A Distributed Q Learning Spectrum Decision Scheme for Cognitive Radio Sensor Network by Jian He, Jun Peng, Fu Jiang, Gaorong Qin, Weirong Liu

“…Cognitive spectrum management can improve the utilization efficiency of spectrum while increasing the energy consumption of sensor network nodes. …”
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Piecewise Model and Parameter Obtainment of Governor Actuator in Turbine by Jie Zhao, Li Wang, Dichen Liu, Jun Wang

“…Several testing functions are selected to compare genetic algorithm and particle swarm optimization algorithm (GA-PSO) with other basic intelligence algorithms. …”
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Research on Energy-Saving Control Strategy of Nonlinear Thermal Management System for Electric Tractor Power Battery Under Plowing Conditions by Xiaoshuang Guo, Ruiliang Xu, Junjiang Zhang, Xianghai Yan, Mengnan Liu, Mingyue Shi

“…Finally, a nonlinear model predictive control cooling optimization strategy is proposed, with the optimization objectives of quickly achieving battery temperature regulation and reducing compressor energy consumption. …”
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Research on Discrete Dynamic System Modeling of Vocal Performance Teaching Platform Based on Big Data Environment by Xiaohui Gong

“…The results show that the optimization model based on the deep recurrent neural network algorithm has the advantages of high feasibility, high intelligence, and wide range of applications. …”
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Research on the blockchain-based trusted ownership confirmation and value transfer system and its light weight of industrial data assets by WANG Dongchu, FU Yusun, YU Ya

“…The consensus protocol algorithm of the blockchain system was optimized based on the trustworthiness of nodes, reducing the probability of malicious attacks on nodes while improving the efficiency of system transaction consensus, achieving security and lightweight parallelism of the entire system. …”
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Comparative Analysis of Bio-Inspired Enhancement Techniques for Localization in 2D Wireless Sensor Networks by Rabhi Seddik

“…The recently introduced DMOA, modeled after the hunting and movement strategies of mongooses, represents a novel approach in optimization. Simulation results indicate that while PSO and FOA perform well under specific conditions, DMOA outperforms them in terms of accuracy and precision, making it a promising solution for improving node localization in WSNs. …”
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基于萤火虫神经网络的轴承性能退化程度评估 by 刘永前, 徐强, 田德, 龙泉

“…Precise assessment of bearing performance degradation is the foundation and key of predictive maintenance for rotating machinery,and also a new research area nowadays.An optimized BP neural network based on glowworm swarm optimization algorithm is proposed and applied for the first time in the performance degradation assessment of bearings.The glowworm swarm optimization algorithm is applied to obtain the initial weights and thresholds of BP neural network,while power spectral entropy,wavelet entropy,box dimension,correlation dimension,kurtosis and skewness are selected as the fault features.Experiments show that the glowworm swarm optimization algorithm has improved the prediction accuracy of network and the proposed method can precisely assess the performance degradation of rolling bearings,the effectiveness and accuracy of the proposed method in engineering application is validated.…”
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Federated deep reinforcement learning-based edge collaborative caching strategy in space-air-ground integrated network by LIU Liang, JING Tengxiang, DUAN Jie, MAO Wuping, YAN Hongcheng, MA Wenjie

“…Simulation results show that compared with other algorithm, the proposed algorithm can improve the cache hit rate of user requests by 18% and reduce the access latency of content by 25% while protecting user privacy.…”
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Beamforming design for energy-constrained full-duplex two-way relaying system by Wei WANG, Liyuan AN, Guoan ZHANG, Shibing ZHANG

“…A beamforming design was proposed under simultaneous wireless information and power transfer (SWIPT) protocol.A utility optimization problem was considered aiming to maximize the harvested energy by jointly optimizing the beamforming matrix,the power splitting ratio at the relay and the transmit powers at the sources.Since the formulated joint optimization problem was nonconvex,it was difficult or even intractable to obtain the global optimal solution.To overcome this issue,the objective problem into three subproblems was decoupled which could be solved by the proposed semidefinite relaxation technique and the derived constraints activation solution,respectively.The solution was finally obtained with the proposed convergent iterative algorithm.Simulation results show that the proposed joint optimization scheme achieves the optimal performance.Compared with the traditional half-duplex (HD) algorithm,the proposed algorithm can obtain 2~3 times energy harvesting (EH) efficiency improvement,while the computational complexity increases slightly.…”
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A Study on the Impact of Obstacle Size on Training Models Based on DQN and DDQN by Lu Siyu, Tao Ye, Zeng Junwei, Zuo Qihuan

