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Articles 1021 - 1050 of 40854

Full-Text Articles in Engineering

Influence Mechanisms Of Cleats On Hydraulic Fracture Propagation In Deep Coalbed Methane Reservoirs, Wang Haiyang, Lu Chen, Su Xu, Wang Yufei, Zhou Desheng Feb 2026

Influence Mechanisms Of Cleats On Hydraulic Fracture Propagation In Deep Coalbed Methane Reservoirs, Wang Haiyang, Lu Chen, Su Xu, Wang Yufei, Zhou Desheng

Coal Geology & Exploration

Objective Creating large-scale fracture networks through hydraulic fracturing serves as an important approach to the commercial development of deep coalbed methane (CBM) reservoirs. However, these reservoirs contain extensively developed cleats. The significantly different cementation strengths of cleat fillings lead to complex interactions between cemented cleats and major hydraulic fractures during fracture propagation. Therefore, clarifying the mechanisms underlying the influence of cemented cleats on hydraulic fracture propagation is critical to improving the simulation effects of deep CBM reservoirs. Methods Using particle flow code (PFC) discrete element method, combined with quasi-triaxial mechanical test results of the No.8 coal seam within the Yichuan …

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Seepage Dynamics And Damage Characteristics Of Shaft Lining Concrete Under Hydraulic Coupling, Xue Weipei, Zhou Yaya, Cheng Hua, Yao Zhishu, Rong Chuanxin, Wang Zhongjian, Wu Hao Feb 2026

Seepage Dynamics And Damage Characteristics Of Shaft Lining Concrete Under Hydraulic Coupling, Xue Weipei, Zhou Yaya, Cheng Hua, Yao Zhishu, Rong Chuanxin, Wang Zhongjian, Wu Hao

Coal Geology & Exploration

Objective Concrete serves as a lining material for support structures used in vertical shafts in coal mines, and its seepage performance and mechanical characteristics play a crucial role in ensuring structural safety. Furthermore, shaft lining concrete is placed under the groundwater level, subjected to a stress environment significantly different from that of surface concrete.Methods To investigate the impacts of groundwater seepage on the performance of shaft lining concrete under triaxial stress conditions, hydraulic coupling tests were conducted using a servo pressure testing machine equipped with a seepage apparatus, yielding data on permeability, elastic volumetric strain, crack volumetric strain, and …

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Evolutionary Mechanisms And Control Strategies For Surrounding Rock Stability Of Inclined Shafts Under Groundwater Seepage, Zhang Cun, Zhao Xiangyu, Chen Yanhong, Ren Zhaopeng, Wu Runze Feb 2026

Evolutionary Mechanisms And Control Strategies For Surrounding Rock Stability Of Inclined Shafts Under Groundwater Seepage, Zhang Cun, Zhao Xiangyu, Chen Yanhong, Ren Zhaopeng, Wu Runze

Coal Geology & Exploration

Background The western coal mining area has emerged as China’s primary coal production base. In this area, multiple ten-million-ton-scale coal mines are constructed using inclined shafts. Since inclined shafts run through multiple aquifers, many of them are subjected to shaft wall rupture and water inrushes to varying degrees.Methods This study aims to determine the impacts of groundwater seepage on the surrounding rock stability of inclined shafts. Using field survey, theoretical analysis, and numerical simulation, this study investigated the shaft wall stability of the main inclined shaft in water-rich sections in the Xiaojihan Coal Mine.Results and Conclusions Theoretical analysis …

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Mechanisms Behind Water Inrush Disasters Induced By Tbm Tunneling Passing Through Deeply Buried Fault Fracture Zones, Li Zhi, Dong Shuning, Shi Zhiyuan, Tong Renjian Feb 2026

Mechanisms Behind Water Inrush Disasters Induced By Tbm Tunneling Passing Through Deeply Buried Fault Fracture Zones, Li Zhi, Dong Shuning, Shi Zhiyuan, Tong Renjian

