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Articles 2941 - 2970 of 27375

Full-Text Articles in Engineering

Assessing The Potential And Suitability Of Geothermal Resources Using Monte Carlo Simulation And Game-Based Combination Weighting Method, He Yixiang, Ding Pengpeng, Liu Shaohua, Wang Mingzhu, Zhu Lei May 2025

Assessing The Potential And Suitability Of Geothermal Resources Using Monte Carlo Simulation And Game-Based Combination Weighting Method, He Yixiang, Ding Pengpeng, Liu Shaohua, Wang Mingzhu, Zhu Lei

Coal Geology & Exploration

Background Geothermal energy in porous sandstone reservoirs is recognized as stable, efficient clean energy. However, these reservoirs feature heterogeneity and exploration uncertainty, posing serious challenges to probabilistic resource assessment and the identification of suitability for resource development.Methods This study investigated the geothermal resources in the Guantao Formation within the northwest Shandong plain. Using the volumetric method and Monte Carlo simulation, this study assessed the uncertainty of the resource potential. Then, considering the characteristics of geothermal resources, the attributes of geological structures, and the social economy, this study developed a multi-dimensional evaluation index system for the suitability of sandstone geothermal …

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Table Of Contents, The Editors May 2025

Table Of Contents, The Editors

Coal Geology & Exploration

No abstract provided.

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Sedimentary Patterns And Exploitation Practices Of Tight-Sand Gas Reservoirs In Coal Measure Strata: A Case Study Of The 3rd Submember Of The Second Member Of The Permian Shanxi Formation In The Daning-Jixian Block, Zhang Lei, Huang Li, Zhao Longmei, Wang Feng, Zhang Yixin, Shi Shi, Zhang Wen, Zhao Haoyang, Chen Tong, Tong Jiangnan May 2025

Sedimentary Patterns And Exploitation Practices Of Tight-Sand Gas Reservoirs In Coal Measure Strata: A Case Study Of The 3rd Submember Of The Second Member Of The Permian Shanxi Formation In The Daning-Jixian Block, Zhang Lei, Huang Li, Zhao Longmei, Wang Feng, Zhang Yixin, Shi Shi, Zhang Wen, Zhao Haoyang, Chen Tong, Tong Jiangnan

Coal Geology & Exploration

Background The third submember of the second member of the Permian Shanxi Formation (also referred to as the Shan 23 submember) in the Daning-Jixian block along the eastern margin of the Ordos Basin is identified as a primary target layer for tight-sand gas production in the block. In the early stage of the block development, play fairways were initially identified through fundamental studies on provenance areas and sedimentary systems. Accordingly, a gas field with an annual production of 10 × 108 m3 was constructed in the block. However, further exploitation reveals that the sandstones in the Shan …

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Application Of A Uav-Borne Gpr System In The Detection Of Water Bodies And Cavities, Wang Ying, Sun Chenchen, Zhang Lu, Chen Yifei, Lu Song, Zhou Feng May 2025

Application Of A Uav-Borne Gpr System In The Detection Of Water Bodies And Cavities, Wang Ying, Sun Chenchen, Zhang Lu, Chen Yifei, Lu Song, Zhou Feng

Coal Geology & Exploration

Objective and Methods The unmanned aerial vehicle (UAV)-borne ground-penetrating radar (GPR) system, enjoying the advantages of high resolution and non-contact detection, is applicable to the detection of water accumulation in coal seams and goaves in mines. Therefore, this study proposed a rapid detection method based on a UAV-borne air-coupled GPR system to enhance the exploration efficiency of mining areas and reduce the time and risks of manual explorations. Given the limitations of the test scenarios in actual coal mines, this study investigated the water body of the Fanxiong reservoir in Ezhou City and surrounding drainage culverts for equivalent validation, aiming …

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Transparent Prevention And Control System For Water Hazards In Mine Floors Under Empowerment Based On Spatiotemporal Information Fusion, Liu Zaibin, Yan Junsheng, Wang Jianghong, Gao Yaoquan, Yang Hui, Bai Baojun, Lu Jingjin, Wang Hongwei, Wang Gang May 2025

