Efficiency management of engineering projects based on particle swarm multi objective optimization algorithm by Xiu Luo, Zhouxin Yi

“…This results indicated that the particle swarm optimization algorithm could provide efficient, cost-effective, and high-quality optimization solutions for engineering project management. …”
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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, a fuzzy controller is presented in order to achieve the maximum power in a solar cell. For improvement of the controller performance and achievement of the maximum power, the fuzzy controller variables are improved by the Grasshopper Optimization Algorithm (GOA). …”
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Improving Sleep Disorder Diagnosis Through Optimized Machine Learning Approaches by Md. Atiqur Rahman, Israt Jahan, Maheen Islam, Taskeed Jabid, Md Sawkat Ali, Mohammad Rifat Ahmmad Rashid, Mohammad Manzurul Islam, Md. Hasanul Ferdaus, Md Mostofa Kamal Rasel, Mahmuda Rawnak Jahan, Shayla Sharmin, Tanzina Afroz Rimi, Atia Sanjida Talukder, Md. Mafiul Hasan Matin, M. Ameer Ali

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Transportation Path Optimization of Modern Logistics Distribution considering Hybrid Tabu Search Algorithm by Jinjin Guo, Huiying Zhang, Guie Sun

“…The optimization of transportation path for distribution vehicles, which is about the mixed tabu search method, can not only reduce the cost but also improve the optimization of the vehicle transportation path. …”
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An Improved KF-RBF Based Estimation Algorithm for Coverage Control with Unknown Density Function by Lei Zuo, Maode Yan, Yaoren Guo, Wenrui Ma

“…Compared with the other estimation algorithms, a novel sampling regulation mechanism is designed to improve the estimation performance and reduce the computational load. …”
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BDCOA: Wavefront Aberration Compensation Using Improved Swarm Intelligence for FSO Communication by Suhas Shankarnahalli Krishnegowda, Arvind Kumar Ganesh, Parameshachari Bidare Divakarachari, Veena Yadav Shankarappa, Nijaguna Gollara Siddappa

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Multi-objective Optimal Design for Passive Part of Hybrid Active Power Filter Based on Bacterial Foraging and Particle Swarm Optimization by 李圣清, 李永安, 罗晓东, 曾黎琳, 何政平

“…With combination of particle swarm optimization algorithm and bacterial foraging optimization, an improved BFO-PSO optimized algorithm based on the random inertia factor and asynchronous time-dependent learning factor is used to solve optimal design,s problems of passive filter parameters for hybrid active filter. …”
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Productivity Improvement of Garments Industry by Implementing Line Balancing Algorithms—A Case Study by Mst. Anjuman Ara, Nafisa Anjum, Dilir Ahbab, Mushfica Takia Sidiika, Risat Rimi Chowdhury

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The Local Path Planning Algorithm for Amphibious Robots Based on an Improved Dynamic Window Approach by Xiaoqiang Dai, Chengye Liu, Qiang Lai, Xin Huang, Qingjun Zeng, Ming Liu

“…The speed resolution adaptive adjustment algorithm improves the ability to pass through a complex multiple-obstacle area, and the dynamic obstacle prediction algorithm optimizes obstacle avoidance paths. …”
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Directed energy deposition (DED) of Inconel 718-SS316 L bimetallic structures: Experimental investigations and optimization through artificial humming bird algorithm for improved h... by D. Rajamani, A.R. Vinod, K. Niranjan Reddy, M. Siva Kumar

“…This study reveals the insights into the development of bimetallic structures through DED process with their microstructures, process-property relationship and multi-response optimization through metaheuristic algorithms concerning the improved high strain rate and mechanical characteristics.…”
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Stability optimization of dynamic migration algorithm for Post-Copy of virtual machine based on KVM by Shuangxi CHEN, Ruoyan ZHAO, Hui LIU, Chunming WU, Wei RUAN