Coal Geology & Exploration

Objectives While passing through a deeply buried water-rich fault fracture zone, a tunnel boring machine (TBM) frequently faces an extremely high risk of water inrushes, seriously restricting the engineering safety and efficiency. Methods This study aims to reveal the evolution patterns of water inrush disasters in the case where the TBM roadway tunneling passes through faults zones and propose technologies for advance prevention and control to mitigate the water inrush risk. Against the engineering background of the tunneling of a main roadway in a coal mine within a North China-type coalfield, this study established a 3D numerical model using the …

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Tle-Unet-Based Image Segmentation And Feature Extraction Of Water-Cooling-Induced Complex Cracks In High-Temperature Rock Masses, Fu Tianyu, Hu Mangu, Zhang Xiaojun, Yang Xiaobin, Lyu Fu, Lyu Xiangfeng, Peng Lei Feb 2026

Tle-Unet-Based Image Segmentation And Feature Extraction Of Water-Cooling-Induced Complex Cracks In High-Temperature Rock Masses, Fu Tianyu, Hu Mangu, Zhang Xiaojun, Yang Xiaobin, Lyu Fu, Lyu Xiangfeng, Peng Lei

Coal Geology & Exploration

Objective and Method Water cooling-induced macroscopic surface cracks in high-temperature rock masses are characterized by fine scales, pronounced length variations, and severe class imbalance in images, posing significant challenges for image segmentation. To address these challenges, this study proposed TLE-UNet, a semantic segmentation network for rock crack images. First, through thermal treatment and uniaxial compression tests of granite specimens, crack images under varying temperatures were acquired. Then, using a self-developed Lite Edge Fusion module, high-resolution shallow features were finely aligned with deep semantic features at varying scales. Furthermore, edge detection and channel-attention mechanisms were combined to enhance crack boundary perception. …

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Multiscale Fusion Aot-Gan Intelligent Filling Of Blank Strip For Formation Microresistivity Imaging Logging, Huang Luyi, Wang Fei, Kong Lingsong, Jiang Qishu Feb 2026

Multiscale Fusion Aot-Gan Intelligent Filling Of Blank Strip For Formation Microresistivity Imaging Logging, Huang Luyi, Wang Fei, Kong Lingsong, Jiang Qishu

Coal Geology & Exploration

Objective Formation microresistivity imaging (FMI) images features incomplete borehole coverage and thus contain blank strips due to the gaps between electrode pads, as well as their pushing and attachment mechanisms. Traditional blank strip filling methods suffer from several limitations, including susceptibility to image distortion and difficulty in retaining information on fine-scale structures such as fractures. This study developed an aggregated contextual-transformation generative adversarial network (AOT-GAN) for blank strip filling, aiming to achieve high-precision and high-fidelity information reconstruction. Methods Initially, a high-quality dataset was prepared based on original FMI images, along with full-borehole images obtained through image inpainting using CIFLog. Then, …

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A Drilling-Punching-Hole Protection Integrated Hydraulic Caving Technology For Broken Soft And Low-Permeability Coal Seams, Yao Ningping, Hao Shijun, Zhang Jinbao, Wei Hongchao, Nie Chao Feb 2026

A Drilling-Punching-Hole Protection Integrated Hydraulic Caving Technology For Broken Soft And Low-Permeability Coal Seams, Yao Ningping, Hao Shijun, Zhang Jinbao, Wei Hongchao, Nie Chao

Coal Geology & Exploration

Objective and Method For broken soft and low-permeability coal seams, gas drainage achieved through permeability enhancement and pressure relief by cross-seam hydraulic caving in coal seam floor faces problems including serious borehole collapse in the drilled coal seam intervals, low construction efficiency, and poor gas drainage performance. To address these problems, this study proposed a high-efficiency drilling-punching-hole protection integrated gas drainage technology, which enabled hydraulic caving, permeability enhancement, and pressure relief. Furthermore, this study developed a drilling-punching-hole protection integrated caving device. Through laboratory experiments conducted under pressure conversion and central channels equipped with controllable opening/closing mechanisms, this study selected the …

