Research on the Construction of Crossborder e-Commerce Logistics Service System Based on Machine Learning Algorithms by Jinbo Xu, Shibiao Mu

“…Second, we design a simple calculation example, use Python programming through a simulated shopping environment, give the solution process of the optimal recommendation strategy in the whole process, and prove the feasibility of the algorithm. …”
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Design of an Optimal SMC Controller for a Twin Rotor Aerodynamic System by Marwa Rasheed Ali, Omer Waleed Abdulwahhab

“…Two optimization algorithms, namely Grey Wolf Optimization (GWO) and Whale Optimization Algorithm (WOA), are used to tune the SMC’s parameters. …”
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Resource allocation strategy based on optimal matching auction in the enterprise network by Xin CONG, Lingling ZI, Xueli SHEN

“…To address the issue that the owners of computer are selfish in the enterprise networks,which caused the low available number of resource nodes and low efficiency of resource allocation,an optimized matching resource allocation strategy OMRA was proposed and its core was the auction mechanism.Selfishness was restrained and the number of available resources was increased by OMRA,so as the operating efficiency of the whole auction market was improved.First,the initial prices were determined by normalizing the costs of different type of resources on the beginning of auction.Secondly,an optimal matching auction algorithm was designed to maximize the interests of the auction markets.Then,service perfecting algorithm was performed such that the sellers could get more services at the current transaction value,thus ensuring the benefits of resource providers.At last,a request price updating algorithm was adopted to assurance that both sellers and buyers could get priorities in the next auction processing.Compared with the cloud resource allocating algorithm via fitness-enabled auction (CRAA/FA),the experiment results indicate that the efficiency of resource allocation improves by 10% and the benefits of market increase by 11.4%.…”
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Modeling and Evolutionary Optimization on Multilevel Production Scheduling: A Case Study by Ruifeng Shi, Chunxia Shangguan, Hong Zhou

“…An integrated model, which can cope with the whole multilevel scheduling information simultaneously, is proposed in this paper, and a specific evolutionary algorithm is designed to solve the integrated model with a twin-screw coding strategy. …”
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Optimal Modeling of Wireless LANs: A Decision-Making Multiobjective Approach by Tomás de Jesús Mateo Sanguino, Jhon Carlos Mendoza Betancourt

“…To reduce this gap, this paper describes an optimization algorithm—based on evolutionary strategy—created as an aid for decision-making prior to the real deployment of wireless LANs. …”
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The method for solving the multi-criteria linear-fractional optimization problem in integers by Alexadra Tkacenko

“… In the papers we propose a method for solving the linear-fractional multi-criteria optimization model with identical denominators in whole numbers. …”
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Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History by Danping Wang, Kunyuan Hu, Lianbo Ma, Maowei He, Hanning Chen

“…A hybrid coevolution particle swarm optimization algorithm with dynamic multispecies strategy based on K-means clustering and nonrevisit strategy based on Binary Space Partitioning fitness tree (called MCPSO-PSH) is proposed. …”
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Optimization Research of the Hinge Position and Output Speed of Electromechanical Erection Device by Wei Cai, Shangjun Ma, Jianxin Zhang, Yong Zhou, Xiang Chen, Geng Liu

“…It can improve work efficiency， make space layout of the whole device optimal and make the installation space the best compact.…”
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Optimization mechanism of attack and defense strategy in honeypot game with evidence for deception by Lihua SONG, Yangyang JIANG, Changyou XING, Guomin ZHANG

“…Using game theory to optimize honeypot behavior is an important method in improving defender’s trapping ability.Existing work tends to use over simplified action spaces and consider isolated game stages.A game model named HoneyED with expanded action spaces and covering comprehensively the whole interaction process between a honeypot and its adversary was proposed.The model was focused on the change in the attacker’s beliefs about its opponent’s real identity.A pure-strategy-equilibrium involving belief was established for the model by theoretical analysis.Then, based on the idea of deep counterfactual regret minimization (Deep-CFR), an optimization algorithm was designed to find an approximate hybrid-strategy-equilibrium.Agents for both sides following hybrid strategies from the approximate equilibrium were obtained.Theoretical and experimental results show that the attacker should quit the game when its belief reaches a certain threshold for maximizing its payoff.But the defender’s strategy is able to maximize the honeypot’s profit by reducing the attacker’s belief to extend its stay as long as possible and by selecting the most suitable response to attackers with different deception recognition abilities.…”
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Assessment of Urban Water Supply System Based on Query Optimization Strategy by Shibao Lu, Yizi Shang, Wei Li, Zhimin Wang

“…This paper has the goal of improving water treatment efficiency and reducing water treatment cost based on comparative studies by applying two types of distributed database query optimization methods, including the system for a distributed database (SDD-1) and all reduction algorithms. …”
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Flood-prone area mapping using a synergistic approach with swarm intelligence and gradient boosting algorithms by Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Sani I. Abba, Jamil Hussain, Soo-Mi Choi

