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  1. 2481

    Performance evaluation of an adopted model based on big-bang big-crunch and artificial neural network for cloud applications by Pradeep Rawat, Robin Singh Bhadoria, Punit Gupta, Priti Dimri, G. P. Saroha

    Published 2021-08-01
    “…Cloud can accomplish this using efficient scheduling algorithm. This article focuses on task scheduling policy which aims to improve the performance in real-time with the least execution time, network cost and execution cost-effective at the same time. …”
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    Article
  2. 2482

    Research on 3D Obstacle Avoidance Path Planning for Apple Picking Robotic Arm by Xinyan Chen, Chun Lu, Ziliang Guo, Chengkai Yin, Xuanbo Wu, Xiaolan Lv, Qing Chen

    Published 2025-04-01
    “…The experimental results show that compared to RRT* and IRRT*, the average path cost of the optimization algorithm is reduced by 31.565 mm and 14.935 mm and the average search time is reduced by 7.18 s and 4.33 s. …”
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    Article
  3. 2483

    Enhancing 4G/LTE Network Path Loss Prediction with PSO-GWO Hybrid Approach by Messaoud Garah, Nabil Boukhennoufa

    Published 2025-07-01
    “…The Hata, COST231, Egli, and SUI models are among the most widely used in urban and suburban environments. …”
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  4. 2484

    Multidisciplinary Collaborative Reliability Analysis of the Gear Reducer based on Inverse Reliability Strategy by Wang Liangliang, Peng Jinshuan, Shao Yiming

    Published 2015-01-01
    “…To overcome the high computational cost of reliability analysis,a reliability analysis method which combines the multidisciplinary genetic algorithm collaborative optimization( GA- CO) based on the inverse reliability strategy( IRS) is proposed( IRS- GA- CO). …”
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    Article
  5. 2485

    Multi-Depot Pickup and Delivery Problem with Resource Sharing by Yong Wang, Lingyu Ran, Xiangyang Guan, Yajie Zou

    Published 2021-01-01
    “…Resource sharing (RS) integrated into the optimization of multi-depot pickup and delivery problem (MDPDP) can greatly reduce the logistics operating cost and required transportation resources by reconfiguring the logistics network. …”
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    Article
  6. 2486

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

    Published 2025-05-01
    “…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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  7. 2487

    Spatio‐temporal dynamic navigation for electric vehicle charging using deep reinforcement learning by Ali Can Erüst, Fatma Yıldız Taşcıkaraoğlu

    Published 2024-12-01
    “…In a data sharing system including transportation network, an electric vehicle (EV) and EV charging stations (EVCSs), it is aimed to determine the most convenient EVCS and the optimal path for reducing the travel, charging and waiting costs. …”
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    Article
  8. 2488

    Microservice Deployment Based on Multiple Controllers for User Response Time Reduction in Edge-Native Computing by Zhaoyang Wang, Jinqi Zhu, Jia Guo, Yang Liu

    Published 2025-05-01
    “…Finally, extensive simulation experiments were conducted to validate the effectiveness of the proposed algorithm. The experimental results demonstrate that, compared with other algorithms, our algorithm significantly improves user response time, optimizes resource utilization, and reduces the total cost.…”
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    Article
  9. 2489

    Power Allocation Technology of Long Time Multi-Star Hopping Beam for LEO Satellite by Ziyi LIU, Xiaoning ZHANG, Zesong FEI

    Published 2023-12-01
    “…LEO satellites have superior development prospects due to their low cost, low latency and small path loss, and are widely used in IoT, B5G and other fields.For the LEO satellite and its coverage area will be in a moving state, a convex optimization-based long-time multi-star beam hopping power allocation algorithm was proposed to maximize the system capacity.Focused on the multi-star hopping beam scenario over a period of time, a system model was developed based on the long-time co-orbital multi-star hopping beam scenario and the long-time heterodyne multi-star hopping beam scenario respectively.The resource allocation algorithm was designed for the two long-time multi-star hopping beams with the weighted objective function as the optimization objective, considered the influence factors of inter-star interference, load balancing and inter-star resource allocation priority, a long-time skipping beam resource allocation algorithm based on convex optimization was proposed.The simulation results showed that the proposed scheme could improve the resource utilization of the system compared with the conventional schemes.…”
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  10. 2490

    Distributed Multi-Energy Trading in Energy Internet: An Aggregative Game Approach by Jingwei Hu, Enhui An, Qiuye Sun, Bonan Huang

    Published 2025-01-01
    “…Since each WE only needs to communicate with its neighbors to exchange information, this distributed process reduces communication burden and improves information security. Furthermore, a multi-energy transmission optimization model is established to determine the transmission path of the transmission energy, which can minimize the transmission cost. …”
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    Article
  11. 2491