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Surface-Borehole Resistivity Tomography For Seepage Detection In Earth-Rock Dams, Tan Lei, Hu Xiongwu, Zhang Pingsong, Jiang Xiaoyi, Dong Ya, Liu Fuda, Li Chunyang, Xu Hu Feb 2026

Surface-Borehole Resistivity Tomography For Seepage Detection In Earth-Rock Dams, Tan Lei, Hu Xiongwu, Zhang Pingsong, Jiang Xiaoyi, Dong Ya, Liu Fuda, Li Chunyang, Xu Hu

Coal Geology & Exploration

Objective Resistivity methods allow for effective detection of seepage in reservoir dams. However, when used to detect the hidden hazards of dams, the surface resistivity method fails to accurately identify vulnerable areas across an entire dam due to blind spots near both dam abutments and insufficient resolutions for deep parts. Methods This study proposed a seepage detection technique for earth-rock dams based on surface-borehole resistivity tomography, followed by the analysis of the distribution of surface-borehole resistivity under the lateral and vertical variations in a seepage zone through numerical simulations. This technique was applied to the Shibi reservoir dam. Using the …

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Note: Greenvent – Revolutionizing Methane Management With Hybrid Energy Processing In Mine Ventilation, Roman J. Jędrzejczyk, Damian K. Chlebda, Jacek Dańczak, Piotr Rosikowski, Monika A. Koperska, Robert E. Hayes, Joseph P. Mmbaga, Robert Hildebrandt, Joanna Profic-Paczkowska Feb 2026

Note: Greenvent – Revolutionizing Methane Management With Hybrid Energy Processing In Mine Ventilation, Roman J. Jędrzejczyk, Damian K. Chlebda, Jacek Dańczak, Piotr Rosikowski, Monika A. Koperska, Robert E. Hayes, Joseph P. Mmbaga, Robert Hildebrandt, Joanna Profic-Paczkowska

Journal of Sustainable Mining

Methane plays a significant role in intensifying the greenhouse effect, possessing a global warming potential more than twenty times greater than that of CO2 when measured on a carbon-dioxide-equivalent basis. Hence, identifying efficient methods to mitigate methane emissions is crucial for safeguarding the environment, ensuring economic viability, and maintaining practicality. Globally, research initiatives are dedicated to crafting an effective catalyst system for methane oxidation, which involves developing catalysts, comprehending their characteristics, and determining the best way of bonding them to structural supports to enhance functionality. Notably, systems that incorporate metals from the non-noble d-block of the periodic table as …

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A New Highly Oxygen-Deficient And Cubic Pr3Zro8-Δ For Intermediate-Temperature Thermochemical Production Of Oxygen And Hydrogen, Jiaxin Lu, Yongliang Zhang, Luhong Chen, Yan Chen, Ke An, Yasser Shoukry, Xinfang Jin, Zhi-Hao Wang, Sai Mu, Kevin Huang Feb 2026

A New Highly Oxygen-Deficient And Cubic Pr3Zro8-Δ For Intermediate-Temperature Thermochemical Production Of Oxygen And Hydrogen, Jiaxin Lu, Yongliang Zhang, Luhong Chen, Yan Chen, Ke An, Yasser Shoukry, Xinfang Jin, Zhi-Hao Wang, Sai Mu, Kevin Huang

Faculty Publications

Two-step thermochemical cycles offer a clean route for hydrogen and oxygen production but are typically limited to high temperatures exceeding 1500 °C. Lowering operating temperatures would enable the use of alternative heat sources such as industrial waste heat. Here, we report Pr3ZrO8 as a new enabling material for efficient intermediate-temperature redox cycling, with thermal reduction at 900 °C in argon and steam oxidation at 400 °C. Pr3ZrO8 adopts a face-centered cubic structure similar to CeO2 but exhibits significantly greater oxygen deficiency, achieving average oxygen and hydrogen fluxes of 331.7 and 70.3 µmol·g-1, respectively, …

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Assessing The Geomechanical Modelling Of Underground Reservoir For Co₂ Storage Trapping Mechanisms, Bonavian Hasiholan, Mohammed Ali Farea, Elhassan Mostafa Abdallah, Sami Abdelrahman M. Yagoub, Yasir Mukhtar Feb 2026

