OPTIMIZED SVM BASED ON IMPROVED FOA AND ITS APPLICATION IN FAULT DAIGNOSIS by SUN YaoQin

“…Aiming at the fact that the classification performance of support vector machine（ SVM） highly depends on the parameters selection,a parameters optimize method of SVM based on improved fruit fly optimization algorithm（ LFOA） was proposed. …”
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FPCB STIFFENER ADHESIVE MACHINE DYNAMIC PERFORMANCE OPTIMIZATION AND ACCURACY ANALYSIS by MEI LingLiang, LIN XiaoXia, MEI XueSong

“…Aiming at the problem of the FPCB（ flexible printed circuit board） stiffener adhesive machine performance optimization,applying the finite element method,a FEA model of the FPCB stiffener adhesive machine has been set up. …”
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Trajectory Optimization of Eight-link Mechanism for Legs of Walking Bio-robot by Zhang Chenxi, Wu Shengquan, He Yong, Fu Chunping

“…Aiming at an eight-link mechanism of bio-robot legs,the mathematical model of optimal design is established by studying the motion trajectory of the mechanism,which is in order to improve the walking speed,stability and ability to overcome obstacles of robot. …”
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Power optimization of superimposed pilot for downlink short-packet transmission in IIoT by XIA Wenchao, XU Jing, ZHOU Xingguang, WU Weihua, ZHAO Haitao

“…Furthermore, the downlink weighted sumrate maximization problem was formulated and transformed into a geometric programming problem aiming to optimize pilot and data power allocation via successive convex approximation method. …”
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Research of Real Time Optimization of Gear for DCT Vehicle Under the Ramp by Ding Hua, Xu Cong

“…Aiming at the problem of frequent shift phenomenon of the vehicle running in the uphill condition,and the unexpected upshift phenomenon of the vehicle running in the downhill condition. …”
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Optimization Design and Analysis of Sprocket Chain Plate Stage Driving Device by Houjin Zhou, Xue Wang, Yabin Wang, Yi Chen

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Fault Feature Extraction Method of Gearbox based on Parameter Optimization VMD by Ding Chengjun, Fu Xiaoyang, Feng Yubo, Zhang Liang

“…Firstly，the drosophila optimization algorithm is used to search for the most optimal combination of the variational mode decomposition's <italic>K</italic> and <italic>α</italic>，aiming at the minimum local entropy of the decomposition result. …”
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Resource optimization algorithm of combination of NFV and SDN for application of multiple services by Xiaorong ZHU, Qian ZHANG

“…Various services of internet of things (IoT) require flexible network deployment to guarantee different quality of service (QoS).Aiming at the problem of IoT service function chain deployment,network function virtualization (NFV) and software defined networking (SDN) were combined to optimize resources.Considering forwarding cost and traffic load balance,a joint optimization model of virtual network function placement and service function chain routing was given and was proved to be NP-Hard.In order to solve this model,two heuristic algorithms were proposed.One was the service chain deployment algorithm of first routing then placing (FRTP) and the other was the placing followed by routing (PFBR) based on node priority.Simulation results demonstrate that FRTP and PFBR algorithm can significantly balance network traffic load while alleviating congestion and improving the acceptance ratio of the chain requests compared with other algorithms.…”
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Program state optimal method based on variable symbolic relation analysis by Xi GUO, Pan WANG

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Theoretical analysis and optimal design of permanent magnet assisted magnetic gears by SHANGGUAN Xuanfeng, LI Shihao, ZHANG Longqi, ZHAO Lei

“…ObjectiveAiming at the problems of low structural strength of surface-mounted magnetic gears and large torque pulsation of convex pole magnetic gears, a permanent magnet assisted magnetic gear was proposed.MethodsFirstly, the basic structure and working principle of the magnetic gear were introduced. …”
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RESEARCH ON ROLLING BEARING FAULT DIAGNOSIS BASED ON MA OPTIMIZATION OF CNN by TIAN LiYong, ZHAO JianJun, YU Ning

“…Aiming at the high dependence of super parameter selection on artificial experience in rolling bearing state identification based on convolution neural network(CNN),a fault diagnosis model(CNN⁃MA)based on mayfly algorithm(MA)was proposed.Firstly,the model used the powerful optimization ability of MA,took the diagnostic accuracy of CNN as the optimization objective,and adaptively adjusted the super parameters in CNN.Secondly,the normalized original signal image set was used to preserve the characteristics of the signal as much as possible.Finally,in order to evaluate the effectiveness of the parameters in the optimization model,compared with the CNN model optimized by particle swarm optimization(PSO)algorithm.The results show that the proposed model has more stable performance,higher recognition accuracy and good anti⁃noise ability.It fully shows the feasibility and reliability of CNN⁃MA model in fault diagnosis of rolling bearings.…”
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Pattern-Based Approach to Topology and Geometry Optimization of Steel Building Structures by Artur Lax, Sławomir Milewski

