TA-RRT*: Adaptive Sampling-Based Path Planning Using Terrain Analysis by Taegeun Oh, Yun-Jae Won, Sungjin Lee

“…While existing RRT*-based algorithms perform node sampling and tree expansion in various ways to optimize path planning, they may still generate inefficient paths in complex terrain environments. …”
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Causal Unit Selection using Tractable Arithmetic Circuits by Haiying Huang, Adnan Darwiche

“…While early studies focused mainly on bounding a specific class of counterfactual objective functions using data, more recent work allows one to find optimal units exactly by reducing the causal objective to a classical objective on a meta-model, and then applying a variant of the classical Variable Elimination (VE) algorithm to the meta-model---assuming a fully specified causal model is available. …”
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Short-Term Traffic Flow Forecasting Model Based on GA-TCN by Rongji Zhang, Feng Sun, Ziwen Song, Xiaolin Wang, Yingcui Du, Shulong Dong

“…Therefore, a short-term traffic flow forecasting model GA-TCN based on genetic algorithm (GA) optimized time convolutional neural network (TCN) is proposed in this paper. …”
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Resource Allocation and Interference Coordination Strategies in Heterogeneous Dual-Layer Satellite Networks by Jinhong Li, Rong Chai, Tianyi Zhou, Chengchao Liang

“…We formulate a mathematical optimization problem to optimize resource allocation while minimizing co-channel interference and develop an ADMM-based distributed algorithm for efficient problem-solving. …”
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Real-time torque distribution simulation of parallel hybrid vehicle engine by Jing Wang

“…This study aims to develop a high-precision, robust torque distribution model to enhance energy utilization while addressing interference from environmental noise and extreme temperatures.MethodsA real-time torque distribution model integrates three core components: a Markov Decision Process framework transforms torque allocation into a mathematical optimization problem; the Proximal Policy Optimization algorithm enhanced with Prioritized Experience Replay dynamically generates control strategies; and Fiber Bragg Grating sensors achieve millisecond-level torque measurement by correlating shaft strain forces with wavelength shifts. …”
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Rethinking Exploration and Experience Exploitation in Value-Based Multi-Agent Reinforcement Learning by Anatolii Borzilov, Alexey Skrynnik, Aleksandr Panov

“…We aim to optimize a deep MARL algorithm with minimal modifications to the well-known QMIX approach. …”
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Lightweight CNN-Based Visual Perception Method for Assessing Local Environment Complexity of Unmanned Surface Vehicle by Tulin Li, Xiufeng Zhang, Yingbo Huang, Chunxi Yang

“…Subsequently, this identification result can be used as feedback for the heuristic algorithm to optimize and plan the USV’s path. The simulation results indicate that the developed model achieves an 80% reduction in model size while maintaining an accuracy exceeding 90%. …”
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MultS-ORB: Multistage Oriented FAST and Rotated BRIEF by Shaojie Zhang, Yinghui Wang, Jiaxing Ma, Jinlong Yang, Liangyi Huang, Xiaojuan Ning

“…The proposed method preserves all the advantages of the traditional ORB algorithm while significantly improving feature matching accuracy under illumination-induced blurring. …”
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European sovereign debt control through reinforcement learning by Tato Khundadze, Willi Semmler, Willi Semmler, Willi Semmler

“…We demonstrate that the Soft Actor-Critic algorithm provides comparable or, in some cases, better solutions to multi-objective macroeconomic optimization problems, in comparison to Nonlinear Model Predictive Control (NMPC) algorithm.…”
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Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surfaces Empowered Cooperative Rate Splitting with User Relaying by Kangchun Zhao, Yijie Mao, Yuanming Shi

“…Moreover, the proposed low-complexity algorithm dramatically reduces the computational complexity while achieving very close performance to the AO method.…”
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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. …”
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A Multiple Collision Channel Assignment Based on Imperfect Game Theory by Haofeng Dai, Shibiao He, Mian Tan, Pengyu Zheng, Hui Zhang

“…The channel allocation in wireless network will greatly affect the whole performance of the network. In order to solve this optimization problem, a kind of non cooperation channel allocation algorithm based on imperfect information was put forward. …”
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A Multiple Collision Channel Assignment Based on Imperfect Game Theory by Haofeng Dai, Shibiao He, Mian Tan, Pengyu Zheng, Hui Zhang

“…The channel allocation in wireless network will greatly affect the whole performance of the network. In order to solve this optimization problem, a kind of non cooperation channel allocation algorithm based on imperfect information was put forward. …”
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Enhancing Power Allocation in DAS: A Hybrid Machine Learning and Reinforcement Learning Model by S. Gnanasekar, K. C. Sriharipriya

“…ML models utilize historical data to forecast optimal power levels, while MARL agents dynamically adjust power allocation based on real-time conditions, aiming to enhance spectral efficiency, minimize interference, and optimize energy efficiency. …”
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Consider the master-slave game model of integrated energy system with step carbon trading and demand response by Yi Zhang, Zhezhou Zhang

“…In the context of deepening energy coupling and the high penetration of renewable energy, this paper proposes a master-slave game model incorporating comprehensive demand response and a stepped carbon trading mechanism. The goal is to optimize scheduling of demand response resources and fully leverage the flexibility of energy use within an integrated energy system while addressing conflicts of interest among multiple stakeholders, thereby enhancing trading revenue in Energy Markets while considering lower carbon emissions. …”
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Increasing the Efficiency Factor of Solar Power Plants Due to Solar Energy Localizing by V. I. Mironchuk, A. A. Velchenko

“…The article presents an analysis of the state of development of solar energy in Europe and  the  Republic  of  Belarus  for 2020.  An algorithm for increasing the efficiency factor of  solar power plants by localizing the solar trajectory depending on the latitude and longitude of the area has been proposed. …”
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TCCM: Trajectory Converged Chaff-Based Mix-Zone Strategy for Enhancing Location Privacy in VANET by Yunheng Wu

“…Additionally, the TCCM strategy incorporates a genetic algorithm to optimize mix zone placement and ensure a balance between privacy protection and resource efficiency. …”
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Adaptive enhancement of shoulder x-ray images using tissue attenuation and type-II fuzzy sets. by Qifeng Liu, Yong Han, Lu Shen, Jialei Du, Marzia Hoque Tania

“…The method integrates automatic tissue attenuation techniques, which enhance the image contrast by removing non-essential tissue components while preserving important tissues and bones. Additionally, we apply an improved Type-II fuzzy set algorithm to further optimize image sharpness. …”
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Enhancement of underwater acoustic signal based on denoising automatic-encoder by Jingwei YIN, Wuxiong LUO, Li LI, Xiao HAN, Longxiang GUO, Jianfeng WANG

“…Aiming at the difficulty of feature extraction of echo signal in active sonar,a self-encoder algorithm based on the combination of denoising self-encoder and convolution denoising self-encoder was proposed.Firstly,the preprocessing of noisy signal was carried out by using the advantage of denoising self-encoder in signal as a whole,and then the local feature of signal was optimized by combining convolutional denoising self-encoder to denoise the signal locally,so as to enhance the signal.The time domain waveform of the received signal is used as the feature input by the algorithm,and retains the signal’s amplitude and phase characteristics.The experimental results show that the algorithm not only effectively reduces the noise component in the signal,but also achieves better recovery effect in both time and frequency domains.…”
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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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