Assessing The Geomechanical Modelling Of Underground Reservoir For Co₂ Storage Trapping Mechanisms, Bonavian Hasiholan, Mohammed Ali Farea, Elhassan Mostafa Abdallah, Sami Abdelrahman M. Yagoub, Yasir Mukhtar

Mathematical Modelling and Numerical Simulation with Applications

Effective carbon dioxide (CO₂) storage is essential for mitigating climate change amid increasing global greenhouse gas emissions. This study investigates the influence of geomechanics on CO₂ storage performance within carbon capture and storage (CCS), focusing on structural, residual, and solubility trapping mechanisms using a fully coupled modeling framework. Two numerical models, with and without geomechanical effects, are developed to evaluate impacts on reservoir behavior, CO₂ migration, and trapping efficiency. Each mechanism is analyzed separately and within an integrated framework to assess their combined contributions. Results indicate that geomechanical coupling increases reservoir pressure, reduces CO₂ flow velocity, enhances migration control, and …

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Research On System And Application Framework Of Tactical Wargaming Simulation Driven By Ai4s, Dayong Liu, Qisheng Guo, Zhiming Dong, Xuehuan Qiu, Zhuoli Liu Feb 2026

Research On System And Application Framework Of Tactical Wargaming Simulation Driven By Ai4s, Dayong Liu, Qisheng Guo, Zhiming Dong, Xuehuan Qiu, Zhuoli Liu

Journal of System Simulation

Abstract: Tactical wargaming simulation, as a crucial tool for combat analysis, simulation training, and equipment demonstration and test, has become a significant means for generating combat effectiveness. Integrating AI into simulation not only enhances simulation efficiency but also diminishes reliance on humans. To assist professionals engaged in tactical wargaming simulation in mastering AI application methods, fostering a systematic mindset, and understanding evolving trends, this paper provided a concise overview of the principles behind AI for science (AI4S). Subsequently, it conducted an analysis of AI4S's application effectiveness in tactical wargaming simulation, established an AI4S-driven wargaming simulation system, and elucidated its composition, …

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Social Cognition Simulation With Large Language Model-Driven Agents, Mingxin Zhang, Jinxuan Wu, Rui Zhu, Yunlong Wang, Wenjuan Meng, Zhe Liu, Xu Li, Xiaolei Chen, Yuxuan Liang, Yi Zheng, Xiangyang Xue Feb 2026

Social Cognition Simulation With Large Language Model-Driven Agents, Mingxin Zhang, Jinxuan Wu, Rui Zhu, Yunlong Wang, Wenjuan Meng, Zhe Liu, Xu Li, Xiaolei Chen, Yuxuan Liang, Yi Zheng, Xiangyang Xue

Journal of System Simulation

Abstract: With the continuous evolution of the capabilities of generative LLMs, their application in social cognition simulation is demonstrating paradigm-shifting potential. Traditional social simulation methods predominantly rely on static rules and simplified behavioral models, making it difficult to capture the dynamic evolution and cultural complexity of human social behavior. LLM-driven agents, equipped with contextual understanding and natural language generation capabilities, are emerging as novel tools for modeling social cognitive mechanisms, enabling the simulation of complex sociopsychological processes such as identity construction, value judgment, and intentional reasoning. This paper briefly introduced the technical foundations of LLMs and highlighted their suitability for …

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Integrated Development Environment For Digital Test Applications Based On Cloud-Edge-End Architecture, Wenguang Yu, Qun Li, Hongjie Dang, Hao Chen, Ping Yang Feb 2026

Integrated Development Environment For Digital Test Applications Based On Cloud-Edge-End Architecture, Wenguang Yu, Qun Li, Hongjie Dang, Hao Chen, Ping Yang

