Onboard Decision-making System of Unmanned Mine Truck by WANG Jia, HUANG Jiade, LIU Zhicong, HUANG Peng, LYU Liang

“…This paper adopts the quadratic programming algorithm based on the shortest time and the optimal energy consumption to solve the speed planning, and adopts the hybrid A-star and curve fitting algorithm based on special scenarios to solve the local path planning, so that the operation efficiency can be improved by 10%~20% in the loading and unloading parking scenario. …”
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Research on subway settlement prediction based on the WTD-PSR combination and GSM-SVR model by Miren Rong, Chao Feng, Yinping Pang, Hailong Wang, Ying Yuan, Wensong Zhang, Lanxin Luo

“…Furthermore, Particle Swarm Optimization (PSO), Gray Wolf Optimization (GWO), Marine Predators Algorithm (MPA), and Whale Optimization Algorithm (WOA) are introduced to optimize the SVR model, and the prediction performance is compared with that of the Long Short-Term Memory (LSTM) model. …”
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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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Trail-Using Ant Behavior Based Energy-Efficient Routing Protocol in Wireless Sensor Networks by Soon-gyo Jung, Byungseok Kang, Sanggil Yeoum, Hyunseung Choo

“…Swarm Intelligence (SI) observes the collective behavior of social insects and other animal societies. Ant Colony Optimization (ACO) algorithm is one of the popular algorithms in SI. …”
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Next generation network resource allocation method based on cooperative game and decision-making in advance by RAO Xiang, ZHANG Shun-yi, SUN Yan-fei, DING Wen-tao

“…It’s an important way to guarantee QoS for the next generation network（NGN） with diverse services by allo-cating resources reasonably and optimizing the efficiency of whole network according to diverse service styles.A net-work resource allocating method based on co-operative game theory for NGN was proposed and analyzed,and it had a weakness which brought about overgreat system costing.In order to overcome this weakness,an idea about deci-sion-making in advance was added,and an improved resource allocation algorithm was proposed,which could guarantee the efficiency of whole network best and reduce the system costing.Simulation results of this method show its validity.…”
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A Hybrid CT-DEWCA-Based Energy-Efficient Routing Protocol for Data and Storage Nodes in Underwater Acoustic Sensor Networks by Imran Khan, Muhammad Rauf, Atif Jamil

“…This research proposes an energy-aware deployment approach and introduces the Controlled Transmission enhanced by hybrid model scheme with Differential Evolution, Whale Optimization, and Chaotic Adaptation (CT-DEWCA) for relay selection. …”
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Energy Management Strategy Based on the Driving Cycle Model for Plugin Hybrid Electric Vehicles by Xiaoling Fu, Huixuan Wang, Naxin Cui, Chenghui Zhang

“…The state of charge (SOC) profile can be obtained by the DP algorithm for the whole driving cycle. In order to optimize the energy management strategy in the hybrid power system, the optimal motor torque control sequence can be calculated using the DP algorithm for the segments between the traffic intersections. …”
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Query scheduling based on cloud-edge multi-data warehouse architecture and cost prediction model by GAO Xuning, YANG Song, LI Mingzhe, ZHANG Yanfeng

“…The scheduling framework and optimization algorithm achieve significant performance improvement on SSB and TPC-DS datasets. …”
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Query scheduling based on cloud-edge multi-data warehouse architecture and cost prediction model by GAO Xuning, YANG Song, LI Mingzhe, ZHANG Yanfeng

“…The scheduling framework and optimization algorithm achieve significant performance improvement on SSB and TPC-DS datasets. …”
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Next generation network resource allocation method based on cooperative game and decision-making in advance by RAO Xiang, ZHANG Shun-yi, SUN Yan-fei, DING Wen-tao