Transparent Prevention And Control System For Water Hazards In Mine Floors Under Empowerment Based On Spatiotemporal Information Fusion, Liu Zaibin, Yan Junsheng, Wang Jianghong, Gao Yaoquan, Yang Hui, Bai Baojun, Lu Jingjin, Wang Hongwei, Wang Gang

Coal Geology & Exploration

Background Water hazards in coal mines frequently cause heavy casualties, severely affecting the safe mining of coal mines. Methods With the continuous advancements in both the construction of real scene 3D views and coal mine intelligentization, this study examined the development of the intelligent geological guarantee system for the Tangjiahui Coal Mine in Inner Mongolia, as well as the prevention and control of water hazards in the Ordovician limestones in the coal mine floor. Accordingly, this study elaborated on enhancing the prevention and control capacity against water hazards in coal mines during the mining cycle of a mining face using …

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Experimental Study On Unloading Confining Pressure Deformation And Damage Failure Of Multi-Source Coal-Based Solid Waste Cemented Backfill, He Xiang, Wei Longqiang, Yang Ke, Zhang Tong, Zhang Cun, Zhang Zilong, Chen Yanjun May 2025

Experimental Study On Unloading Confining Pressure Deformation And Damage Failure Of Multi-Source Coal-Based Solid Waste Cemented Backfill, He Xiang, Wei Longqiang, Yang Ke, Zhang Tong, Zhang Cun, Zhang Zilong, Chen Yanjun

Coal Geology & Exploration

Objective The preparation of multi-source coal-based solid waste into filling materials for interval strip filling mining is one of the important means of green coal mining. The deformation and failure law of multi-source coal-based solid waste cemented backfill during strip coal pillar mining directly affects the stability of the stope.Methods Five typical solid wastes were mixed with cement to prepare cemented backfill. The conventional triaxial and constant axial pressure unloading confining pressure stress tests of backfill specimens were carried out. The stress-strain curves and failure characteristics of backfill under two stress loading paths were analyzed. The evolution law of …

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Fluoride Ion Removal From Mine Water Via Nucleation Crystallization Pelleting Process, Zhang Xiyu, Dong Shuning, Wang Hao, Jin Pengkang, Wang Xiaodong, Wang Qiangmin, Zhang Tao May 2025

Fluoride Ion Removal From Mine Water Via Nucleation Crystallization Pelleting Process, Zhang Xiyu, Dong Shuning, Wang Hao, Jin Pengkang, Wang Xiaodong, Wang Qiangmin, Zhang Tao

Coal Geology & Exploration

Objective The mine water associated with coal mining tends to be rich in fluoride ions. If discharged directly without effective treatment, such water will cause severe pollution to regional ecology, affecting the quality of water resources and the stability of the ecosystem. Methods This study focuses on the challenging treatment of the fluoride pollution caused by coal mining-associated mine water. To overcome the bottlenecks including low efficiency and weak anti-interference of traditional methods for fluoride removal, this study designed a setup for fluoride removal using the nucleation crystallization pelleting (NCP) processing and proposed a novel fluoride removal method—NCP chemical precipitation. …

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A Seismic Random Noise Suppression Method Based On Cnn-Mamba, Wei Xiujuan, Liu Xingye, Zhou Huailai May 2025

A Seismic Random Noise Suppression Method Based On Cnn-Mamba, Wei Xiujuan, Liu Xingye, Zhou Huailai

Coal Geology & Exploration

Background Seismic random noise suppression is recognized as a key step to improve the quality of seismic data. Data-driven deep learning provides an intelligent solution for the noise suppression. However, mainstream random noise intelligent methods based on convolutional neural networks (CNNs) are constrained by their local receptive fields. This limitation results in insufficient collaborative optimization between local details and macroscopic structures during denoising, further reducing the noise suppression accuracy. Transformer models, which are widely applied to global feature extraction, can effectively capture long-distance dependencies through the self-attention mechanism, theoretically overcoming the limitations of CNNs in global modeling. However, these models …

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Endo Almost 3–Absorbing Sub-Modules (Modules) And Related Concepts, Wafaa H. Hanoon, Mahmood S. Fiadh, Marwah W. Allami May 2025