Journal of System Simulation

Abstract: Digital test applications need to be constructed using the unified digital test development tool. After analyzing the features of digital test applications such as large-sample autonomous run, high computational efficiency requirement, and diverse task scenarios, this paper proposes the integrated development environment (IDE) for digital test applications based on cloud-edge-end architecture. The layered expandable architecture, the hybrid integration framework of multi-source heterogeneous models, and the cloud-edge-end collaborative deployment architecture are designed for the IDE of digital test applications. The IDE supports the rapid development, integration, and execution of digital test models and enables development of digital test applications on …

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Research On Chain-Of-Thought Technology For Situational Awareness Based On Modular Reasoning, Hongyuan Ji, Duzheng Qing Feb 2026

Research On Chain-Of-Thought Technology For Situational Awareness Based On Modular Reasoning, Hongyuan Ji, Duzheng Qing

Journal of System Simulation

Abstract: To address issues such as insufficient intelligence of situational understanding in traditional simulation systems, a situational visual question answering dataset was constructed, and a modular reasoning framework was proposed. The SACoT was built, which, under a zero-shot setting, employed expert prompts to guide the model in task decomposition and multimodal information fusion, generating reasoning chains to enhance semantic cognition and interpretability and offering a scalable solution with low computation cost. Experimental results indicate that SACoT improves task allocation, enables models to focus on query-relevant image details, mitigates the fragmentation of chain-of-thought induced by multi-step reasoning, and reduces long-form …

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Simulation Of Robotic Arm Ball-Catching Strategy Based On Curriculum Rl Of Transformer, Ziyao Zhang, Yunfeng Ji Feb 2026

Simulation Of Robotic Arm Ball-Catching Strategy Based On Curriculum Rl Of Transformer, Ziyao Zhang, Yunfeng Ji

Journal of System Simulation

Abstract: Method integrating the PPO algorithm with Transformer network architecture is proposed, and curriculum learning strategy is introduced to solve the difficult training convergence and low efficiency of traditional RL methods in complex and dynamic high-degree-of-freedom tasks such as robotic arm ball catching. The Transformer is employed to effectively capture the complex high-dimensional dependency between the robotic arm's state space, ball trajectory, and environmental physical parameters. Curriculum learning progressively increases catching difficulty by designing training tasks from simple to complex objectives. The experimental results show this method increases the ball-catching success rate by over 60% compared to the traditional …

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Research On Uav Target Tracking Algorithm For Simulation Scenarios, Xinyi Li, Zhenfei Wang, Han Wu Feb 2026

Research On Uav Target Tracking Algorithm For Simulation Scenarios, Xinyi Li, Zhenfei Wang, Han Wu

Journal of System Simulation

Abstract: To address the need for automatic UAV tracking of moving targets in simulated experiments, this paper proposed a long-term automatic tracking method based on an improved channel and spatial reliability-aware tracker (CSRT) algorithm. The target edge features were detected using the Laplacian of guided filter (LOGF) through guided filtering and then fused with the histogram of oriented gradient (HOG) and color names (CN) features to enhance the algorithm's discriminative ability for the target. To evaluate the target state, the paper used average peak correlation energy and perceptual hash Hamming distance. When the target was occluded, the paper employed YOLOv8 …

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Distributed Optimization For Integrated Energy Based On Multi-Agent Reinforcement Learning, Caixia Tao, Naikun Chen, Fengyang Gao, Jiangang Zhang Feb 2026

Distributed Optimization For Integrated Energy Based On Multi-Agent Reinforcement Learning, Caixia Tao, Naikun Chen, Fengyang Gao, Jiangang Zhang

Journal of System Simulation

Abstract: To address the energy management and privacy preservation problems faced by the coordinated optimization of distributed integrated energy systems, a distributed coordinated optimization strategy based on the multi-agent proximal policy optimization algorithm was proposed. An energy management model was established under the MDP framework; the electrical and thermal heterogeneous energy characteristics were considered; a multi-region two-layer interaction mechanism was constructed. Under the framework of centralized training and decentralized execution, homomorphic encryption was utilized to avoid privacy leakage during the coordination process, while accurately quantifying individual contributions to mitigate the problem of variance explosion in multi-agent policy evaluation. In the …

