Reconstructing rearrangement phylogenies of natural genomes by Leonard Bohnenkämper, Jens Stoye, Daniel Doerr

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Corrosion rate prediction for long-distance submarine pipelines based on MWIWOA-SVM by Zhengshan LUO, Haipeng LYU, Jihao LUO

“…MethodsTo address these issues, Multi-Way Improved Whale Optimization Algorithm (MWIWOA) was proposed to optimize the SVM-based prediction model for the internal corrosion rate of long-distance submarine pipelines. …”
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基于改进Kriging模型的主动学习可靠性分析方法 by 陈哲, 杨旭锋, 程鑫

“…,the differential evolution algorithm is introduced to explore the optimal parameter of Kriging model and improve the accuracy of Kriging prediction information.As a result,the training point in each iteration is guaranteed to be the global optimal one and the efficiency of ALK model is largely improved.…”
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Intelligent Assessment of Personal Credit Risk Based on Machine Learning by Chuansheng Wang, Hang Yu

“…Then, the XGBoost algorithm is used to evaluate the credit risk level of customers, and the traditional Sparrow Search Algorithm is improved by using Tent chaotic mapping, sine and cosine search, reverse learning, and Cauchy mutation strategy to improve the optimization performance of algorithm parameters. …”
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Maximum Power Exploitation of Photovoltaic System under Fast-Varying Solar Irradiation and Local Shading by Yi-Jui Chiu, Bi Li, Chin-Ling Chen, Shui-Yang Lien, Ding Chen, Ji-Ming Yi, Yung-Hui Shih

“…The influence of the PV output power characteristics and local shading on the power generation efficiency of the PV system was analyzed using MATLAB and the improved model. Aiming at the problem that most maximum power point tracking (MPPT) algorithms have difficulty quickly tracking the maximum power point (MPP) under fast-varying solar irradiation; a polynomial fitting-MPPT (PF-MPPT) algorithm and a simple fitting-MPPT (SPF-MPPT) algorithm based on polynomial fitting were proposed to track the maximum power point under the fast-varying solar irradiation. …”
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Research on the application of deep learning based video recognition for power plant leakage and dripping by Zhang Yuan, Si Yuan

“…Then, by combining semantic segmentation, data augmentation, attention mechanisms, and changing activation functions with convolutional neural networks, the YOLOv5 algorithm is deeply optimized, including improvements in training strategies and model evaluation adjustments. …”
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Design of the College Students’ Music Big Data Management System Based on Computer Assistance by Peng Cheng

“…With the rapid development of science and technology, the college music big data management system also needs a computer-aided data model for optimization. In order to improve the efficiency of computer-aided teaching of the music big data management system in colleges and universities, this paper analyzes and processes the music database of music software based on the computer-aided Bayesian algorithm and establishes a Bayesian model. …”
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Movie Box Office Prediction Based on IFOA-GRNN by Wei Lu, Xiaoqiao Zhang, Xinchen Zhan

“…The contribution of this article is to propose a generalized regression neural network model based on an improved fruit fly optimization algorithm, which can greatly improve the accuracy of movie box office prediction.…”
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基于进化计算的多任务可调机构刚体导引综合 by 杨志刚, 徐礼钜, 林光春, 张均富

“…The method of rigid-body guidance synthesis of adjustable mechanisms for multiple alternation tasks based on evolutionary computation is proposed.The mechanism optimization model of multi-tasks is established,and the global optimization solution will be gained easily by using evolutionary computation.The algorithm of evolutionary computation is improved.A method that can adaptively adjust mutation rate and mutation value according to fitness of individual is proposed,which can effectively improve the evolutionary speed and the accuracy of the solutions.Two numeric examples are given to illustrate the method.…”
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Classification Prediction of Rockburst in Railway Tunnel Based on Hybrid PSO-BP Neural Network by Min Zhang

“…Then, the BP neural network is improved by using particle swarm optimization (PSO) combined with the simulated annealing algorithm. …”
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Green Energy Strategic Management for Service of Quality Composition in the Internet of Things Environment by Jianhao Gao

“…The simulation results reveal that MFO has good optimization effect in the abovementioned models, and the optimization effect of MFO is improved by 8% and 6% compared with the genetic algorithm and particle swarm optimization, so as to realize the green energy strategic management of QoS composition in the environment of IoT.…”
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Electricity Demand Projection Using a Path-Coefficient Analysis and BAG-SA Approach: A Case Study of China by Qunli Wu, Chenyang Peng