Endo Almost 3–Absorbing Sub-Modules (Modules) And Related Concepts, Wafaa H. Hanoon, Mahmood S. Fiadh, Marwah W. Allami

Iraqi Journal for Computer Science and Mathematics

The concept of Endo Almost 3-Absorbing sub-modules (modules) is presented in this study, along with observations and the connections between Endo 2-Absorbing sub-modules (modules), Endo Approximately 2-Absorbing sub-modules (modules), Endo quasi-prime sub-modules (modules), and Endo prime sub-modules (modules). The study provides a range of attributes, illustrations, and justifications for these concepts. We aim to utilize the ramifications of this research to develop new ideas based on Endo Almost 3-Absorbing sub-modules (modules). Along with observations and an exploration of the relationships between Endo 2-Absorbing sub-modules (modules), Endo Approximately 2-Absorbing sub-modules (modules), Endo quasi-prime sub-modules (modules), and Endo prime sub-modules (modules), the …

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Retracted: A Group Decision-Making For Selecting Multi-Deep Face Recognition Models, Abdulbasit Alazzawi, Qahtan M. Yas, Burhan Albayati May 2025

Retracted: A Group Decision-Making For Selecting Multi-Deep Face Recognition Models, Abdulbasit Alazzawi, Qahtan M. Yas, Burhan Albayati

Iraqi Journal for Computer Science and Mathematics

Deep face recognition is a significant area of biometric authentication that addresses challenges such as low resolution, varying facial expressions, and inconsistent lighting. This paper presents a robust deep-learning approach to tackle these challenges. The study aims to employ multi-criteria decision-making techniques and verify the influence of individual and group expert opinions in decision-making. However, balancing criteria such as accuracy, sensitivity, specificity, precision, and recall remain challenging across different models. To fill this gap, the study utilized a decision-support framework that included the fuzzy analytical hierarchical process to set criteria weights based on expert input and the Technique for Order …

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Ecg-Based Biometric Key Generation Using Principal Component Analysis And Machine Learning, Ahmad Abadleh May 2025

Ecg-Based Biometric Key Generation Using Principal Component Analysis And Machine Learning, Ahmad Abadleh

Iraqi Journal for Computer Science and Mathematics

Biometric authentication techniques are fast becoming imperative methods for secure identifications in a wide range of applications, while most of the traditional systems are easily spoofed or forged. In this paper a new approach of deriving a unique biometric key from an electrocardiogram signal is presented owing to physiological uniqueness of heart activity. In this respect, by focusing on RR intervals extracted from ECG signals, the PCA is applied in order to reduce its dimensionality and then form a compact and distinctive biometric key. Thereafter, a Random Forest classifier was used in evaluating the effectiveness of features, where a high …

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Retracted: Robust Security System: A Novel Facial Recognition Optimization Using Coronavirus-Inspired Algorithm And Machine Learning, Saif Mohanad Kadhim, Johnny Koh Siaw Paw, Yaw Chong Tak, Shahad Thamear Abd Al-Latief May 2025

Retracted: Robust Security System: A Novel Facial Recognition Optimization Using Coronavirus-Inspired Algorithm And Machine Learning, Saif Mohanad Kadhim, Johnny Koh Siaw Paw, Yaw Chong Tak, Shahad Thamear Abd Al-Latief

Iraqi Journal for Computer Science and Mathematics

Facial recognition has become an invaluable and rapidly advancing technology that plays a crucial role in various daily applications. From identity authentication to video surveillance, mobile payment, and even law enforcement and security measures. Despite the remarkable progress, facial recognition is still a dynamic research field and confronts several challenges. One of the main challenges is the high variability in facial images due to factors like facial expressions, lighting conditions, aging, and the presence of accessories. Additionally, the computational complexity and the time concerns surrounding face recognition systems have raised considerations that need to be addressed. This research presents a …

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Retracted: Accurate Electrocardiogram Classification Of Heart Disease Using Deep Learning Network, Hadeel M. Saleh, Sahar Hamad Ahmed, Akeel Sh. Mahmoud May 2025

Retracted: Accurate Electrocardiogram Classification Of Heart Disease Using Deep Learning Network, Hadeel M. Saleh, Sahar Hamad Ahmed, Akeel Sh. Mahmoud

