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

“…The above results indicate that the proposed model and hybrid algorithm have good performance and effectiveness, which can help improve the quality of engineering production line scheduling management.…”
Get full text

Comparison of Support Vector Machine-Based Techniques for Detection of Bearing Faults by Lijun Wang, Shengfei Ji, Nanyang Ji

“…The global optimization and high computational efficiency of SFLA are applied to the SVM model. …”
Get full text

Movie Box Office Prediction Based on IFOA-GRNN by Wei Lu, Xiaoqiao Zhang, Xinchen Zhan

“…At present, the main method of forecasting movie box office is subjective prediction, which is not widely accepted due to its accuracy and applicability. This study improves the fruit fly algorithm to optimize the generalized regression neural network (IFOA-GRNN) model to predict whether a movie can become a high-grossing movie. …”
Get full text

铰链四杆刚体导引机构综合的区间逃逸粒子群算法 by 易建, 何兵, 车林仙

“…The length of the bars is regarded as the restrict condition to obtain the unconstrained optimization model for rigid-body guidance approximate kinematc synthesis of hinged 4-bar linkages and this optimal problem is solved by means of the particle swarm optimization （PSO） algorithm. …”
Get full text

Intelligent tuning method for service scheduling in electric power communication networks based on operational risk and QoS guarantee. by Yang Yu, YueLin Jiang, Zeng Dou, Li Cong, Wei Huang, Qiang Zhang, Yang Hu, YanJun Bi

“…Based on a comprehensive assessment of service transmission reliability and time costs, a route satisfaction evaluation function model has been developed. Utilizing this model, an enhanced Risk-Time Ant Colony Optimization (RT-ACO) routing algorithm is proposed, which builds upon the traditional ant colony algorithm. …”
Get full text

Bearing Fault Prediction Based on Mixed Domain Features and GWO-SVM by Xuan Zhou, Ruiyang Xia, Zhaodong Zhang, Sasa Duan, Mao Cheng, Chengjiang Zhou, Min Mao

“…Achievements: the signal-to-noise ratio can be effectively improved to 77.8 by using the wavelet denoising, and the parameter modeling optimized by the GWO algorithm can significantly improve the prediction accuracy, with an increase of about 3%–5%. …”
Get full text

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

“…The optimal power allocation under the condition of a single slot is realized by subcarrier diversity grouping and improved genetic algorithm, and then the subcarrier power below the rate threshold is recycled and allocated to the slot with good prediction performance. …”
Get full text

Discussing the Construction of a Budget Management System Combining Multimedia Technology and Financial Risk Management by Xiaoyi Jiang

“…In the traditional support vector machine, when the test sample is located at the boundary point of the hyperplane, the judgment may be wrong. In the aspect of SVM model improvement, according to the discrimination method of SVM, the weighted K-nearest neighbor algorithm is introduced to redistinguish the qualified test samples in the feature space. …”
Get full text

Exploration of Energy-Saving Chilling Landscape Design Based on Algo for Group Intelligence by Zhuo Li

“…The experimental results show that the algo for group intelligence outperforms another algorithm in terms of solving ability to the extent that the average optimization ability is improved by 13.45%, so the algo for group intelligence demonstrates its superior ability to take into account both local and global search. …”
Get full text

Federated learning resource management for energy-constrained industrial IoT devices by Shaoshuai FAN, Jianbo WU, Hui TIAN

“…Given the impact of limited wireless resources, a dynamic multi-dimensional resource joint management algorithm was proposed, which intended to tackle the problem of device failure and training interruption caused by the limited battery energy in federated learning network in industrial Internet of things (IIoT).Firstly, the optimization problem was decoupled into battery energy allocation, equipment resource allocation and communication resource allocation sub-problems which were interdependent with the goal of maximizing the fixed-time learning accuracy.Then, the equipment transmission and computing resource allocation problem were solved based on particle swarm optimization algorithm under the given energy budget.Thereafter, the resource block iterative matching algorithm was proposed to optimize the optimal communication resource allocation strategy.Finally, the online energy allocation algorithm was proposed to adjust the energy budget allocation.Simulation results validate the proposed algorithm can improve the model learning accuracy compared with other benchmarks, and can perform better in energy shortage scenarios.…”
Get full text