“…Building on these insights, the research seeks to advance and refine the concept of patterns, aiming to further enhance their applicability and efficiency in structural optimization. …”
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Topology Optimization Design of Transmission Case Housing Used in Electric Vehicle by Zhang Qing, Li Hongbiao, Zhou Qia, Yan Huidong, Guo Wentian, Yang Xianxue

“…Aiming at the structure of transmission case housing used in electric vehicle,the topology optimization analysis of transmission case housing used in electric vehicle,including the external and internal reinforcing plates and outside profile is conducted by using the method of topology optimization analysis from the forward design. …”
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An algorithm for joint optimization of dynamic routing and scheduling in time-sensitive networking by Yang ZHOU, Honglong CHEN, Lei ZHANG

“…Time-sensitive networking (TSN) is a set of protocols developed by the IEEE TSN task group, aiming at achieving deterministic communications over Ethernet.As the implementation method of TSN traffic scheduling is not specified in the protocols, the routing and scheduling algorithm for TSN remains an open issue.The joint optimization problem of routing and scheduling in TSN for industrial applications was modeled, and then an online heuristic algorithm was proposed to deliver the routing and scheduling solution for dynamic traffics.The routing path was determined by optimizing both the transmission delay and network load factors, and the scheduling time was quickly conducted by twice clipping operations.Finally, a simulated TSN testbed was developed with NeSTiNg framework based on OMNeT.The simulation results show that the execution time of the proposed algorithm outperforms the baseline algorithms even with large scale of network size and network traffics.It shows that the proposed algorithm guarantees the real-time performance even in dynamically changing networks.…”
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A computation offloading scheme for energy consumption optimization in Internet of vehicles by Wenxuan GAO, Xinjie YANG

“…In Internet of vehicles (IoV), vehicle-oriented applications are generally computation-intensive and latency-sensitive.Introducing idle computing resources from mobile vehicles as a supplement to network computing power can effectively alleviate the load pressure on edge servers.The problem of task allocation for edge computation offloading in the context of IoV environment were researched.By fully leveraging the combined computing resources of roadside units (RSU), user vehicles, and mobile vehicles within the RSU service range, a computation offloading strategy based on the sparrow search algorithm was proposed and referred to as sparrow search based computation offloading scheme (S²COS), aiming to optimize the overall system energy consumption.In addition, this strategy fully taked into account practical network issues such as service time constraints caused by vehicle mobility and the potential occurrence of computation node failures.The simulation results demonstrate that S²COS can meet the latency requirements for computation-intensive and latency-sensitive tasks, while significantly reducing system energy consumption.…”
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Optimal Control Analysis in the Treatment of Solid Tumors using Combined Therapy by Salaheldin Omer, Hermane Mambili-Mamboundou

“…Additionally, we formulated and solved an optimal control problem using the Pontryagin’s maximum principle, aiming to minimize tumor size and the concentration of transforming growth factor-beta while also reducing chemotherapy and siRNA drug-induced toxicity in patients. …”
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Multi-agent cooperative confrontation with proximal policy optimization in urban environments by MI Guangming, ZHANG Hui, ZHANG Jing, ZHUO Li

“…To address the issue that urban environments often make command systems inefficient and inflexible due to their geospatial complexity and dynamic changes, a multi-agent cooperative confrontation method with proximal policy optimization for urban environments was proposed. First, on the basis of establishing a comprehensive urban confrontation environment, the AC (actor-critic) network with proximal policy optimization was used to solve the problem. …”
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Bi-Objective Optimization of Product Selection and Ranking Considering Sequential Search by Yuyang Tan, Hao Gong, Chunxiang Guo

“…To address this gap, we study a bi-objective product selection and ranking (BP-SS) problem considering sequential search, aiming to jointly optimize the expected revenue and market share. …”
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Structure Analysis and Optimization of Welding Fume , Water Bath Cleaning Device by ZHAO Xin-tong, MA Ming-xiao

“…The handling tilting condition and moving road impact are analyzed by using ADAMS and ANSYS The static analysis shows that the material properties of selected profiles are not fully utilized, the transient dynamic analysis showed that in the purifying machine by the road surface impact load truckle bracket and the maximum stress, the overall structure of the least affected by So, according to the results of the analysis in the optimization of the structure of static analysis, the optimization results show that the selected 2020 profiles can meet the requirements of structural strength, and the optimized structure modal analysis, provide the basis for the selection of fan get resonance frequency of each order…”
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Intelligent anti-jamming decision algorithm based on proximal policy optimization by MA Song, LI Li, LI Wei, HUANG Wei, WANG Jun

“…The existing intelligent anti-jamming methods based on deep reinforcement learning are applied to space-ground TT&amp;C and communication links, in which the deep neural network used for decision-making has a complex structure, and the resources of satellites and other vehicles are limited, making it difficult to independently complete the timely training of complex neural network under the constraints of limited complexity, and the decision-making of anti-jamming cannot converge. Aiming at the above problems, an intelligent anti-jamming decision algorithm based on proximal policy optimization was proposed, which deployed the decision-making neural network and the training neural network in the vehicles and the ground station, respectively. …”
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