Fractional hitting sets for efficient multiset sketching by Timothé Rouzé, Igor Martayan, Camille Marchet, Antoine Limasset

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Anchorage accurately assembles anchor-flanked synthetic long reads by Xiaofei Carl Zang, Xiang Li, Kyle Metcalfe, Tuval Ben-Yehezkel, Ryan Kelley, Mingfu Shao

“…The optimality is defined as maximizing the weight of the smallest node while matching the estimated sequence length. …”
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Efficient persistence landscape generation by Taylor Henderson, Robert Simon

“…This article presents a novel output-sensitive plane sweep algorithm for computing the top- k persistence landscapes in optimal time and space: significantly outperforming previous algorithms. …”
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Prediction model of middle school student performance based on MBSO and MDBO-BP-Adaboost method by Rencheng Fang, Tao Zhou, Baohua Yu, Zhigang Li, Long Ma, Tao Luo, Yongcai Zhang, Xinqi Liu

“…Firstly, the model incorporates the good point set initialization, triangle wandering strategy and adaptive t-distribution strategy to obtain the Modified Dung Beetle Optimization Algorithm (MDBO), secondly, it uses MDBO to optimize the weights and thresholds of the BP neural network, and lastly, the optimized BP neural network is used as a weak learner for Adaboost. …”
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Energy Efficiency Maximization for Device-to-Device Communication Underlaying Cellular Networks on Multiple Bands by Yuan Zhang, Yang Yang, Linglong Dai

“…However, most of existing works only optimize the EE in the single-cell scenario, while little attention is paid to maximizing the EE of the whole cellular network underlaid with D2D communication with randomly distributed users on multiple bands. …”
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An Improved Crop Disease Identification Method Based on Lightweight Convolutional Neural Network by Tingzhong Wang, Honghao Xu, Yudong Hai, Yutian Cui, Ziyuan Chen

“…In order to improve the training learning rate, Adam optimizer combining momentum algorithm and RMSprop algorithm is used to dynamically adjust the learning rate; the combination of the two algorithms makes the loss function converge to the lowest point faster. …”
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An Improved Differential Evolution Method Based on the Dynamic Search Strategy to Solve Dynamic Economic Dispatch Problem with Valve-Point Effects by Guangyu Chen, Xiaoqun Ding

“…DE is the main optimizer in the method proposed. While chaotic sequences are applied to obtain the dynamic parameter settings in DE, dynamic search strategy which consists of two steps, global search strategy and local search strategy, is used to improve algorithm efficiency. …”
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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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Data-driven framework for prediction of mechanical properties of waste glass aggregates concrete by Kennedy C. Onyelowe, Shadi Hanandeh, Viroon Kamchoom, Ahmed M. Ebid, Hamza Imran, Miguel Angel Duque Vaca, Greys Carolina Herrera Morales, Nestor Ulloa, Krishna Prakash Arunachalam

“…Abstract This research presents a novel data-driven framework for predicting the mechanical properties of waste glass aggregate concrete using six advanced metaheuristic optimization algorithms: Bat Algorithm (Bat), Cuckoo Search Algorithm (Cuckoo), Elephant Herding Optimization (Elephant), Firefly Algorithm (Firefly), Rhinoceros Optimization Algorithm (Rhino), and Gray Wolf Optimizer (Wolf). …”
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Secure resource allocation in hybrid energy-harvesting relay and full-duplex receiver by Wei WANG, Xinrui LI, Liuguo YIN, Guoan ZHANG, Shibing ZHANG