Iraqi Journal for Computer Science and Mathematics

Long short-term memory networks can effectively process complex temporal patterns in electrocardiogram data. These sequential models excel at classifying heart disease from the rich signals captured by electrocardiograms. However, traditional algorithms struggle with the intricate waveforms encoded in each heartbeat. Deeper architectures such as LSTM are better equipped to untangle the subtle variations between healthy sinus rhythms and lethal arrhythmias. In this study, an LSTM model was developed to diagnose disease from the PTB dataset. The network was trained using a fusion of deep learning schemes for sequential data. The model underwent several evaluations, from a confusion matrix mapping predictions …

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Retracted: Intrusion Detection System For Iot Based On Modified Random Forest Algorithm, Omar Z. Akif, Sura Mazin Ali, Ann F. Sabih, Ahmed T. Sadiq, S. K. Subramaniam May 2025

Retracted: Intrusion Detection System For Iot Based On Modified Random Forest Algorithm, Omar Z. Akif, Sura Mazin Ali, Ann F. Sabih, Ahmed T. Sadiq, S. K. Subramaniam

Iraqi Journal for Computer Science and Mathematics

An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used …

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Retracted: Cipher Text To Secure Li-Fi System Using Hybrid Encryption Algorithm, Mohammed M. Ahmed, Satea H. Alnajjar May 2025

Retracted: Cipher Text To Secure Li-Fi System Using Hybrid Encryption Algorithm, Mohammed M. Ahmed, Satea H. Alnajjar

Iraqi Journal for Computer Science and Mathematics

It is important to pay attention to develop our security systems, due to the increase in cyberattacks and the development of their methods and the work to develop quantum computers capable of penetrating the solution of complex equations of encryption algorithms. The need to develop protection methods has emerged in line with the development of hackers to ensure the security and safety of users' data. In this research, work was done on the modern Li-Fi technology based on comparing the values with Kim's model and a distance of more than 13 km was reached in the fresh air. This technology …

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A New Class Of Endo-R.B Module And Its Relationship With Modules, Mohammed Salman Murad, Buthyna Najad Shihab May 2025

A New Class Of Endo-R.B Module And Its Relationship With Modules, Mohammed Salman Murad, Buthyna Najad Shihab

Iraqi Journal for Computer Science and Mathematics

This paper gives a definition of a new class of T-module and T-submodule called an Endo-Restricted Bounded module (submodule) written shortly by Endo-R.B. module (submodule) and present some different approaches to connect this class of module with other types of modules such as: compressible modules, monoform modules, critically compressible modules, retractable modules, and quasi-Dedekind modules. One of the main purpose of this work is to introduce a few new conditions and reveal some properties and corollaries. This paper considered to be another solution or answer for Zelmanowitz’s problem. In fact, an Endo-R.B. T-module plays an important role to this problem …

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Using Predictive Analytics To Reduce Small Business Cost Estimation Error, Diana Solt May 2025

Using Predictive Analytics To Reduce Small Business Cost Estimation Error, Diana Solt

Journal of Applied Packaging Research

Small and medium packaging companies generally employ the use of custom-developed quoting programs to bid goods and services. Custom bid programs (e.g. Excel) are used to capture the company-specific costs of production. The inputs of variable costs, such as machine rate and scrap rate, are critical to get correct; however, companies often rely on educated guesses and industry expertise to quote packaging products to end-users. Due to the guesswork involved there can be a financial difference between the quoted costs and actual costs. This variance is often the cause of significant lost dollars. Price, if not determined correctly, could negatively …

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Design And Optimization Of Low-Loss, High-Gain Metamaterial-Based Log-Periodic Dipole Array Antenna For Full Ka-Band Coverage, Mohamed El Moniar, Ahmed Abd El Hady, Yasser Ismail, Nihal Areed May 2025

Design And Optimization Of Low-Loss, High-Gain Metamaterial-Based Log-Periodic Dipole Array Antenna For Full Ka-Band Coverage, Mohamed El Moniar, Ahmed Abd El Hady, Yasser Ismail, Nihal Areed