“…This research introduces a novel approach to increase the accuracy of FSM by optimizing the CatBoost algorithm with two swarm-based metaheuristic algorithms: the Zebra optimization algorithm (ZOA) and the Whale optimization algorithm (WOA). …”
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Memory-Saving Implementation of High-Speed Privacy Amplification Algorithm for Continuous-Variable Quantum Key Distribution by Dengwen Li, Peng Huang, Yingming Zhou, Yuan Li, Guihua Zeng

“…Here, we propose a novel privacy amplification scheme with an optimal hash function. In particular, by utilizing the linear feedback shift register (LFSR) technique, we optimize and simplify the construction of the Toeplitz matrix. …”
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Application of Machine Learning for Bulbous Bow Optimization Design and Ship Resistance Prediction by Yujie Shen, Shuxia Ye, Yongwei Zhang, Liang Qi, Qian Jiang, Liwen Cai, Bo Jiang

“…Then, a convergence factor is introduced to balance the global and local search abilities of the whale algorithm to improve the convergence speed. …”
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Real-Time Resource Allocation Algorithm for the Quasi-Two-Dimensional Mobile Delay/Disrupt Tolerant Networking by Ying Wang, Yonghui Zhang

“…Resource allocation is one of the core techniques in multi-homing delay/disrupt tolerant networking（DTN）, which decides the efficiency of DTN routing, and even affects the whole system. However, schemes based on neural network and genetic algorithms are of computational complexity that is not applied to real-time applications. …”
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Real-Time Resource Allocation Algorithm for the Quasi-Two-Dimensional Mobile Delay/Disrupt Tolerant Networking by Ying Wang, Yonghui Zhang

“…Resource allocation is one of the core techniques in multi-homing delay/disrupt tolerant networking（DTN）, which decides the efficiency of DTN routing, and even affects the whole system. However, schemes based on neural network and genetic algorithms are of computational complexity that is not applied to real-time applications. …”
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An Effective QoS-Aware Hybrid Optimization Approach for Workflow Scheduling in Cloud Computing by Min Cui, Yipeng Wang

“…Furthermore, an improved Whale Optimization Algorithm (WOA) based on Lévy flight is proposed. …”
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Research on Nonlinear Error Compensation and Intelligent Optimization Method for UAV Target Positioning by Yinglei Li, Qingping Hu, Shiyan Sun, Wenjian Ying, Xiaojia Yan

“…Simulation experiments show that the positioning error distance of the KYCOA is reduced by 66.75%, 41.89%, and 62.06% when compared with that of the original Coati Optimization Algorithm (COA), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA), respectively. …”
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5G-Practical Byzantine Fault Tolerance: An Improved PBFT Consensus Algorithm for the 5G Network by Xin Liu, Xing Fan, Baoning Niu, Xianrong Zheng

“…The consensus algorithm is the core technology of blockchain systems to maintain data consistency, and its performance directly affects the efficiency and security of the whole system. …”
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COD Optimization Prediction Model Based on CAWOA-ELM in Water Ecological Environment by Lili Jiang, Liu Yang, Yang Huang, Yi Wu, Huixian Li, XiYan Shen, Meng Bi, Lin Hong, Yiting Yang, Zuping Ding, Wenjie Chen

“…In order to detect high error rate and poor convergence of the water ecological chemical oxygen demand (COD) prediction model, combining the limit learning machine (ELM) model and whale optimization algorithm, CAWOA is improved by the sin chaos search strategy, while the ELM optimizes the parameters of the algorithm to improve convergence speed, thus improving the generalization performance of the ELM. …”
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Trajectory and communication scheduling optimization for the rechargeable UAV aided data collection system by Qianwen LI, Jianfeng CHEN, Miao CUI, Guangchi ZHANG

“…A rechargeable unmanned aerial vehicle (UAV) aided wireless sensor network was considered, which consists of multiple ground terminals with a large amount of time-sensitive data to be collected.Due to the limited battery capacity, the UAV cannot collect the data from all terminals through a single flight mission, and it needs to return to the charging pile to replenish its flight energy several times during the whole mission.The optimization of the terminal scheduling, trajectory, flight speed and transmission rate for the UAV was studied to maximize the number of terminals whose data had been collected within the data lifetime limit.Due to the variable coupling and the existence of discrete binary scheduling variables, the considered optimization problem is difficult to solve.To tackle such a difficulty, an efficient algorithm was proposed based on the stochastic optimization and the feature engineering.Specifically, the flight hover communication protocol was introduced to simplify the UAV flight process.And then a terminal scheduling algorithm was innovatively proposed with the influence factor and the stochastic preference, which extracted the features that affect the service time of the UAV, optimized the weights of the features, and further simplified the optimization problem into multiple subproblems.The subproblems were then solved by using the block coordinate descent and successive convex approximation techniques.Simulation results show that the proposed optimization algorithm achieves significant performance gains over several benchmark schemes in the scenarios with different data lifetime requirements and different numbers of ground terminals.…”
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