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Prediction Of Inflow Wind Field For Large-Scale Wind Turbines Based On Multimodal Hybrid Deep Learning, Jiheng Wang, Yang Hu, Ziqiu Song, Fang Fang, Jizhen Liu Feb 2026

Prediction Of Inflow Wind Field For Large-Scale Wind Turbines Based On Multimodal Hybrid Deep Learning, Jiheng Wang, Yang Hu, Ziqiu Song, Fang Fang, Jizhen Liu

Journal of System Simulation

Abstract: To address the demand for high-precision inflow wind field prediction in large-scale wind turbines, traditional CFD methods suffer from high computational costs and poor real-time applicability. This paper proposed a multimodal hybrid deep learning-based wind field prediction method. The proposed method took turbine operating parameters and far-range wind field images as inputs and generated short-range wind field images as outputs. By employing a U-Net-Transformer-GAN hybrid architecture, the model achieved multi-scale feature extraction, temporal dependency modeling, and highresolution wind field image generation. The vorticity transport equation and Kármán-Howarth turbulence statistics were incorporated as weak constraints to enhance physical consistency, while …

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Llm-Driven Multi-Agent Social Network Simulation: Interdisciplinary Integration And Cutting-Edge Development, Jiting Li, Yi Sun, Yirong Wang, Yiqin Lin, Jun Jia, Gangsong Ding Feb 2026

Llm-Driven Multi-Agent Social Network Simulation: Interdisciplinary Integration And Cutting-Edge Development, Jiting Li, Yi Sun, Yirong Wang, Yiqin Lin, Jun Jia, Gangsong Ding

Journal of System Simulation

Abstract: The breakthrough of LLMs has provided powerful tools for social network research, advancing multi-agent social network simulation into a new era. This review systematically examined recent progress in LLM-driven multi-agent social network simulation research through a integrated perspective of multi-disciplines such as artificial intelligence, psychology, communication studies, and sociology. A three-tiered research system, which has gradually formed in this field and encompassed micro-level individual behaviors, meso-level interactive relations, and macro-level system emergence, was summarized. At the micro-level, research focuses on individual human behavior simulation, and numerous studies are dedicated to developing human-like agents with complex cognitive and affective architectures …

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An Adaptive Robot Path Planning Based On Improved Rea* Algorithm, Ling Zhu, Jing Li, Zhaohui Zhang Feb 2026

An Adaptive Robot Path Planning Based On Improved Rea* Algorithm, Ling Zhu, Jing Li, Zhaohui Zhang

Journal of System Simulation

Abstract: In order to improve the computational efficiency and path smoothness in a robot's global path planning, an adaptive robot path planning strategy based on an improved unilateral rectangle expansion A*(REA*) algorithm was proposed. The robot's operational safety was ensured by setting a buffer around obstacles. A passable interval formed by unilateral rectangle expansion was used as the operation unit, and bidirectional alternating search was combined to enhance the path planning efficiency. Inspired by potential field theory, the evaluation function was optimized by introducing a vector form to achieve fast adaptive obstacle avoidance. A new path planning strategy was proposed …

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Evolutionary Game-Based Analysis Of Responses To Hallucinations In Generative Artificial Intelligence, Qiang Yan, Qianyu Zhang, Na Wei Feb 2026

Evolutionary Game-Based Analysis Of Responses To Hallucinations In Generative Artificial Intelligence, Qiang Yan, Qianyu Zhang, Na Wei

Journal of System Simulation

Abstract: The accelerated deployment of generative artificial intelligence, particularly large language models, has amplified the social risks of hallucinations, posing systemic threats to the credibility of the information ecosystem, the effectiveness of users’ cognitive decision-making, and the governance security in the public domain. Research primarily focuses on hallucination mitigation mechanisms at the technical level or the design of regulatory frameworks at the policy level, lacking a systematic theoretical analysis of the evolutionary logic of strategic interactions among the “large language models, users, and regulators” under conditions of bounded rationality. By introducing evolutionary game theory into the field of generative artificial …