“…While DDQN introduces another network for evaluation, which could better decrease overestimation and explore more possible actions to improve training performance. …”
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Predicting antimicrobial mechanism-of-action from transcriptomes: A generalizable explainable artificial intelligence approach. by Josh L Espinoza, Chris L Dupont, Aubrie O'Rourke, Sinem Beyhan, Pavel Morales, Amy Spoering, Kirsten J Meyer, Agnes P Chan, Yongwook Choi, William C Nierman, Kim Lewis, Karen E Nelson

“…Here we describe an explainable artificial intelligence classification methodology that emphasizes prediction performance and human interpretability by using a Hierarchical Ensemble of Classifiers model optimized with a novel feature selection algorithm called Clairvoyance; collectively referred to as a CoHEC model. …”
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Selection Based on Colony Fitness for Differential Evolution by Zi Ming, Yang Li, Shijie Peng, Xuechao Wu, Jinyi Guo

“…Selection based on the first version of the colony is embodied in DE/rand/1, a basic DE algorithm, while selection based on the second version is used in CoBiDE, a state-of-the-art DE algorithm. …”
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Hybrid precoding and power allocation for mmWave NOMA systems based on time delay line arrays by Gangcan SUN, Xinli WU, Wanming HAO, Zhengyu ZHU

“…Methods:To reduce inter-user interference,an improved K-means algorithm is proposed to group users and select a cluster head for each group of users, which maximizes the correlation of user channels in the same cluster and reduces the correlation between users in different clusters as much as possible;Then,a low-complexity analog precoding is designed to maximize the array gain of the antenna based on the relevant user channel matrix composed of the cluster head set, followed by a digital precoding designed to eliminate inter-user interference with the maximum equivalent channel gain between beams using a forced-zero technique; Finally, an EE maximization problem is formed to optimize the transmit power under users'quality of services and total transmit power constraints,and a two-layer iterative algorithm is proposed for the resulting non-convex optimization problem. …”
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Application of the Lagrange Equation for Intelligent Sensor Vibration Control for Power Network Monitoring by Xiaojing Cheng

“…The TMD natural frequency is 14.179 rad/s and the damping ratio is 0.0432 by the DH optimization method, while the TMD natural frequency is 14.1812 rad/s, and the damping ratio is 0.0436 by the augmented Lagrangian optimization algorithm. …”
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ROITP: Road Obstacle-Involved Trajectory Planner for Autonomous Trucks by Yechen Qin, Yiwei Huang, Wenhao Yu, Hong Wang

“…The planner categorizes road obstacles using a learning-based algorithm. A discrete optimization algorithm selects a multi-objective optimal trajectory while taking into account constraints and objective functions derived from truck dynamics. …”
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A Hybrid Dynamic Path-Planning Method for Obstacle Avoidance in Unmanned Aerial Vehicle-Based Power Inspection by Zheng Huang, Chengling Jiang, Chao Shen, Bin Liu, Tao Huang, Minghui Zhang

“…Based on a breadth-first search strategy, the path obtained is optimized to reduce path complexity. To address the RRT* algorithm’s limitation in dynamic obstacle avoidance, a local path-planning method combining the improved DWA algorithm is proposed, improving efficiency in areas with dense obstacles. …”
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Continuous Train Positioning Using Visible Light Communication Assisted with Zero Velocity Update by Yanpeng ZHANG, Rongrong ZHANG, Nan MENG, Bingqing ZHANG, Xia XIAO

“…The zero velocity update (ZUPT) algorithm can correct IMU errors by detecting the vehicle’s motion state and attitude angle to improve the accuracy and stability of positioning. …”
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Bilevel Programming Model of Urban Public Transport Network under Fairness Constraints by Jingjing Hao, Xinquan Liu, Xiaojing Shen, Nana Feng

“…The model improves the fairness of the urban public transport system effectively while ensuring the travel demand of the residents. …”
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A Location Selection Policy of Live Virtual Machine Migration for Power Saving and Load Balancing by Jia Zhao, Yan Ding, Gaochao Xu, Liang Hu, Yushuang Dong, Xiaodong Fu

“…We propose a novel approach MOGA-LS, which is a heuristic and self-adaptive multiobjective optimization algorithm based on the improved genetic algorithm (GA). …”
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Coordinated Scheduling for Zero-Wait RGV/ASR Warehousing Systems with Finite Buffers by Wenbin Gu, Na Tang, Lei Wang, Zhenyang Guo, Yushang Cao, Minghai Yuan

“…Additionally, in 15 randomized test scenarios, AMHS demonstrated superior performance over three benchmark algorithms—Genetic Algorithm (GA), Discrete Imperialist Competitive Algorithm (DICA), and Improved Whale Optimization Algorithm (IWOA)—achieving an average makespan reduction of 12.6% relative to GA.…”
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