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.…”
Get full text

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. …”
Get full text

A New Noninterior Continuation Method for Solving a System of Equalities and Inequalities by Jianguang Zhu, Binbin Hao

“…By using slack variables and minimum function, we first reformulate the system of equalities and inequalities as a system of nonsmooth equations, and, using smoothing technique, we construct the smooth operator. …”
Get full text

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. …”
Get full text

A design-based framework for optimal stratification using super-population models with application on real data set of breast cancer. by Faizan Danish

“…This study investigates the determination of stratification points for two study variables within the framework of simple random sampling, with a focus on estimating the population mean using a closely related auxiliary variable. …”
Get full text

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. …”
Get full text

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. …”
Get full text

Fuzzy Controller Design Optimized by the Grasshopper Algorithm to Realize Maximum Power in Photovoltaic Systems by Kamran Safaei, Aida Esmaeilian-Marnani, Hossein Emami, Amir Hossein Zaeri

“…In this paper, the ISE evaluation index is employed as the cost function of algorithm to verify the obtained results. …”
Get full text

Kernel Density Estimation for Joint Scrambling in Sensitive Surveys by Alvan Caleb Arulandu, Sat Gupta

“…Randomized response models aim to protect respondent privacy when sampling sensitive variables but consequently compromise estimator efficiency. …”
Get full text

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. …”
Get full text

Multi-objective trajectory planning for connected and autonomous vehicles in mixed traffic flow by Hui Li, Yunfei Ge, Yahui Guo, Yu Guan, Xu Zhang

“…The reward function integrates multiple objectives, including safety, fuel consumption, and traffic efficiency. …”
Get full text

Vibration Response and Evaluation Method of High-Speed Tracked Vehicles Driving Off-Road by Xin-yong Qiao, Ying Jin, Cheng Gu

“…Three fitting methods, namely polynomial response surface, Kriging method, and radial basis function neural network, were used to establish approximate models between the design variables and the objective function, respectively. …”
Get full text

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. …”

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. …”
Get full text

Parental acceptance of novel children's medical syringes and their influencing factors by Su Wen Luo, Peng Rui Yang

“…Furthermore, the product's function and price value significantly shape users' behavioral intentions. …”
Get full text

DeBo: Contrast enhancement for image registration using binary differential evolution and bat optimization. by Muhammad Adeel Akram, Tallha Akram, Umer Javed, Muhammad Rafiq, Mehvish Naz, Di He

“…In this study, we proposed a hybrid binary differential evolution and BAT optimization model to enhance contrast stretching by optimizing a decision variables in the transformation function. To validate its efficiency, the proposed approach is utilized as a preprocessor before feature extraction in image registration. …”
Get full text

Back-Analysis of Parameters of Jointed Surrounding Rock of Metro Station Based on Random Forest Algorithm Optimized by Cuckoo Search Algorithm by Xinping Guo, Annan Jiang, Xiang Liu

“…In this method, the mean square error between the measured displacement (stress) and the calculated displacement (stress) is taken as the objective function, and the joint parameters are taken as the decision variables. …”
Get full text

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. …”
Get full text

Greening concept in inventory system for deteriorating items with preservation investment and price and stock dependent demand via marine predators algorithm by Hachen Ali, Gobinda Chandra Panda, Adel Fahad Alrasheedi, Ali Akbar Shaikh, Jeonghwan Gwak

“…The resulting objective function is highly nonlinear and complex. To solve it efficiently, this study employs the Marine Predators Algorithm (MPA)—a newly developed metaheuristic algorithm well-suited for continuous, nonlinear optimization. …”
Get full text

Relación entre comunidad íctica y cobertura vegetal riparia en dos períodos hidrológicos (Eje Cafetero, Colombia) by María Angélica Pérez-Mayorga, Saúl Prada-Pedreros

“…Therewere no significant differences (P>0.05) among the structural variables, the HYPE and the RVC. According to r and r2 the diet of most fish species did not vary as a function of RVC and HYPE; however, according to the CCA diet varies as a function of HYPE but not of RVC. …”
Get full text