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Intelligent Air Combat Decision-Making Method Based On Bigru And Priority Dynamic Sampling, Zhengkun Ding, Jiaqi Liu, Junzheng Xu, Yuezhu Xu, Xingmei Wang Feb 2026

Intelligent Air Combat Decision-Making Method Based On Bigru And Priority Dynamic Sampling, Zhengkun Ding, Jiaqi Liu, Junzheng Xu, Yuezhu Xu, Xingmei Wang

Journal of System Simulation

Abstract: Current multi-agent reinforcement learning algorithms suffer from low efficiency in utilizing experience data and difficulties in setting appropriate learning rates. To address these issues, this paper proposed a BiGRU multi-agent PPO with priority sampling and dynamic learning rate. The algorithm incorporated a BiGRU network to enhance the policy network's ability to model temporal information. A priority partial sampling mechanism was introduced to improve the utilization efficiency of high-value experience data. Additionally, an improved Adam optimizer with dynamic learning rate adjustment was employed to address the challenge of learning rate configuration. Simulation experiment results demonstrate that the algorithm significantly …

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Knowledge-Enhanced Llm-Based Method For Regional Traffic Signal Control, Risheng Xu, Linyao Yang, Yuanqi Qin, Xiao Wang, Changyin Sun Feb 2026

Knowledge-Enhanced Llm-Based Method For Regional Traffic Signal Control, Risheng Xu, Linyao Yang, Yuanqi Qin, Xiao Wang, Changyin Sun

Journal of System Simulation

Abstract: Adaptive traffic signal control (ATSC) is crucial for alleviating regional traffic congestion, yet it faces severe challenges in real-time response to unexpected events and global coordination. The DRL method relies on pure data-driven approaches, suffering from core limitations such as poor generalization, weak interpretability, and a lack of guidance from emergency disposal knowledge, which makes them difficult to meet the demands of complex traffic scenarios. A control system that integrates knowledge-driven and data-optimized approaches was proposed. The GraphRAG was used to construct a dynamic traffic knowledge graph, providing LLMs with real-time updated historical emergency disposal experience and road …

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Resource-Efficient Continuous Learning Framework For Edge Real-Time Video Analytics, Shuxia Wu, Junjie Zhang, Delong Chen, Zheyi Chen Feb 2026

Resource-Efficient Continuous Learning Framework For Edge Real-Time Video Analytics, Shuxia Wu, Junjie Zhang, Delong Chen, Zheyi Chen

Journal of System Simulation

Abstract: By deploying lightweight models at the network edge, edge systems can provide services of real-time video analytics. However, due to the data drift caused by the discrepancy between model training and actual deployment, it is challenging to construct lightweight models that match real-world environments. To address this challenge, a resource-efficient continuous learning framework for edge real-time video analytics (CL4VA) was proposed. A region of interest-granularity predictor for accuracy degradation was introduced to efficiently select key samples from real-time video streams. A two-layer mixed sample pool was constructed to adaptively trigger the model's continuous learning and avoid the issue of …

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Reinforcement Learning Based Method For Uav Team Orienteering Optimization Under Multi-Constraint Condition, Can Yang, Kai Chen, Feng Zhu Feb 2026

Reinforcement Learning Based Method For Uav Team Orienteering Optimization Under Multi-Constraint Condition, Can Yang, Kai Chen, Feng Zhu

Journal of System Simulation

Abstract: Traditional optimization methods struggle with efficiency, while reinforcement learning approaches often yield low solution quality and high training costs. In response, this paper proposes an attention mechanism-based reinforcement learning method. A dynamic attention strategy network with multi-information fusion is designed to improve solution quality. A visibility-graph approach is employed to simplify threat zone constraints and speed up convergence, and a decoding sequence reordering mechanism is introduced for further performance optimization of the solution. The simulation results show that the method generates high-quality solutions within milliseconds, achieving total rewards that approach or even surpass those obtained by traditional solvers …

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Strike Strategy Planning Method Of Unmanned Ground Vehicles Based On Improved Ppo Algorithm, Bingkun Wang, Yue Wang, Mei Yang, Pengnian Zhang, Bohao Fan, Jie Tang Feb 2026