“…The BAG-SA algorithm is employed to optimize the coefficients of the multiple linear and quadratic forms of electricity demand estimation model. …”
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Group Stable Matching Problem in Freight Pooling Service of Vehicle–Cargo Matching Platform by Linlin Kong, Min Huang

“…Based on the characteristics of the problem, the algorithm is improved by removing ineffective constraints and only using key constraints, significantly reducing computational complexity, optimizing the solving process, and greatly improving the model’s solution efficiency. …”
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Research on Short-Term Load Forecasting of LSTM Regional Power Grid Based on Multi-Source Parameter Coupling by Bo Li, Yaohua Liao, Siyang Liu, Chao Liu, Zhensheng Wu

“…In order to further optimize the performance of the LSTM model, the IPSO algorithm, and linear difference decreasing inertia weight are introduced to improve the global optimization ability and convergence speed of the PSO algorithm and reduce the risk of local optimal solutions. …”
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Node selection based on label quantity information in federated learning by Jiahua MA, Xinghua SUN, Wenchao XIA, Xijun WANG, Hongzhou TAN, Hongbo ZHU

“…Aiming at the problem that the difference of node data distribution has adverse effect on the performance of federated learning algorithm, a node selection algorithm based on label quantity information was proposed.An optimization objective based on the label quantity information of nodes was designed, considering the optimization problem of selecting the nodes with balanced label distribution under a certain time consumption limit.According to the correlation between the aggregated label distribution of selected nodes and the convergence of the global model, the upper bound of the weight divergence of the global model was reduced to improve the convergence stability of the algorithm.Simulation results shows that the new algorithm had higher convergence efficiency than the existing node selection algorithm.…”
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基于遗传-二次规划法的封闭差动人字齿轮传动系统混合优化设计 by 朱增宝, 朱如鹏, 尹敏

“…Using the positive transmission way of modified gear,a mathematical optimization model of the encased differential herringbone gear transmission system is set up by taking the lightest gear weight of this transmission system as the optimization objective.Taking the advantage of its optimization function of genetic algorithm and quadratic programming algorithm in MATLAB toolbox,the compound optimization design is carried out.The research results show that the problem of which the initial value of quadratic programming is difficult to determine is solved well by using the results of the genetic algorithm as the initial value of quadratic programming optimization.Compared with the genetic algorithm or quadratic programming,the optimization design variables of this compound optimization are obviously improved and the gear weight of the system is markedly reduced.The compound optimization method provides a simple and practical solution to obtain precise global optimal solution of the large-scale nonlinear constraint optimization.…”
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Node selection based on label quantity information in federated learning by Jiahua MA, Xinghua SUN, Wenchao XIA, Xijun WANG, Hongzhou TAN, Hongbo ZHU

“…Aiming at the problem that the difference of node data distribution has adverse effect on the performance of federated learning algorithm, a node selection algorithm based on label quantity information was proposed.An optimization objective based on the label quantity information of nodes was designed, considering the optimization problem of selecting the nodes with balanced label distribution under a certain time consumption limit.According to the correlation between the aggregated label distribution of selected nodes and the convergence of the global model, the upper bound of the weight divergence of the global model was reduced to improve the convergence stability of the algorithm.Simulation results shows that the new algorithm had higher convergence efficiency than the existing node selection algorithm.…”
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液压挖掘机工作装置综合优化研究 by 姜饶保, 黄斌, 何清华, 贺继林

“…The backhoe working device of hydraulic excavator is a typical openedchain four-bar mechanism,the distribution of it’s joints is very important to the working performance and useful life.It’s hard to get the satisfactory optimal result by routine methods.So,an integrative optimization model of working device is built to be optimized using genetic algorithm.The experimental results show that the integrative optimization method based on genetic algorithm is faster and more effective than traditional optimization method;the integrative working performance of the improved working device is improved largely.…”
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Startup Drift Compensation of MEMS INS Based on PSO–GRNN Network by Songlai Han, Jingyi Xie, Jing Dong

“…In the process of training this model, we used the PSO algorithm to optimize the spread parameter of the PSO-GRNN model. …”
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Cost-efficient dynamic quota-controlled routing in multi-community delay-tolerant networks by Jiagao Wu, Yue Ma, Linfeng Liu

“…To solve this problem, we propose an improved genetic algorithm called genetic algorithm for delivery probability and time-to-live optimization for the dynamic quota-controlled routing scheme to reduce the routing cost further. …”
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