with penalized B-splines for oceanographic and ecological applications by Kwan-Young Bak, Dong-Young Lee, Ju-Seong Lee, Hee-Jung Jee, R. Jisung Park, Ja-Yong Koo, Jae-Hwan Jhong

“…The total variation penalty controls curve smoothness by penalizing abrupt changes in the estimated function, while the group penalty ensures that all response variables share a consistent set of knots, enhancing interpretability. …”
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Energy efficiency in middle-income countries with DEA: An approach for Latin America by Néstor Xavier Maya, M.M. Prieto, Laura Megido

“…From this analysis, the production function, the technical efficiency, the total energy efficiency factor and their respective correlation coefficients versus the per capita income variable are obtained for each country. …”
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Optimizing capacitor size and placement in radial distribution networks for maximum efficiency by R. Arunjothi, K.P. Meena

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The dichotomy of human decision-making: An experimental assessment of stone tool efficiency. by David Nora, João Marreiros, Walter Gneisinger, Antonella Pedergnana, Telmo Pereira

“…This strongly suggests that each raw material used in archaeological contexts to produce blanks should be evaluated for its efficiency. In addition, it may be pertinent to extend this approach to other blunt artefactssuch as scrapers, burins, anvils, and hammerstones when investigating aspects of interconnected behaviours such as artefact variability, resource economy, group mobility, and site function. …”
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PRODUCTIVITY AND EFFICIENCY OF MAIZE (ZEA MAYS) FARMERS IN ADAMAWA STATE, NIGERIA by Abdu Karniliyus TASHIKALMA, Dengle Yuniyus GIROH

“…Education and extension contact were statistically significant (p≤0.05) and increase technical efficiency among respondents. Furthermore, the stochastic cost function analysis indicated that 80.24% variations in allocative efficiencies were as a result of the variables included in the model. …”
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An Efficient Sparse Twin Parametric Insensitive Support Vector Regression Model by Shuanghong Qu, Yushan Guo, Renato De Leone, Min Huang, Pu Li

“…Similar to twin parametric insensitive support vector regression (TPISVR), STPISVR constructs a pair of nonparallel parametric insensitive bound functions to indirectly determine the regression function. …”
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Structural optimization of stiffened panel structures with continuous and discrete design variables using deep reinforcement learning by Ryota NONAMI, Mitsuru KITAMURA

“…To overcome such an environment, in this study, an optimization flow for structural optimization is considered, and states, actions, and rewards appropriately representing design variables, constraint conditions, and objective functions are discussed. …”
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Technical Efficiency of Sweet Potato Production: A Stochastic Frontier Analysis by Godfrey C. Onuwa, Solomon T. Folorunsho, Ganiyu Binuyo, Mercy Emefiene, Onyekwere P. Ifenkwe

“…Data collected was analyzed using descriptive statistics and stochastic frontier production function. The socioeconomic variables of the respondents affected their farm efficiency and level of farm output. …”
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Computationally Efficient Hybrid Downscaling of Surf Zone Hydrodynamics: Methodology and Evaluation by E. R. Echevarria, S. Contardo, B. Pérez‐Díaz, R. K. Hoeke, B. Leighton, C. Trenham, L. Cagigal, F. J. Méndez

“…Abstract We present a hybrid surf‐zone model that combines numerical simulations and statistical/machine learning techniques, enabling accurate calculations of nearshore wave and hydrodynamic parameters with high computational efficiency. The approach involves defining representative forcing conditions, carrying out numerical model (XBeach) simulations for these cases, and training machine learning models capable of predicting selected model output variables. …”
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New feedback functions for synchronizing chaotic maps by M. K. Ali

“…Synchronization of chaotic maps is studied using the method of variable feedback. A general method is presented for generating feedback functions for maps. …”
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