    Reoptimization Heuristic for the Capacitated Vehicle Routing Problem by Rodrigo Linfati, John Willmer Escobar

    Published 2018-01-01
    “…Next, the local search procedure is executed to improve the solution. A classic optimization is performed on all instances using the original and new customers’ information for later comparison to minimize distance. …”
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  12. 2492

    Reliability-Based Opportunistic Maintenance Modeling for Multi-Component Systems with Economic Dependence under Base Warranty by Rongcai Wang, Zhonghua Cheng, Enzhi Dong, Chiming Guo, Liqing Rong

    Published 2021-01-01
    “…A simulated annealing (SA) algorithm is proposed to determine the optimal maintenance cost of the system and the optimal OM threshold under BW. …”
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  13. 2493

    Manufacturing engineering production line scheduling management technology integrating availability constraints and heuristic rules by Gu Yun

    Published 2025-06-01
    “…In comparing the performance of heuristic algorithms with other algorithms, the optimization rates of heuristic algorithms with SHPSO, QLINSGA-II, and Q-Learning-Sarsa-K-mes-GA were 96.7, 90, 78.6, and 84.7%, respectively. …”
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  14. 2494

    SIC-Free Based Indoor Two-User NOMA-VLCP System by Jianli Jin, Qianlong Shang, Jianping Wang, Huimin Lu, Danyang Chen, Dongmei Yang

    Published 2024-11-01
    “…The particle swarm optimization (PSO) algorithm is employed to construct a joint optimization function that optimizes the power allocation factor of the two users and the roll-off coefficient of the square-root-raised-cosine(SRRC) filter. …”
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  15. 2495

    Advanced day-ahead scheduling of HVAC demand response control using novel strategy of Q-learning, model predictive control, and input convex neural networks by Rahman Heidarykiany, Cristinel Ababei

    Published 2025-05-01
    “…More specifically, new input convex long short-term memory (ICLSTM) models are employed to predict dynamic states in an MPC optimal control technique integrated within a Q-Learning reinforcement learning (RL) algorithm to further improve the learned temporal behaviors of nonlinear HVAC systems. …”
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  16. 2496

    Joint Allocation of Power and Subcarrier for Low Delay and Stable Power Line Communication by Zhixiong Chen, Zhihui Yang, Zeng Dou

    Published 2025-01-01
    “…Finally, the performance of the algorithm is compared and analyzed by simulation. The results show that the proposed algorithm can reduce the rate fluctuation and improve the system delay performance and deterministic transmission ability under the condition of ensuring the average rate optimization.…”
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  17. 2497

    Bilevel Programming Model of Urban Public Transport Network under Fairness Constraints by Jingjing Hao, Xinquan Liu, Xiaojing Shen, Nana Feng

    Published 2019-01-01
    “…The results showed that (1) the travel cost deprivation coefficient of the three groups declined from 33.42 to 26.51, with a decrease of 20.68%; the Gini coefficient of the road area declined from 0.248 to 0.030, with a decrease of 87.76%; it could be seen that the transportation equity feeling of low-income groups and objective resource allocation improved significantly; (2) before the optimization of public transport network, the sharing rate of cars, buses, and bicycles was 42%, 47%, and 11%, respectively; after the optimization, the sharing rate of each mode was 7%, 82%, and 11%, respectively. …”
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  18. 2498

    Similar Instances Reuse Based Numerical Control Process Decision Method for Prismatic Parts by Changhong XU, Shusheng ZHANG, Jiachen LIANG, Rui HUANG, Rong BIAN

    Published 2025-01-01
    “…The NC process decision efficiency is improved by 84.6%. On the other hand, the manufacturing cost of the optimal NC process scheme is 16.6% lower.Conclusions The experimental results showed that the proposed approach can generate optimal NC process schemes for parts effectively and automatically, decrease production costs, and shorten the development cycle. …”
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  19. 2499

    Influence of artificial intelligence on higher education reform and talent cultivation in the digital intelligence era by Limin Qian, Weiran Cao, Lifeng Chen

    Published 2025-02-01
    “…Abstract In order to solve the problems of inefficient allocation of teaching resources and inaccurate recommendation of learning paths in higher education, this paper proposes a smart education optimization model (SEOM) by combining the improved random forest algorithm (RFA) based on adaptive enhancement mechanism and the Graph Neural Network (GNN) algorithm. …”
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  20. 2500

    Towards load adaptive routing based on link critical degree for delay-sensitive traffic in IP networks by Yang YANG, Jia-hai YANG, Hui WANG, Chen-xi LI, Yu-ding WANG

    Published 2015-03-01
    “…Firstly, an optimization objective function has been put forward; and then decomposed into several sub-functions by using convex optimization theory; finally, the optimization objective function and sub-functions were transformed into a simple distributed protocol. …”
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