Multi-objective cloud workflow scheduling algorithm based on grid variance by Xiaoan BAO, Yundi CAO, Na ZHANG, Junyan QIAN, Jianwen CAO

“…Multi-objective cloud workflow scheduling algorithm based on grid variance and the strategy of bad particles self-learning were presented.Firstly,the characteristics of task scheduling was token into consideration,and particle encoding was discredited.Secondly,the strategy of mapping Pareto optimal workflow scheduling set to self-adaptive grid coordinate system,and calculating the grid distribution value of each Pareto optimal solution was used.Thirdly,grid variance was adopted to evaluate the diversity of current Pareto front and dynamically adjust evolution strategies.Finally,the concept of being dominated times was introduced into bad particles self-learning strategy for filtering out bad particles in population.The simulation experiment shows that workflow scheduling solution set by this algorithm is better than the MOPSO algorithm on both IGD and S performance indexes,and the optimal value is superior to the ε-FDPSO and NSGA-Ⅱ algorithm.…”
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Smart System Resource Coordination Algorithm Based on 6G Technology by Fang Wang

“…This paper combines 6G technology to study the smart system resource coordination algorithm and analyzes the calculation process and actual effect of the algorithm. …”
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Implementation of Evolution Strategies (ES) Algorithm to Optimization Lovebird Feed Composition by Agung Mustika Rizki, Wayan Firdaus Mahmudy, Gusti Eka Yuliastuti

“…<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span>Lovebird current society, especially popular among bird lovers. …”
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Comparative Study of Some New Hybrid Fuzzy Algorithms for Manipulator Control by Sudeept Mohan, Surekha Bhanot

“…In this paper, some new hybrid fuzzy control algorithms have been proposed for manipulator control. …”
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Methods and Algorithms for Flexible Job Shop Scheduling − A State of the Art by Guliashki Vassil, Kirilov Leoneed, Marinova Galia

“…On the other hand, the ways to solve this type of problems include exact methods and heuristic or metaheuristic algorithms. This paper the aim to review the progress of research in the field of solving FJSSP over the last 10 years, as well as to show current trends for future scientific developments in this area.…”
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Sparse adaptive constant blind equalization algorithm for sparse multipath channel by Si-yang MA, Hua PENG, Bin WANG

“…In order to improve the convergence rate of the blind equalizer for sparse multipath channel,a novel blind equalization approach called l₀-norm constraint proportionate normalized least mean square constant algorithm was proposed for M-order phase-shift keying (MPSK) signal.Based on the constant modulus characteristics of MPSK signal and the sparse property of equalizer,a new blind equalization cost function with the l₀-norm penalty on the equalizer tap coefficients was firstly constructed.Then the update formula of the tap coefficients was derived according to the gradient descent algorithm.Moreover,the iteration step was updated by drawing upon the normalized proportionate factor.The algorithm not only assigned step sizes proportionate to the magnitude of the current individual tap weights,but also attracted the inactive taps to zero adaptively.Theoretical analysis and simulation results show that the proposed algorithm outperforms the existing blind equalization algorithms for sparse channel in reducing ISI and improving convergence rate.…”
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High-performance federated continual learning algorithm for heterogeneous streaming data by Hui JIANG, Tianliu HE, Min LIU, Sheng SUN, Yuwei WANG

“…Aiming at the problems of poor model performance and low training efficiency in training streaming data of AI models that provide intelligent services, a high-performance federated continual learning algorithm for heterogeneous streaming data (FCL-HSD) was proposed in the distributed terminal system with privacy data.In order to solve the problem of the current model forgetting old data, a model with dynamically extensible structure was introduced in the local training stage, and an extension audit mechanism was designed to ensure the capability of the AI model to recognize old data at the cost of small storage overhead.Considering the heterogeneity of terminal data, a customized global model strategy based on data distribution similarity was designed at the central server side, and an aggregation-by-block manner was implemented for different modules of the model.The feasibility and effectiveness of the proposed algorithm were verified under various data increment scenarios with different data sets.Experimental results show that, compared with existing works, the proposed algorithm can effectively improve the model performance to classify old data on the premise of ensuring the capability to classify new data.…”
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SYNTHESIS OF VIRTUAL ENTERPRISE BASED ON COMBINATION OF WEB-SERVICES AND THE ALGORITHM OF DELIVERY by Victor P. Romanov, Aleksandra O. Varfolomeeva

“…The authors propose to use the theory of formal grammar as a means of supporting the automated composition of services of virtual enterprise based on algorithms of intellectual planning.…”
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Review of plant disease image recognition algorithms based on deep learning by Yang Hankun, Zhu Bowei, Zhang Yanmin, Xu Yidong

“…This article reviews the current status, challenges, and future directions of deep learning in plant disease identification. …”
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Optimization Design of Hub Reducer Based on Improved Sparrow Search Algorithm by LI Jian-wei, YU Guang-bin

