Enhancing computational efficiency in solving Knapsack problem: insights from algorithmic parallelization and optimization by Bashar Bin Usman, Okeyinka Aderemi Elisha, Ibrahim Abdullahi, Idris Rabiu, Adamu Isah, Abdulganiyyu Abdulrahman

“…Hence, the application of approximate algorithms is usually considered when encountering this optimization problem. …”
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DGA malicious domain name identification based on XGBoost and particle swarm optimization algorithm by CHEN Zesheng, ZHOU Min, FENG Lichun, CHEN Weijie

“…Experimental results demonstrate that the XGBoost model optimized by PSO exhibits improved performance in DGA malicious domain classification. …”
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Optimization of Business English Teaching Based on the Integration of Interactive Virtual Reality Genetic Algorithm by Xiao Ma

“…The results of the simulation experiment indicate that the improved algorithm designed in this article can reduce the computational overhead of the meta-algorithm to a great extent, and the improvement strategy is designed based on the evaluation results of practical examples.…”
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Quality of service optimization algorithm based on deep reinforcement learning in software defined network by Cenhuishan LIAO, Junyan CHEN, Guanping LIANG, Xiaolan XIE, Xiaoye LU

“…Deep reinforcement learning has strong abilities of decision-making and generalization and often applies to the quality of service (QoS) optimization in software defined network (SDN).However, traditional deep reinforcement learning algorithms have problems such as slow convergence and instability.An algorithm of quality of service optimization algorithm of based on deep reinforcement learning (AQSDRL) was proposed to solve the QoS problem of SDN in the data center network (DCN) applications.AQSDRL introduces the softmax deep double deterministic policy gradient (SD3) algorithm for model training, and a SumTree-based prioritized empirical replay mechanism was used to optimize the SD3 algorithm.The samples with more significant temporal-difference error (TD-error) were extracted with higher probability to train the neural network, effectively improving the convergence speed and stability of the algorithm.The experimental results show that the proposed AQSDRL effectively reduces the network transmission delay and improves the load balancing performance of the network than the existing deep reinforcement learning algorithms.…”
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SMOTE algorithm optimization and application in corporate credit risk prediction with diversification strategy consideration by Han Wei

“…Empirical results demonstrate the optimized SMOTE algorithm’s superiority over six comparison models, such as random over-sampling, under-sampling, etc. …”
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Optimizing Crop Yield Prediction: An In-Depth Analysis of Outlier Detection Algorithms on Davangere Region by C. S. Anu, C. R. Nirmala, A. Bhowmik, A. Johnson Santhosh

“…This method demonstrated improved performance in refining the crop yield prediction model by identifying and removing outliers, thereby contributing to more accurate predictions and optimized planning in the dynamic landscape of the Davangere region.…”
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Energy optimization using adaptive control algorithm to enhance the performance of SDN_IOT environment by I. Varalakshmi, M. Thenmozhi

“…The system reduces energy consumption by 18%, improves detection accuracy by 2% (from 97.5% to 99.4%), and lowers the false positive rate to 0.01% compared to existing algorithms. …”
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Fruit-Fly-Optimized Weighted Averaging Algorithm for Data Fusion in MEMS IMU Array by Ting Zhu, Gao Peng, Jianping Li, Jiawei Xuan, Jingbei Tian

“…In this study, an optimal weighted averaging algorithm based on the fruit fly optimization algorithm (FOA) is proposed by analyzing the data fusion mechanism of the MEMS IMU array. …”
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Multi-objective optimization of dual-stator permanent magnet motor based on composite algorithm by Xiaoguang Kong, Zhuo Yang

“…Then, the Taguchi method optimizes the significant variables, the genetic algorithm based on the Kriging response surface model optimizes the non-significant variables, and finally, the optimal solution is selected on the Pareto front. …”
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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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A GD-PSO Algorithm for Smart Transportation Supply Chain ABS Portfolio Optimization by Yingjia Sun, Hongfeng Ren

“…In this article, a penalty function based on graph density (GD) was introduced to the particle swarm optimization algorithm (PSO), and a GD-PSO algorithm was proposed. …”
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A Fast Satellite Selection Algorithm Based on Hierarchical Clustering and Iterative Subset Optimization by Dan Jing, Weidie Li, Liang Han, Xinchen Li, Liangchao Li, Yan Zhang, Liang Guo, Mengdao Xing

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Flow direction algorithm for optimal coordination of directional overcurrent relays considering arc flash by Dina K. Mahmoud, Shady H．E．Abdel Aleem, Ahmed M. Ibrahim, Mahmoud M. Sayed, Wael Abdelfattah

“…This paper presents a novel meta-heuristic optimization method called flow direction algorithm (FDA) to achieve optimal coordination of Directional Overcurrent Relays (DOCRs) while considering the impact of Arc Flash (AF). …”
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Load optimization of cogeneration units based on intuitive multi-objective fish swarm algorithm by Xueqiang Shen, Jiaxin Wang

“…Convergence direction is adaptively adjusted using intuitionistic fuzzy entropy, with Pareto frontier solutions determining optimal load allocation. Evaluated via the Zitzler-Deb-Thiele (ZDT) benchmark functions, IFEMOAFSA achieves a 42.63% comprehensive performance improvement over four benchmark algorithms, verified by Mean Inverted Generational Distance (MIGD) and Mean Hypervolume Metric (MHV). …”
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Optimization of the control system of BP-PID rice polishing unit based on WAO algorithm by HUANG Jinliang, ZHOU Jin, YU Wei

“…ObjectiveAddress the current issues of poor internal flow stability, low single-machine efficiency, and subpar polishing quality in rice polishing units.MethodsFirstly, the traditional polishing machine was improved, its control parameters were clarified, and the mathematical model of the rice polishing unit was established. …”
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Retracted: VR Panorama Mosaic Algorithm Based on Particle Swarm Optimization and Mutual Information by Zhonggao Yang, Dan Xiang, Yili Cheng

“…This algorithm is based on particle swarm optimization, combined with the advantages of traditional mutual information algorithm, according to the characteristics of virtual reality imaging, a new model is established. …”
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Portfolio optimization with MOPSO-Shrinkage hybrid model by Minh Tran, Nhat M. Nguyen

“…Unlike traditional shrinkage covariance models, which struggle in highly dynamic environments, our hybrid model optimally selects stocks and improves risk-adjusted returns. …”
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Practical Application of Complementary Regulation Strategy of Run-of-River Small Hydropower and Distributed Photovoltaic Based on Multi-Scale Copula-MPC Algorithm by Xianpin Zhu, Weibo Li, Shuai Cao, Wei Xu

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Smart homes energy management: Optimal multi-objective appliance scheduling model considering electrical energy storage and renewable energy resources by Moslem Dehghani, Seyyed Mohammad Bornapour

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Synergizing neural networks with multi-objective thermal exchange optimization and PROMETHEE decision-making to improve PCM-based photovoltaic thermal systems by Yongxin Li, Ali Basem, As'ad Alizadeh, Pradeep Kumar Singh, Saurav Dixit, Hanaa Kadhim Abdulaali, Rifaqat Ali, Pancham Cajla, Husam Rajab, Kaouther Ghachem

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