Prediction Model for Compaction Quality of Earth-Rock Dams Based on IFA-RF Model by Weiwei Lin, Yuling Yan, Pu Xu, Xiao Zhang, Yichuan Zhong

“…The method utilizes a dynamic inertia weight, an adaptive factor, and a differential evolution strategy to enhance the search capability of the firefly algorithm. …”
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Full Information Numerical Simulation of Two-Dimensional Steady Ground Temperature Field by Fan Jiang, Shikun Dai, Ying Zhang, Hongjun Tian

“…The background field is a uniform layered medium, and the anomalous field is converted into one-dimensional ordinary differential equations under different wavenumbers via one-dimensional full information Fourier transform. …”
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Improving Forecasts of the EGARCH Model Using Artificial Neural Network and Fuzzy Inference System by Geleta T. Mohammed, Jane A. Aduda, Ananda O. Kube

“…After the simulation, parameter estimation of the proposed model using a differential evolution algorithm on the simulated data is done. …”
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Stochastic robot failure management in an assembly line under industry 4.0 environment by Kuldip Singh Sangwan, Anirudh Tusnial, Suveg V Iyer

“…The paper demonstrates the superiority of the proposed model over the genetic algorithm and differential evolution models. The robustness of the proposed model is evaluated at different production rates. …”
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Parametric Model for Coaxial Cavity Filter with Combined KCCA and MLSSVR by Shengbiao Wu, Huaning Li, Xianpeng Chen

“…First, the low-dimensional tuning data is mapped to the high-dimensional feature space by kernel canonical correlation analysis, and the nonlinear feature vectors are fused by the kernel function; second, the multioutput least squares support vector regression algorithm is used for parametric modeling to solve the problems of low accuracy and poor prediction performance; third, the support vector of the parameter model is optimized by the differential evolution whale algorithm (DWA) to improve the convergence and generalization ability of the model in actual tuning. …”
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基于混合蛙跳算法的齿轮传动优化设计 by 何兵, 车林仙, 刘初升

“…The hybrid optimization algorithm（HODEFL） overcame the disadvantages on low precision and premature convergence of shuffled frog leaping algorithm（SFLA） for high-dimensional optimization by taking advantages of strong global search and rapid convergence of DE/best/2/bin（DEb2） in differential evolution algorithm（SDE）.The SFLA and DE are hybridized to form a hybrid optimization algorithm（HODEFL） in order to overcome the disadvantages of the SFLA.The study object is the optimization design of the cylindrical helical gear reducer,establishing minimum volume.By comparing with the improved particle swarm optimization（LWPSO）,SFLA and with DEb2 evolutionary algorithm,the HODEFL algorithm is superior to other three algorithms in terms of optimization efficiency,computational accuracy and robustness.…”
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Multiobjective Optimization Design of a Fractional Order PID Controller for a Gun Control System by Qiang Gao, Jilin Chen, Li Wang, Shiqing Xu, Yuanlong Hou

“…To solve the specified nonlinear optimization problem, a novel Pareto optimal solution based multiobjective differential evolution algorithm is proposed. To enhance the convergent rate of the optimization process, an opposition based learning method is embedded in the chaotic population initialization process. …”
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Minimizing the Active Power Losses and Retaining the Voltage Profile of the Distribution System Using Soft Computing Techniques with DG Source by P. Sundararaman, E. Mohan, S. V. Aswin Kumer, Sridhar Udayakumar, Abdissa Fekadu Moti

“…The proposed BAT algorithm has been executed with the MATLAB 2016 software and compared with the differential evolution technique for IEEE 33 bus, IEEE 69 bus, and Indian real time 62 bus systems. …”
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Numerical Simulation Study on the Strengthening Mechanism of Rock Materials under Impact Loads by Xin Liu, Kai Wang, Chunan Tang, Xikun Qian

“…The orthogonal design and range method are used to analyze the sensitivity of the dynamic damage constitutive parameters, and a differential evolution algorithm is used to invert the relevant parameters of the constitutive model. …”
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A Comparison of Inversion Methods for Surrogate‐Based Groundwater Contamination Source Identification With Varying Degrees of Model Complexity by Zhenbo Chang, Zhilin Guo, Kewei Chen, Zibo Wang, Yang Zhan, Wenxi Lu, Chunmiao Zheng

“…Each method has its own advantages and disadvantages under specific site conditions. To evaluate the applicability of these methods, we chose one representative inversion algorithm from each category, namely the Improved Butterfly Optimization Algorithm (IBOA) for simulation optimization, the Ensemble Smoother with Multiple Data Assimilation (ES‐MDA) for data assimilation, and the DiffeRential Evolution Adaptive Metropolis with a Snooker Update and Sampling from a Past Archive (DREAM(ZS)) for Bayesian inference. …”
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An Effective ABC-SVM Approach for Surface Roughness Prediction in Manufacturing Processes by Juan Lu, Xiaoping Liao, Steven Li, Haibin Ouyang, Kai Chen, Bing Huang