“…The dynamic migration technology of virtual machine provides a strong support for the resource scheduling of virtualization system.As one of the two core algorithms of virtual machine dynamic migration, Post-Copy algorithm has been a hot issue for scholars at home and abroad for its advantages of stable migration time and short migration downtime.The fault tolerance mechanism of virtual machine, the connection between the transfer mode of memory page and the page missing error during the migration process, and the source code of QEMU-KVM platform were studied.A fault tolerant method based on transaction synchronization was proposed to improve the stability of the Post-Copy migration algorithm.The experimental results show that the proposed algorithm can ensure the fast repair of deep end virtual machine failure, target virtual machine failure and network fault during the migration process, and solve the stability problem at a small cost.The method proposed effectively improves the stability of the Post-Copy migration algorithm, and provides reference for the future optimization research direction.…”
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Wind energy resource assessment based on joint wolf pack intelligent optimization algorithm. by Jiayuan Wang

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Optimal Location through Distributed Algorithm to Avoid Energy Hole in Mobile Sink WSNs by Li Qing-hua, Gui Wei-hua, Chen Zhi-gang

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Economic operation analysis of the power grid combining communication network and distributed optimization algorithm by Yi Zhifei

“…In the verification of the economic dispatch problem, the total output power of the distributed optimization algorithm reached 13594.87 MW, and the economic cost was reduced by about 23%. …”
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A FPGA Accelerator of Distributed A3C Algorithm with Optimal Resource Deployment by Fen Ge, Guohui Zhang, Ziyu Li, Fang Zhou

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Cold Chain Logistics Path Optimization with Adaptive Speed and Hybrid Genetic Algorithm Solution by Yuhui Sun, Dazhi Pan

“…Through comparison to other algorithms in the literature, the results show that the hybrid genetic algorithm not only improves customer satisfaction, but also maintains a lower total cost, which is obviously superior when solving the complex cold chain distribution path optimization problem; further comparison and analysis of the mathematical model in this paper with the single-dimension satisfaction model reveals that under the same satisfaction constraint threshold, the model in this paper can significantly reduce the system operating cost; we also deeply discuss the influence mechanism of vehicle traveling mode and customer point sparsity radius on distribution path planning.…”
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Development of algorithms for constructing two-dimensional optimal boundary-adaptive grids and their software implementation by A. E. Chistyakov, V. V. Sidoryakina, S. V. Protsenko

“…The application of such methods contributes to improving the accuracy, efficiency, and cost-effectiveness of computational algorithms.Materials and Methods. …”
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Optimizing demand charge of data center base on PE method by Yan HUANG, Peng WANG, Gao-hui XIE

“…Demand charge and energy charge are the two main components of data center electricity cost,previous re-searches have not take demand charge into consideration.PEDC algorithm was proposed by modeling time slot,work-load,service quality constraint and response time constraint.With PEDC algorithm peak power was decreased by partial execution on the condition of service quality constrai and response time constraint.PE method was executed in the heavy loaded time slots to reduce peak power so as to ize demand charge.Energy charge and total charge were also optimized.By comparing with four algorithms and with accurately predicted,PEDC algorithm can reduce elec-tricity cost by 5.9%~12.7% and improve cluster utilization 1.32 times.…”
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Optimization and Scheduling of Integrated Energy Systems with Hydrogen-electricity Coupling Based on PKO Algorithm by Wenli QIN, Na RONG, Xingyan LIU

“…To address the problems of getting stuck in local optima and slow convergence speed during the solution process, the Pied Kingfisher Optimizer (PKO) algorithm was introduced. [Result] The model aims to minimize the total system cost as the objective function, and solves for the optimal scheduling results of the output of each energy network unit; Compared with traditional optimization algorithms, PKO has a faster convergence speed and is better able to achieve the goal of global optimal solution.…”
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Improving Earth surface temperature forecasting through the optimization of deep learning hyper-parameters using Barnacles Mating Optimizer by Zuriani Mustaffa, Mohd Herwan Sulaiman, Muhammad ‘Arif Mohamad

“…This study proposes a hybrid forecasting model for Earth surface temperature using Deep Learning (DL). To improve the DL model's performance, an optimization algorithm called Barnacles Mating Optimizer (BMO) is integrated to optimize both weights and biases. …”
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