Indoor Positioning System based on SSA-ELM Neural Network for Visible Light by JIA Kejun, NIU Zhen, YU Kai, ZHANG Zhicong, PENG Duo, CAO Minghua

“…Compared with the Back Propagation (BP), SSA-BP, and ELM positioning algorithms, the positioning accuracy of the SSA-ELM algorithm is improved by 83.55%, 45.71%, and 26.26%, respectively, while the positioning time is reduced by 36.48%, 17.69%, and 6.61%, respectively. …”
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Time-Dependent Electric Vehicle Routing Problem with Time Windows and Path Flexibility by Li Wang, Shuai Gao, Kai Wang, Tong Li, Lin Li, Zhiyuan Chen

“…Hereinafter, an improved version of the variable neighborhood search (VNS) algorithm is utilized to solve the proposed models, in which multithreading technique is adopted to improve the solution efficiency significantly. …”
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Enhanced Convolutional Neural Network for Accurate Crop Recommendation System on Climate Data by Adnan Myasar M., AI_Sadi Hafidh l., Abhilash Pideka Kundil

“…The chosen features are classified and Improved Convolutional Neural Network (ICNN) algorithm predicts crops accurately. …”
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A Distributed Q Learning Spectrum Decision Scheme for Cognitive Radio Sensor Network by Jian He, Jun Peng, Fu Jiang, Gaorong Qin, Weirong Liu

“…Then, the learning strategy selection scheme is designed to solve the optimization problem by establishing a learning model. …”
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Vehicle-routing problem for low-carbon cold chain logistics based on the idea of cost–benefit by Yan Liu, Fengming Tao, Rui Zhu

“…Therefore, based on the idea of cost–benefit, a comprehensive vehicle routing problem optimization model with the objective function of minimizing the cost of unit satisfied customer is presented. …”
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Short-Term Wind Power Prediction Based on MVMD-AVOA-CNN-LSTM-AM by Xiqing Zang, Zehua Wang, Shixu Zhang, Mingsong Bai

“…For this reason, this paper proposes a combined prediction model based on the Pearson correlation coefficient method, multivariate variational mode decomposition (MVMD), African vultures optimization algorithm (AVOA) for leader–follower patterns, convolutional neural network (CNN), long short-term memory (LSTM), and attention mechanism (AM). …”
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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

“…The first and second stage models are solved using the simulation-optimization and genetic-algorithm-based approaches, respectively. …”
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A Hierarchical Reinforcement Learning Framework for Multi-Agent Cooperative Maneuver Interception in Dynamic Environments by Qinlong Huang, Yasong Luo, Zhong Liu, Jiawei Xia, Ming Chang, Jiaqi Li

“…To address the challenges of real-time decision-making and resource optimization in multi-agent cooperative interception tasks within dynamic environments, this paper proposes a hierarchical framework for reinforcement learning-based interception algorithm (HFRL-IA). …”
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Cognitive MIMO radar waveform design for multiple moving extended targets by SHEN Tingli, ZHANG Yunlei, LU Jianbin, YU Guohua

“…In order to solve the problem of boosting cognitive MIMO radar for multiple moving target detection in cluttered backgrounds, this paper constructs a multi-target optimization model based on the dual mutual information criterion, takes into account the problem of linear variation of the motion target impulse response (TIR), estimates the TIR at the next moment by using Kalman filtering algorithm. …”
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Similar Instances Reuse Based Numerical Control Process Decision Method for Prismatic Parts by Changhong XU, Shusheng ZHANG, Jiachen LIANG, Rui HUANG, Rong BIAN

“…The PSD-based ant colony algorithm is proposed and described in detail to generate several locally optimal paths. …”
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Broad learning system based on attention mechanism and tracking differentiator by LIAO Lüchao, ZOU Weidong, YANG Jialong, LU Huihuang, XIA Yuanqing, GAO Jianlei