Strike Strategy Planning Method Of Unmanned Ground Vehicles Based On Improved Ppo Algorithm, Bingkun Wang, Yue Wang, Mei Yang, Pengnian Zhang, Bohao Fan, Jie Tang

Journal of System Simulation

Abstract: An improved PPO algorithm based on the hybrid action space and gated recurrent unit (GRU) is proposed to address the limitations of predefined strike rules in maximizing the hitting accuracy of unmanned ground vehicles and the difficult coupling and optimization of continuous motion planning and discrete strike decision-making. The environmental model and target model are built for the process of unmanned ground vehicles' strike missions, coupled with a three-layer model for unmanned ground vehicles that fuses kinematic constraints, situational awareness, and dynamic decision-making. Two distinct policy networks are employed, including the continuous motion planning network for path planning, and …

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Knowledge Closed-Loop Driving-Based Intelligent Game Confrontation Simulation, Quan Liu, Yu Wang, Linyue Liu, Hao Chen, Jian Huang Feb 2026

Knowledge Closed-Loop Driving-Based Intelligent Game Confrontation Simulation, Quan Liu, Yu Wang, Linyue Liu, Hao Chen, Jian Huang

Journal of System Simulation

Abstract: For human-machine intelligence integration and collaborative intelligence enhancement, a “knowledge-model-data-knowledge” closed-loop paradigm for combat simulation is proposed to guide the design of a DRL-based game confrontation simulation architecture. By building a combat priori knowledge-guided DRL agent model, mining and analyzing the time series data of agent interactions generated during simulations, and extracting combat posterior knowledge that expands the cognition boundaries of commanders, the knowledge closed-loop driving mechanism for intelligent combat simulations is achieved. The experimental results indicate that the proposed mechanism can effectively endow the combat simulation system with intelligence growth capabilities, providing valuable reference for the deepening …

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Intelligent Decision-Making Method In Imbalanced Air Combat Based On Asymmetric Self-Play, Wei Zheng, Jiahao Tang, Xiaoping Xiong, Xin Fan Feb 2026

Intelligent Decision-Making Method In Imbalanced Air Combat Based On Asymmetric Self-Play, Wei Zheng, Jiahao Tang, Xiaoping Xiong, Xin Fan

Journal of System Simulation

Abstract: To solve the problem of strategy convergence caused by role homogenization in traditional self-play for imbalanced air combat, an intelligent decision-making method based on asymmetric selfplay was proposed. This method decoupled tactics from control by employing a hierarchical reinforcement learning framework and designed differentiated reward functions for advantaged and disadvantaged sides. Bidirectional independent policy pools were constructed to promote the co-evolution of strategies. The proximal policy optimization algorithm was utilized to train the model. Experiments in 1v1 weapon-imbalanced and 2v1 numerically-imbalanced scenarios demonstrate that compared to symmetric self-play, the proposed method increases the kill rate of the advantaged …

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Agent-Based Pathfinding Method For Indoor Fire Emergency Evacuation, Ao Tian, Jianqin Zhang, Zheng Wen, Chaonan Hu, Hong Zhao, Bo Shen Feb 2026

Agent-Based Pathfinding Method For Indoor Fire Emergency Evacuation, Ao Tian, Jianqin Zhang, Zheng Wen, Chaonan Hu, Hong Zhao, Bo Shen

Journal of System Simulation

Abstract: To improve emergency evacuation efficiency and reduce casualties in dynamic fire scenarios, a real-time path re-planning method based on agents and dynamic A* algorithm framework is proposed. The behavior and actions of the agent is modeled. A reward function is designed, and an agent-based evacuation framework is constructed. Based on fire simulation data, a dynamic cost network involving parameters such as thermal radiation, smoke visibility, and CO concentration is constructed to achieve spatiotemporally continuous modeling of fire environments. By optimizing the composite cost function through dynamic weight allocation, combined with an improved heuristic function and dynamic search mechanism, local …

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