Research on Short-Term Load Forecasting of LSTM Regional Power Grid Based on Multi-Source Parameter Coupling by Bo Li, Yaohua Liao, Siyang Liu, Chao Liu, Zhensheng Wu

“…In order to further optimize the performance of the LSTM model, the IPSO algorithm, and linear difference decreasing inertia weight are introduced to improve the global optimization ability and convergence speed of the PSO algorithm and reduce the risk of local optimal solutions. …”
Get full text

Adaptive Neural Network Iterative Sliding Mode Course Tracking Control for Unmanned Surface Vessels by Chunbo Zhao, Huaran Yan, Deyi Gao, Renqiang Wang, Qinrong Li

“…Therefore, the fusion of multiple algorithms can be applied to improve the performance of the control system.…”
Get full text

Robust Allocation of FACTS Devices in Coordinated Transmission and Generation Expansion Planning considering Renewable Resources and Demand Response Programs by Sara Mahmoudi Rashid, Ehsan Akbari, Farshad Khalafian, Mohmmad Hossein Atazadegan, Saeid Shahmoradi, Abbas Zare Ghaleh Seyyedi

“…Furthermore, the conventional Pareto optimization is adopted using fuzzy weighted sum method (FWSM) to achieve a single-objective model. …”
Get full text

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

“…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.…”
Get full text

Active micro-vibration isolation system for adaptive vibration suppression tests using piezoelectric stack actuator by Zhiyuan Gao, Lei Zhang, Tongxin Xu, Xiaojin Zhu

“…System identification is conducted using an improved particle swarm optimization method, specifically the Hybrid PSO-Jaya algorithm, which sequentially integrates the PSO algorithm with the Jaya algorithm. …”
Get full text

Group Stable Matching Problem in Freight Pooling Service of Vehicle–Cargo Matching Platform by Linlin Kong, Min Huang

“…Based on the characteristics of the problem, the algorithm is improved by removing ineffective constraints and only using key constraints, significantly reducing computational complexity, optimizing the solving process, and greatly improving the model’s solution efficiency. …”
Get full text

Trajectory Tracking Control of a Six-Degree-of-Freedom Manipulator Based on EAVOA-LADRC by Xinxin Shi, Haihao Yu

“…Through experimental comparison, the improved algorithm has faster convergence speed and better optimal solution, and has smaller joint angle error in the trajectory tracking control of six-degree-of-freedom manipulator based on LADRC.…”
Get full text

Flexible Job Shop Scheduling Based on Energy Consumption of Method Research by Yajie Li, Longlong Li, Xiaoying Yang, Bingfeng Zhao

“…By establishing a multi-objective optimization model aimed at minimizing the maximum completion time and energy consumption, this paper solves the flexible job-shop scheduling problem considering energy consumption (GFJSP) based on an improved deep reinforcement learning algorithm, D3QN. …”
Get full text

Network access and spectrum allocation in next-generation multi-heterogeneous networks by Xiaoqing Dong, Lianglun Cheng, Gengzhong Zheng, Tao Wang

“…By preprocessing of objective function, constraint simplification, and standardization, the complex spectrum allocation problem is transformed into a standard form of the 01 programming problem, and the solution is obtained by an improved Hungarian algorithm. Second, an intelligent optimization algorithm named improved non-dominated sorting genetic algorithm II is proposed, which combines the interference constraints of the primary network and the service quality requirements of the secondary users into the objective value evaluation of non-dominated sorting, and corrects the chromosomes that do not meet the constraints. …”
Get full text

Research on management mode of talent team in E-government based on big data analysis by Shixuan Hao

“…The performance analysis of the Apriori algorithm before and after improvement shows that the optimized Apriori algorithm can significantly reduce the number of scans of the data transaction database and the system running time, and the algorithm efficiency has increased by 48.26 %. …”
Get full text