“…Further, to evaluate the optimization performance of ABC in parameters determination of SVM, this study compares the prediction performance of SVM models optimized by well-known evolutionary and swarm-based algorithms (differential evolution (DE), genetic algorithm (GA), particle swarm optimization (PSO), and ABC) and analyzes ability of these optimization algorithms from their optimization mechanism and convergence speed based on experimental datasets of turning and milling. …”
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Peningkatan Akurasi Metode Weighted Fuzzy Time Series Forecasting Menggunakan Algoritma Evolusi Differensial dan Fuzzy C-Means by Agus Fachrur Rozy, Solimun Solimun, Ni Wayan Surya Wardhani

“…There are two commonly applied approaches: the Differential Evolution (DE) algorithm and Fuzzy C-Means (FCM). …”
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Multi-Objective Optimization of Three-Stage Turbomachine Rotor Based on Complex Transfer Matrix Method by Hüseyin Tarık Niş, Ahmet Yıldız

“…In order to design a more efficient structure of a three-stage turbomachine rotor, we integrated this method with various optimization algorithms, including genetic algorithm (GA), differential evolution (DE), simulated annealing (SA), gravitational search algorithm (GSA), black hole (BH), particle swarm optimization (PSO), Harris hawk optimization (HHO), artificial bee colony (ABC), and non-metaheuristic pattern search (PS). …”
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Modeling of the Power Station Boiler Combustion Efficiency Considering Multiple Work Condition with Feature Selection by TANG Zhenhao, WU Xiaoyan, CAO Shengxian

“…It is difficult for power station boiler efficiency to measure precisely A datadriven modeling method is proposed to establish the boiler combustion efficiency model, according to the machine learning theories A classification and regression trees (CART) algorithm provides correlated variables which have significant relation with the boiler combustion efficiency by data analysis Then, a KNearest Neighbor (KNN) classifies the samples to distinguish the data from different work conditions Based on the classified data, a least square support vector machine (LSSVM) optimized by differential evolution (DE) algorithm is proposed to establish a datadriven model (DDMMF) The parameters of LSSVM are optimized dynamically by DE to improve the model accuracy Finally, the prediction model is corrected dynamically for further improvement of the prediction accuracy The experimental results based on actual production data illustrate that the proposed approach can predict the boiler combustion efficiency accurately, which meets the requirements of boiler control and optimization…”
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Multistage Threshold Segmentation Method Based on Improved Electric Eel Foraging Optimization by Yunlong Hu, Liangkuan Zhu, Hongyang Zhao

“…To optimize threshold selection in color image segmentation, this paper proposes a multi-strategy improved Electric Eel Foraging Optimization (MIEEFO). The proposed algorithm integrates Differential Evolution and Quasi-Opposition-Based Learning strategies into the Electric Eel Foraging Optimization, enhancing its search capability, accelerating convergence, and preventing the population from falling into local optima. …”
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Rolling Bearing Fault Diagnosis Method Based on Improved Variational Mode Decomposition and Information Entropy by Wen FAN, Lian GE, Xiaoting XIAO, Fangji GAN, Xin LAI, Hongxia DENG, Qi HUANG

“…A new fitness function combining differential evolution (DE) algorithm with gray wolf optimization (GWO) algorithm is proposed to form a new hybrid optimization algorithm, named DEGWO. …”
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Chance-Constrained Optimization of Photovoltaic System Allocation considering Power Loss, Voltage Level, and Line Current by Ibrahim Cagri Barutcu

“…In this paper, uncertainty scenarios are handled with Monte Carlo Simulation (MCS) under genetic algorithm (GA) and differential evolution- (DE-) based optimization, and probability distribution functions (pdf) of bus voltages and line current are obtained to be used in chance-constrained stochastic programming. …”
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Service Composition and Optimal Selection for Industrial Software Integration with QoS and Availability by Yangzhen Cao, Shanhui Liu, Chaoyang Li, Hongen Yang, Yuanyang Wang

“…To efficiently solve the proposed model, a hybrid enhanced multi-objective Gray Wolf Optimizer (HEMOGWO) was developed. This algorithm integrated Tent chaotic mapping and a Levy flight-enhanced differential evolution (DE) strategy. …”
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Investigation on Evolutionary Computation Techniques of a Nonlinear System by Tran Trong Dao

“…A nonlinear mathematical model is required to describe the dynamic behaviour of batch process; this justifies the use of evolutionary method of the EAs to deal with this process. Four algorithms from the field of artificial intelligent—differential evolution (DE), self-organizing migrating algorithm (SOMA), genetic algorithm (GA), and simulated annealing (SA)—are used in this investigation. …”
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Efficient control strategy for electric furnace temperature regulation using quadratic interpolation optimization by Serdar Ekinci, Davut Izci, Veysel Gider, Laith Abualigah, Mohit Bajaj, Ievgen Zaitsev

“…To ensure optimal performance, the parameters of the RPIDD2 controller are optimized using metaheuristic algorithms, including the flood optimization algorithm (FLA), reptile search algorithm (RSA), particle swarm optimization (PSO) and differential evolution (DE). …”
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