A Support Vector Machine Model with Hyperparameters Optimised by Mind Evolutionary Algorithm for Assessing Permeability of Rock by Wenjin Zhu, Zhiming Chao, Guotao Ma

“…Based on the constructed database, a Support Vector Machine (SVM) model with hyperparameters optimised by Mind Evolutionary Algorithm (MEA) was proposed to predict the permeability of rock. Meanwhile, the Genetic Algorithm- (GA-) and Particle Swarm Algorithm- (PSO-) SVM models were constructed to compare the improving effects of MEA on the foretelling accuracy of machine learning models with those of GA and PSO, respectively. …”
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Optimal Design and Analysis of Traction Steering Mechanism for Loading Transport Vehicle by Ruochao Wang, Zhikuan Yin, Zisheng Liu, Zijue Wang, Taiming Zhang, Jiantao Yao

“…A trapezoidal traction steering mechanism based on Ackerman principle is designed， and uses the sequential quadratic programming genetic algorithm in multivariate nonlinear programming to optimize the specific dimensions of the trapezoidal traction steering mechanism， the size parameters which more satisfy the Ackerman principle are obtained. …”
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Design and Optimization of the Master Manipulator of Minimally Invasive Surgery Robots by Liu Fen, Song Liqiang, Huang Fang, Han Rui, Sang Hongqiang

“…The Jacobian matrix of the master manipulator is solved, the comprehensive performance index of the master manipulator is defined based on the global performance dexterity index and the workspace utilization ratio, and the key link scale parameters are optimized by the genetic algorithm. The results show that the comprehensive performance index of the master manipulator after optimization is 18.41% higher than that before optimization, and the master manipulator is more compact, has better performance besides meeting the design requirements of the workspace.…”
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Big data classification method of non relational distributed submission information under differentiated requirements by Lu HAN, Weiyu CHEN, Fei ZHANG, Jianfeng HE, Huaizhen SU

“…The classification method of non-relational distributed submitted information big data under the differentiated demand was studied, aiming at the problem of multi-source heterogeneous, widely distributed submitted information with more differentiated application requirements and inability to distinguish the available information.Firstly, the usability, openness and expansibility of the non-relational distributed submission information database were analyzed.The unstructured database storage TRIP was used to store non-relational distributed submission information by combining the basic requirements of field types.Then, the hashing process within the Hamming hash family was analyzed.Under the constraint of linearity level requirements, cellular automata with multiple attractors were used to optimize the system.The optimal parameters of the multiple attractor cellular automata classifier were improved through genetic algorithm, thus improving the big data classification method.Experimental results show that this method can effectively identify and classify structured data and unstructured data in non relational distributed submission information, and has high classification accuracy.…”
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Improved dynamic programming method for solving multi-objective and multi-stage decision-making problems by Zhihao Liang, Kegang Zhao, Kunyang He, Yanwei Liu

“…The results demonstrate that the NSDP algorithm achieves better outcome in multiple performance metrics and higher solving efficiency, compared with non-dominated sorting genetic algorithm II and multi-objective particle swarm optimization.…”
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RELIABILITY ANALYSIS OF REACTION FORCE DEVELOPED IN THE LUBRICATED REVOLUTE JOINT FOR A SLIDER-CRANK SYSTEM INCLUDING JOINT WITH CLEARANCE AND LUBRICATION by ZHAO Kuan, XUE He, CHEN JianJun, QIAO XinZhou

“…In order to overcome this limitation,the parameters are pretreated through Genetic Algorithm to get the optimum parameters values. …”
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Complexity Analysis of a Four-Dimensional Energy-Economy-Environment Dynamic System by Shuai Jin, Liuwei Zhao

“…Based on the official data, the Levenberg–Marquardt backpropagation neural network method was optimized by genetic algorithm to effectively identify the parameters in the 3E system. …”
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Metaheuristic Approaches for Hydropower System Scheduling by Ieda G. Hidalgo, Regiane S. de Barros, Jéssica P. T. Fernandes, João Paulo F. Estrócio, Paulo B. Correia

“…We propose two solution methods using metaheuristic approaches. They combine Genetic Algorithm with Strength Pareto Evolutionary Algorithm and Ant Colony Optimization. …”
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A New DG Multiobjective Optimization Method Based on an Improved Evolutionary Algorithm by Wanxing Sheng, Ke-yan Liu, Yongmei Liu, Xiaoli Meng, Xiaohui Song

“…The proposed algorithm was implemented and compared with the strength Pareto evolutionary algorithm 2 (SPEA2), a particle swarm optimization (PSO) algorithm, and nondominated sorting genetic algorithm II (NGSA-II). The comparison of the results demonstrates the validity and practicality of utilizing DG units in terms of economic dispatch and optimal operation in a distribution power system.…”
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Two-Echelon Location-Routing Problem with Fuzzy Demand of Rural E-Commerce Logistics by Xiaojuan LU, Jianjun WANG, Shuai WU, Shiyu ZHENG, Qian LIU