“…Taking into account the wireless physical layer security in energy-constrained relaying systems,a secure resource allocation scheme was proposed under simultaneous wireless information and power transfer (SWIPT) protocol.The utility optimization problem was considered aiming to maximize the secrecy rate by jointly optimizing the power splitting (PS) ratio and the transmit powers under the constraint of the transmit powers of the nodes and the harvested energy of the relay.The objective problem,which is non-convex,was decoupled into two subproblems.One was to optimize the PS ratio,another was to optimize the transmit powers.The optimal solution of the subproblems can be obtained in the closed-form.Then,the suboptimal solution is obtained with the proposed convergent iterative algorithm.Simulation results show the effects of artificial noise signal,residual self-interference signal,transmit power of nodes,amplification factor of relay and other factors on the security performance.Compared with the traditional gradient descent algorithm,the proposed algorithm can reduce more than 80% of the computational load,while the algorithm has the slightly better performance.…”
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Pengembangan Deep Learning untuk Sistem Deteksi Dini Komplikasi Kaki Diabetik Menggunakan Citra Termogram by Medycha Emhandyksa, Indah Soesanti, Rina Susilowati

“…In this study, four deep convolutional neural network models were designed with Occam's razor principle through hyperparameter settings on the algorithm structure aspect in the form of number of layers and optimization aspect in the form of optimizer type. …”
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A smarter approach to liquefaction risk: harnessing dynamic cone penetration test data and machine learning for safer infrastructure by Shubhendu Vikram Singh, Sufyan Ghani

“…ML models, including Support Vector Machine (SVM) optimized with Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Genetic Algorithm (GA), and Firefly Algorithm (FA), were employed to predict the e/qd ratio using key geotechnical parameters, such as fine content, peak ground acceleration, reduction factor, and penetration rate. …”
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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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Clustering-based energy-aware virtual network embedding by Xu Liu, Zhongbao Zhang, Junning Li, Sen Su

“…Extensive simulations demonstrate that this algorithm significantly reduces the energy cost by up to 14% over the state-of-the-art algorithm while maintaining similar revenue.…”
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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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Temperature Compensation Method for MEMS Ring Gyroscope Based on PSO-TVFEMD-SE-TFPF and FTTA-LSTM by Hongqiao Huang, Wen Ye, Li Liu, Wenjing Wang, Yan Wang, Huiliang Cao

“…This study proposes a novel parallel denoising and temperature compensation fusion algorithm for MEMS ring gyroscopes. First, the particle swarm optimization (PSO) algorithm is used to optimize the time-varying filter-based empirical mode decomposition (TVFEMD), obtaining optimal decomposition parameters. …”
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Structural knowledge-driven meta-learning for task offloading in vehicular networks with integrated communications, sensing and computing by Ruijin Sun, Yao Wen, Nan Cheng, Wei Wang, Rong Chai, Yilong Hui

“…Although this non-convex problem can be handled by the alternating minimization (AM) algorithm that alternatively minimizes the divided four sub-problems, it leads to high computational complexity and local optimal solution. …”
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A Decomposition-Integration Framework of Carbon Price Forecasting Based on Econometrics and Machine Learning Methods by Zhehao Huang, Benhuan Nie, Yuqiao Lan, Changhong Zhang

“…Empirical evidence demonstrates that this framework not only accurately captures the diverse characteristics of different data components but also significantly outperforms traditional benchmark models in predictive accuracy. By optimizing the GRU model with the grey wolf optimizer (GWO) algorithm, the framework enhances both prediction stability and adaptability, while the nonlinear integration approach effectively mitigates error accumulation. …”
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Microgrid system for electric vehicle charging stations integrated with renewable energy sources using a hybrid DOA–SBNN approach by Kommoju Naga Durga Veera Sai Eswar, M. Arun Noyal Doss, Mohammad Shorfuzzaman, Ali Elrashidi

“…The manuscript introduces a hybrid technique for efficient electric vehicle (EV) charging integrating the Dollmaker Optimization algorithm (DOA) and spatial Bayesian neural network (SBNN). …”
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Energy-Efficient UAV Relaying Robust Resource Allocation in Uncertain Adversarial Networks by Shakil Ahmed, Mostafa Zaman Chowdhury, Saifur Rahman Sabuj, Md Imtiajul Alam, Yeong Min Jang

“…We derive EE UAV relay-user maximization problem in the adversarial wireless networks at last. While the problem is non-convex, we propose an iterative and sub-optimal algorithm to optimize EE UAV relay with constraints, such as ICC, trajectory, speed, acceleration, and transmit power. …”
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