PRODUCTION AND INCOME ANALYSIS OF DRIED FISH BUSINESS IN BENGKULU CITY by Bambang Sumantri, Irnad, Winta Septria, Melly Suryanti, Widya Kartika Laksmawati

“…The analytical method used is the Cobb-Douglas production function model to answer the first objective and income analysis to answer the second objective. …”
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APPLICATION OF HYBRID RANDOM SEARCH METHOD TO OPTIMISATION OF ENGINEERING SYSTEMS’ PARAMETERS by A. V. Panteleev, D. A. Rodionova

“…These problems belong to the class of constrained global optimization problems, where the level surface of the objective function has uneven relief and there is a large number of variables. …”
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Color image hybrid noise filtering algorithm based on deep convolution neural network by Yongfei Yu, Yuanjian Yan

“…Then, the probability density function and noise probability density function of Gaussian noise are calculated to determine the hybrid noise feature points of color image. …”
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Optimization of power output in plateau photovoltaic power stations using a hybrid Kepler and Gaussian quantum particle swarm algorithm by Shuang Gan, Heng Hu, Shaoshuai Li, Qian Peng, Taidong Yan, Huasheng Gong, Yuancheng Zhang

“…The optimization process is modeled with key decision variables, including panel configurations, snow removal strategies, and system efficiency adjustments. …”
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Response Surface Optimization of CuS Photocatalytic Process Using UV‐vis Irradiation for Wastewater Treatment by Caressa Munien, Emmanuel Kweinor Tetteh, Sudesh Rathilal

“…Thus, this study aimed to optimize the operating parameters of the photocatalytic degradation process using copper sulphide (CuS) and UV‐visible irradiation via response surface methodology (RSM) to determine the relationship that exists between the most significant factors and the water quality parameters. The efficiency of the CuS photocatalyst was evaluated as a function of three input variables viz. …”
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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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Online identification of stability region for large-scale wind farms, Part I: Clustering based piecewise affine impedance modeling by Jia Luo, Peng Wang, Haoran Zhao, Chenxinwei Yuan, Tiancheng Liu, Vladimir Terzija

“…In each partition, the impedance is expressed as a first-order explicit function of the complex variable and the operating state variables. …”
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Research on Robust Adaptive Model Predictive Control Based on Vehicle State Uncertainty by Yinping Li, Li Liu

“…To overcome these limitations, three key innovations are introduced: a three-degree-of-freedom vehicle dynamic model integrated with recursive least squares-based online estimation of tire slip stiffness for real-time lateral force compensation; an adaptive weight adjustment mechanism that dynamically balances control energy consumption and tracking accuracy by tuning cost function weights based on real-time state errors; and a dynamic constraint relaxation strategy using slack variables with variable penalty terms to resolve infeasibility while suppressing excessive constraint violations. …”
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Development of Sub-channel Program and Multi-objective Optimization Method Research for Printed Circuit Heat Exchanger by CHEN Liqin, HUO Honglei, XIE Renyao, YANG Yi

“…The results of sensitivity analysis show that as the flow channel width and height of the cold side flow channel increase, the sensitivity of the objective function to the variables continues to decrease, the optimization effect gradually becomes worse, and there are optimal design points, which are 4 mm and 1 mm respectively. …”
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Respiratory Muscle Strength as a Predictor of VO2max and Aerobic Endurance in Competitive Athletes by Gökhan Deliceoğlu, Banu Kabak, Veli O. Çakır, Halil İbrahim Ceylan, Muntean Raul-Ioan, Dan Iulian Alexe, Valentina Stefanica

“…Previous research has elucidated the complex interactions between respiratory and skeletal muscles during exercise, highlighting the critical role of efficient respiration in maximizing athletic performance. …”
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Predicting Endpoint Temperature of Molten Steel in VD Furnace Refining Process Using Metallurgical Mechanism and Bayesian Optimization XGBoost by Ji XU, Zicheng XIN, Mo LAN, Wenhui LIN, Bo ZHANG, Qing LIU

“…The MM–BO–XGBoost model demonstrates excellent training efficiency and prediction performance.Conclusion The analysis of the mechanism of the VD furnace refining process and Pearson correlation analysis are conducted, and the input variables for the prediction model of VD furnace endpoint liquid steel temperature are identified. …”
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Lattice Boltzmann Method for the Generalized Black-Scholes Equation by Fangfang Wu, Duoduo Xu, Ming Tian, Yingying Wang

“…In this paper, an efficient lattice Boltzmann model for the generalized Black-Scholes equation governing option pricing is proposed. …”
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Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature by S. Schöngart, S. Schöngart, L. Gudmundsson, M. Hauser, P. Pfleiderer, Q. Lejeune, S. Nath, S. I. Seneviratne, C.-F. Schleussner, C.-F. Schleussner, C.-F. Schleussner

“…Owing to their runtime efficiency, emulators are especially useful when large amounts of data are required, for example, for in-depth exploration of the emission space, for investigating high-impact low-probability events, or for estimating uncertainties and variability. …”
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Ridge regression and its applications in genetic studies. by M Arashi, M Roozbeh, N A Hamzah, M Gasparini

“…On the other hand, the efficiency of the rank ridge regression estimator is highly dependent on the ridge parameter. …”
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System Modeling to Optimize the Production Quantity of Men's and Women's Jackets and Achieve Maximum Profit: A Case Study at Konveksi ABC Cikarang Using Linear Programming by Wisnu Aji

“…The objective function is designed to maximize profit, and the model is solved using IBM ILOG CPLEX software. …”
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Multiobjective optimization of suspension bridges via coupled modeling and dual population multiobjective particle swarm optimization by Peiling Yang, Jianhua Deng, Anli Wang

“…The Lasso function is used for elastic net regression analysis to evaluate the impact of design variables on the objective functions. …”
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Proportional Topology Optimization algorithm with virtual elements for multi-material problems considering mass and cost constraints by Minh Tuan Tran, Minh Ngoc Nguyen

“…., the derivative of the objective function with respect to design variables. Instead, the amount of material distributed into each element is determined proportionally to the contribution of that element to the objective function. …”
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A toolkit for facilitating markerless integration of expression cassettes in Komagataella phaffii via CRISPR/Cas9 by Laura García-Calvo, Charlotte Kummen, Solvor Rustad, Sissel Beate Rønning, Annette Fagerlund

“…Abstract Background The yeast Komagataella phaffii (formerly known as Pichia pastoris) has been widely used for functional expression of recombinant proteins, including plant and animal food proteins. …”
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Numerical Mixing Index: Definition and Application on Concrete Mixer by Cristian Ferrari, Nicolò Beccati, Luca Magri

“…The method predicts the distribution efficiency of the materials within a truck mixer as a function of its internal geometry, rotation speed, and mixture composition. …”
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Providing a Framework for Performance Evaluation of Organizations in Successfully Implementing TQM, Based on Knowledge Management Approach and Organizational Agility by Neda Irannejad, Hadi Shirouyehzad, Arash Shahin

“…To express the above-given relationship, group interpretive structural modelling (ISM (interpretive structural modelling)) techniques have been used to rank the components of each domain; also, fuzzy quality function deployment (FQFD (fuzzy quality function deployment)) technique has been applied to find the weight and relationship of the three mentioned domains by examining the independent and interface variables of the previous step. …”
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