“…To alleviate these problems, broad learning system based on attention mechanism and tracking differentiator (TD), abbreviated as A-TD-BLS, was proposed. In terms of model structure, A-TD-BLS introduced self-attention mechanism to the original BLS, and further fused and transformed the extracted features through attention weighting to improve the feature learning ability.In terms of model training methods, a weight optimization algorithm based on tracking differentiator was designed.This method effectively alleviates the overfitting phenomenon of the original BLS by limiting the size of the weight values, significantly reduces the influence of the number of hidden layer nodes on model performance and makes the generalization performance more stable.Moreover, the training algorithm was extended to the BLS incremental learning framework, so that the model can improve performance by dynamically adding hidden layer nodes.Multiple experiments conducted on some benchmark datasets show that compared to the original BLS, the classification accuracy of A-TD-BLS is increased by 1.27% on average on classification datasets and the root mean square error of A-TD-BLS is reduced by 0.53 on average on regression datasets.Besides, A-TD-BLS is less affected by the number of hidden layer nodes and has more stable generalization performance. …”
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Augmented Reality Interactive Guide System and Method for Tourist Attractions Based on Geographic Location by Xueqiu Zhuang, Huihua Jiao, Kai Lu

“…This paper proposes an improved probabilistic algorithm model to accurately locate tourists. …”
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Driving Pattern Analysis, Gear Shift Classification, and Fuel Efficiency in Light-Duty Vehicles: A Machine Learning Approach Using GPS and OBD II PID Signals by Juan José Molina-Campoverde, Juan Zurita-Jara, Paúl Molina-Campoverde

“…A multiple linear regression model was developed to estimate instantaneous fuel consumption (in L/100 km) using the gear predicted by the KNN algorithm and other relevant variables. …”
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Dynamic-budget superpixel active learning for semantic segmentation by Yuemin Wang, Ian Stavness

“…A static budget could result in over- or under-labeling images as the number of high-impact regions in each image can vary.MethodsIn this paper, we present a novel dynamic-budget superpixel querying strategy that can query the optimal numbers of high-uncertainty superpixels in an image to improve the querying efficiency of regional active learning algorithms designed for semantic segmentation.ResultsFor two distinct datasets, we show that by allowing a dynamic budget for each image, the active learning algorithm is more effective compared to static-budget querying at the same low total labeling budget. …”
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Real-time torque distribution simulation of parallel hybrid vehicle engine by Jing Wang

“…Validation employed the Gamma Technologies Suite simulation platform and the Next Generation Simulation dataset, with benchmark comparisons against Equivalent Consumption Minimization Strategy, Fuzzy Logic Control, and Thermostat Strategy models.ResultsThe optimized Proximal Policy Optimization algorithm achieved 93.2% accuracy and 1.0% loss rate upon convergence, with an average feedback time of 32 milliseconds. …”
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HUMAN-ORIENTED QUALITY MANAGEMENT SYSTEM OF ENTERPRISE: CONTROL OF NON-CONFORMING PRODUCT AND UTILIZATION by Vyacheslav Feoktistovich Bezyazychny, Maria Evgenyevna Ilyina

“…The presented model algorithm reflects all possible action variants directed on the improvement and the most effective use of non-conforming product. …”
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Research on automatic identification method for pipeline girth weld defects based on X-ray images and sparse representation by Shaohui JIA, Yaping LI, Weixin GAO, Yunchao PENG, Xinjian ZHANG, Yuxia WANG

“…To maximize the library of image features within the dictionary matrix, an optimal model was established for X-ray SDR images of welds based on orthogonal optimization, along with a dictionary matrix solving algorithm featuring orthogonal optimization. …”
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A Generalized Shape Function for Vibration Suppression Analysis of Acoustic Black Hole Beams Based on Fractional Calculus Theory by Jun Xu, Ning Chen

“…To obtain the best parameters of the shape function under various parameters, the Particle Swarm Optimization (PSO) algorithm is employed. The results demonstrate that by selecting appropriate ML parameters and viscoelastic materials, the dissipation characteristics of the structure can be significantly improved. …”
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A Robust Enhanced Ensemble Learning Method for Breast Cancer Data Diagnosis on Imbalanced Data by Zhenzhen Wang, Junde Xie, Jia Zhang

“…Specifically, a double-level over-sampling technology is developed to increase the diversity of synthesized minority breast cancer samples before model training, and an improved Random Forest is proposed to reconcile the bias and variance. …”
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Performance Analysis of CO2 Systems Integrated with Ejector and Dedicated Mechanical Subcooling by Dai Baomin, Zhao Ruirui, Liu Shengchun, Qian Jiabao, Xu Tianyahui, Liu Chen, Yang Peifang

“…A thermodynamic model of the system was devised. Then, the discharge pressure and subcooling degree were optimized using a genetic algorithm by considering the coefficient of performance (COP) as the objective function. …”
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