“…It’s an important way to guarantee QoS for the next generation network（NGN） with diverse services by allo-cating resources reasonably and optimizing the efficiency of whole network according to diverse service styles.A net-work resource allocating method based on co-operative game theory for NGN was proposed and analyzed,and it had a weakness which brought about overgreat system costing.In order to overcome this weakness,an idea about deci-sion-making in advance was added,and an improved resource allocation algorithm was proposed,which could guarantee the efficiency of whole network best and reduce the system costing.Simulation results of this method show its validity.…”
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Digital twin empowered lightweight and efficient blockchain for dynamic internet of vehicles by Haoye Chai, Supeng Leng, Jianhua He, Ke Zhang

“…The decentralized LPMA-DDPG algorithm is helpful for implementing the optimal DT construction strategy in practical ITS.…”
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Fast Nonparametric Inference of Network Backbones for Weighted Graph Sparsification by Alec Kirkley

“…We then construct an efficient and provably optimal greedy algorithm to identify the backbone minimizing our objectives, whose run-time complexity is log-linear in the number of edges. …”
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参数方程曲线的最优逼近算法及实现 by 丁克会, 席平原, 周红斌

“…The features of single and double arc approximating,and combines the merits of two kinds of fitting are discussed. By the algorithm of approximating curve in optimizing three-point arc and mixing single and double arc in permission tolerance,smooth link of whole approximating arc with inflexion points and extreme value points is attained. …”
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Trajectory Planning for Point-to-Point Motion Using High-order Polynomials by Hossein Barghi Jond, Vasif V. Nabiyev, TuÄrul Ãavdar

“…The problem aims to find suitable polynomial trajectories that connect an initial to a final configuration while satisfying other specified constraints. The constraints are considered as zero velocity at the endpoint as well as a limitation on acceleration for the whole motion time. …”
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Policy Efforts to Promote the Adoption of Autonomous Vehicles: Subsidy and AV Lanes by Chao Liu, Hongfei Jia, Yu Lin, Guanfeng Wang, Jingjing Tian, Ruiyi Wu, Heyao Gao

“…Due to the mutual influence of the two models, an iterative optimization approach is applied to solve the whole model. …”
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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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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

“…We evaluated our methods using whole transcriptome responses from Escherichia coli challenged with 41 known antibiotics and 9 crude extracts while depositing 122 transcriptomes unique to this study. …”
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Real-time urban regional route planning model for connected vehicles based on V2X communication by Pangwei Wang, Hui Deng, Juan Zhang, Mingfang Zhang

“…Second, according to the topology structure of the current regional road network, all predicted routes are listed based on the Dijkstra algorithm. Third, the predicted travel time of each alternative route is calculated, while the predicted route with the least travel time is selected as the optimal route. …”
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Interpretable prediction model for hand-foot-and-mouth disease incidence based on improved LSTM and XGBoost by Xiao LI, Shuyu HE, Yan PENG, Rongxin YANG, Lu TAO, Tingqi LOU, Wenqi HE

“…To further enhance the LSTM performance, the GWO is employed to adaptively optimize the key parameters of the LSTM. Thirdly, to fully leverage the advantages of XGBoost in handling nonlinear relationships and high-dimensional data while overcoming its complexities in parameter tuning and slower convergence, the GA is used to optimize the parameters of XGBoost. …”
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Research on deep reinforcement learning based intelligent shop scheduling method by Zihui LUO, Chengling JIANG, Liang LIU, Xiaolong ZHENG, Huadong MA

“…The unprecedented prosperity of the industrial internet of things (IIoT) has opened up a new path for the traditional industrial manufacturing model.Intelligent shop scheduling is one of the key technologies to achieve the overall control and flexible production of the whole production process.It requires an effective plan with a minimum makespan to allocate multiple processes and multiple machines for production scheduling.Firstly, the shop scheduling problem was defined as a Markov decision process (MDP), and a shop scheduling model based on the pointer network was established.Secondly, the job scheduling process was regarded as a mapping from one sequence to another, and a new shop scheduling algorithm based on deep reinforcement learning (DRL) was proposed.By analyzing the convergence of the model under different parameter settings, the optimal parameters were determined.Experimental results on different scales of public data sets and actual production data sets show that the proposed DRL algorithm can obtain better performances.…”
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