“…Additionally, we present a two-stage Improved Non-Dominated Sorting Genetic Algorithm II (INSGA-II) that integrates stochastic simulation and a K-means clustering algorithm to effectively solve the problem. …”
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An optimized approach for container deployment driven by a two-stage load balancing mechanism. by Chaoze Lu, Jianchao Zhou, Qifeng Zou

“…The subsequent stage utilizes a genetic algorithm for fine-grained resource allocation, ensuring an equitable distribution of resources to each container service on a single virtual machine. …”
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Multicompare Tests of the Performance of Different Metaheuristics in EEG Dipole Source Localization by Diana Irazú Escalona-Vargas, Ivan Lopez-Arevalo, David Gutiérrez

“…We study the use of nonparametric multicompare statistical tests on the performance of simulated annealing (SA), genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution (DE), when used for electroencephalographic (EEG) source localization. …”
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Urban Rail Transit Scheduling under Time-Varying Passenger Demand by Xing Zhao, Zhongyan Hou, Jihuai Chen, Yin Zhang, Junying Sun

“…A hybrid algorithm which consists of the main algorithm based on genetic algorithm and the nested algorithm based on train traction calculation and safety distance requirement is designed to solve the model. …”
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Optimal Trajectory Planning and Linear Velocity Feedback Control of a Flexible Piezoelectric Manipulator for Vibration Suppression by Junqiang Lou, Yanding Wei, Guoping Li, Yiling Yang, Fengran Xie

“…And the sum of the link vibration energy is chosen as the objective function. Then, genetic algorithm is used to determine the optimal trajectory. …”
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RESEARCH ON PARAMETRIC ANALYSIS AND MULTI-OBJECTIVE OPTIMIZATION OF CYLINDRICAL PRESSURE STRUCTURE by LIU Feng, TU ChaoHua, ZHAO YanKai

“…In order to improve the design efficiency and performance of the cylindrical pressure structure,strength and stability analysis methods were determined,the initial scheme was analyzed. the second development of Abaqus software was carried out by using Python language,Abaqus was integrated with i Sight software,the parametric analysis flow of pressure structure was designed,could realize automatic modeling and analysis of cylindrical pressure structure. the most Latin hypercube method was used to selectting the sample points,the sensitivity analysis of the design variables were carried out,The comparison of the fitting accuracy shown that the response surface model had the highest accuracy,the approximate model of the cylindrical pressure structure based on the fourth-order response surface was obtained. the multi-objective optimization model was established,The second generation of non dominated sorting genetic algorithm was used to solving the multi-objective optimization problem,the results shown that the weight of the optimization scheme was reduced,while the ultimate strength was greatly improved,improved the performance of the cylindrical pressure structure.…”
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An Improved NSGA-II Algorithm for Transit Network Design and Frequency Setting Problem by Shushan Chai, Qinghuai Liang

“…In order to obtain the better network schemes, a multi-population genetic algorithm is proposed based on NSGA-II framework. …”
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Lightweight Design and Dynamics Analysis of ZYL-15000D Directional Drill Reducer by Xiaohong Zhao, Xianguo Yan, Zhi Chen, Hang Su

“…This paper selects the method of reducing the transmission ratio to optimize the size parameters of the reducer. MATLAB genetic algorithm is used in the optimization design, and the minimum volume of the rotary part reducer is taken as the objective of optimization design, while the design variables and constraints are determined. …”
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An efficient spectrum sensing of mixed kernel SVM based on sampling covariance matrix by Jianyuan NIE, Jianrong BAO, Bin JIANG, Chao LIU, Fang ZHU, Jianhai HE

“…In recent years,with the blind detection algorithms were proposed,more and more blind algorithms based on sampling covariance matrix were applied to spectrum sensing.The detection threshold was an approximation,and the detection performance would be affected for this algorithms.Thus,the mixed kernel function support vector machine (SVM) efficient spectrum sensing based on sampling covariance matrix was proposed.The statistics which were maximum minimum eigenvalue (MME) and covariance absolute value (CAV) of sensing signal sampling covariance matrices were used as the feature vectors of SVM and were trained to generate a spectrum sensing classifier.The advantage of this algorithm was that it needn’t calculate the detection threshold and the extraction of features reduces size of the sample set.The genetic algorithm (GA) was used to optimize the parameters of mixed kernel function SVM algorithm.The experimental results show that the proposed method has higher detection probability than MME and CAV algorithms,and has less sensing time than SVM,which has good practicability.…”
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Optimal Design of the Sealing Structure of a Hydraulic Cylinder on the Basis of a Surrogate Model by Hong Zhang, Yu Sun, Chenchen Li, Haoran Wang

“…Then, a surrogate model was fitted and optimised through a constrained Latin hypercube method, an interpolating recmultiquadric radial basis function method, and the genetic algorithm. The results indicate that the seal and seal groove structures obtained through optimisation with the surrogate model provide a superior sealing effect to unoptimised structures. …”
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Performance Evaluation of Antlion Optimizer Based Regulator in Automatic Generation Control of Interconnected Power System by Esha Gupta, Akash Saxena

“…The comparison of the regulator performance obtained from ALO is carried out with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Gravitational Search Algorithm (GSA) based regulators. …”
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