“…The algorithm introduces the particle symbiosis mechanism and Levy flight mechanism， uses the current individual to balance the individual， and is guided only by the historical optimal individual and the global optimal individual. …”
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An Application of Genetic Algorithm in Determining Salesmen’s Routes: A Case Study by Noufal Zhafira, Feri Afrinaldi, Taufik

“…The problem is solved by employing genetic algorithm (GA) and a Matlab® based computer program is developed to run the algorithm. …”
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A Hybrid Lightning Search Algorithm-Simplex Method for Global Optimization by Yuting Lu, Yongquan Zhou, Xiuli Wu

“…Simplex method (SM) iteratively optimizes the current worst step leaders to avoid the population searching at the edge, thus improving the convergence accuracy and rate of the algorithm. …”
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High-performance federated continual learning algorithm for heterogeneous streaming data by Hui JIANG, Tianliu HE, Min LIU, Sheng SUN, Yuwei WANG

“…Aiming at the problems of poor model performance and low training efficiency in training streaming data of AI models that provide intelligent services, a high-performance federated continual learning algorithm for heterogeneous streaming data (FCL-HSD) was proposed in the distributed terminal system with privacy data.In order to solve the problem of the current model forgetting old data, a model with dynamically extensible structure was introduced in the local training stage, and an extension audit mechanism was designed to ensure the capability of the AI model to recognize old data at the cost of small storage overhead.Considering the heterogeneity of terminal data, a customized global model strategy based on data distribution similarity was designed at the central server side, and an aggregation-by-block manner was implemented for different modules of the model.The feasibility and effectiveness of the proposed algorithm were verified under various data increment scenarios with different data sets.Experimental results show that, compared with existing works, the proposed algorithm can effectively improve the model performance to classify old data on the premise of ensuring the capability to classify new data.…”
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Investigation of temperature distribution in friction stir welding with experimental and regression algorithms by Mehmet Erbil Özcan

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Distributed data trading algorithm based on multi-objective utility optimization by Xiaohong HUANG, Yong ZHANG, Desheng SHAN, Yekui QIAN, Lu HAN, Dandan LI, Qun CONG

“…The traditional centralized data trading models are not well applicable to the current intelligent era where everything is interconnected and real-time data is generated, and in order to maximize the use of collected data, it is essential to design an effective data trading framework.Therefore, a distributed data trading framework based on consortium blockchain was proposed, which realized P2P data trading without relying on a third party.Aiming at the problem that existing data trading models only consider the factors of the data itself and ignore the factors related to user tasks, a bi-level multi-objective optimization model was constructed based on multi-dimensional factors, such as data quality, data attributes, attribute relevance and consumer competition, to optimize the utilities of data provider (DP) and data consumer (DC).To solve the above model, an improved multi-objective genetic algorithm-collaborative NSGAII was proposed, calculated by the cooperation of DP, DC and data aggregator (AG).The simulation results show that the collaborative NSGAII achieves better performance in terms of the utilities of DP and DC, thus realizing more effective data trading.…”
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Battery State of Health Estimation Methods: Implementation and Comparison of 11 Algorithms by Eojin Kim, Sunghun Jung

“…Through detailed comparative analysis, this study not only guides researchers and practitioners in selecting optimal SOH estimation techniques but also lays the groundwork for innovative hybrid algorithm development to address limitations in current battery management systems. …”
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Maintenance and Operation Optimization Algorithm of PV Plants under Multiconstraint Conditions by Chi Hua, Liang Kuang, Dechang Pi

“…However, most of the photovoltaic power stations in China fail to rationally optimize the utilization of resources and time. The current study puts forward effort implementation via genetic algorithm-based multiconstrained optimization methodology. …”
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Meta-path convolution based heterogeneous graph neural network algorithm by QIN Zhilong, DENG Kun, LIU Xingyan

“…Extensive experiments were carried out on ACM, IMDB and DBLP datasets, and compared with the current mainstream algorithms. The experimental results show that the average increase of Macro-F1 in the node classification task is 0.5%～3.5%, and the ARI value in the node clustering task is increased by 1%～3%, which proves that the algorithm is effective and feasible.…”
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Cultural Value and Strategy of Ethnic Music Based on Distribution Estimation Algorithm by Junyan Shi, Qinliang Ning

“…The current social construction process is gradually accelerating, and people’s growing spiritual and cultural needs are eager to be satisfied. …”
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Low-Power Indoor Positioning Algorithm Based on iBeacon Network by Xiaona Zhang, Shufang Zhang, Shuaiheng Huai

“…In this article, we use a low-power iBeacon network to conduct an in-depth analysis and research on the principle of indoor positioning and adopt an efficient and fast positioning algorithm. Secondly, based on the obtained analysis, an iBeacon-based indoor positioning system is proposed to analyze how to use iBeacon for accurate positioning and whether it can effectively compensate for the current mainstream positioning system. …”
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