Turkish Journal of Electrical Engineering and Computer Sciences

This work describes a microstrip log-periodic dipole array (MLPDA) antenna that uses metamaterials and operates across the whole Ka-band. The suggested MLPDA antenna layout provides a wide bandwidth with fewer dipole elements than traditional MLPDA antennas while maintaining the same resonance frequencies. To reduce size while covering a wide operational spectrum, the antenna design includes bending dipoles as radiating elements, as well as an incomplete ground plane. Furthermore, the proposed MLPDA antenna’s energy loss has been reduced while boosting its signal strength (gain) by inserting a metamaterial-based structure in front of it at a certain distance and on the same …

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Skin Cancer Diagnosis Utilizing Hybrid Discrete Cosine Transform And High-Performance Convolutional Neural Networks, Mohammed M. Abo-Zahhad, Mohammed Abo-Zahhad May 2025

Skin Cancer Diagnosis Utilizing Hybrid Discrete Cosine Transform And High-Performance Convolutional Neural Networks, Mohammed M. Abo-Zahhad, Mohammed Abo-Zahhad

Mansoura Engineering Journal

Detecting skin cancer early and accurately is crucial for successfully treating this potentially fatal disease. Enhancing the accuracy of visual inspection techniques is often necessary to improve clinical decision-making and increase the chance of successful treatment outcomes. In this research, high-performance deep learning (DL) models for automated skin cancer categorization and early skin cancer diagnosis screening are developed and evaluated in conjunction with the discrete cosine transform (DCT). For this purpose, features are extracted from medical images using both techniques. The DCT is used for feature extraction and dimensionality reduction, while deep learning (DL) trains fully connected models for classification …

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Research On Grey-Box Modeling Method Of Digital Twins For Cantilever Structure, Wenjia Zhang, Heming Zhang May 2025

Research On Grey-Box Modeling Method Of Digital Twins For Cantilever Structure, Wenjia Zhang, Heming Zhang

Journal of System Simulation

Abstract: The construction of accurate and highly real-time digital twin models in complex industrial setting presents several challenges. Traditional model construction approaches based only on mechanism or data show certain limitations. Therefore, this study is based on the idea of grey-box modeling, taking the cantilever structure within a boom-type roadheader as the object, and proposes a novel modeling approach that combines the characteristics of the mechanism model and introduces a self-attention mechanism. This method performs grayscale transformation on the original input and splices it with physical features to achieve organic fusion of mechanism information, which not only enhances the expressiveness …

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An Extended Image Features Based Uncalibrated Visual Servoing Method, Shuzhen Zhang, Yukun Cheng, Yangbo Liu, Fusheng Zha May 2025

An Extended Image Features Based Uncalibrated Visual Servoing Method, Shuzhen Zhang, Yukun Cheng, Yangbo Liu, Fusheng Zha

Journal of System Simulation

Abstract: Aiming at the traditional uncalibrated visual servo relying on the estimation of image Jacobi matrix and the coupling of the motion of each degree of freedom of the camera, on the basis of imagebased uncalibrated visual servo, an extended image features based uncalibrated visual servo method is proposed. By analyzing the relationship between image features and camera frames change in the visual servoing process, the visual servoing process in the image space is decomposed into four basic processes: translation, stretching, rotation and scaling; by analyzing the changing of image features in the visual servoing process, extended image features are …

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A Modeling And Simulation Method For Firepower Intelligent Decision-Making Of Directed Energy System Basedon Joint Dqn, Changhong Qu, Junjie Wang, Kun Wang, Qingyong Cui, Jiangyang Chen, Xinpeng Wang May 2025

A Modeling And Simulation Method For Firepower Intelligent Decision-Making Of Directed Energy System Basedon Joint Dqn, Changhong Qu, Junjie Wang, Kun Wang, Qingyong Cui, Jiangyang Chen, Xinpeng Wang

Journal of System Simulation

Abstract: In order to solve the problem of dynamically addressing firepower intelligent decision-making in anti-UAV cluster combat using a directed energy system, a deep reinforcement learning model is established. Based on the high multi-agent state and action space dimensions of this model, a modeling and simulation method of firepower intelligent decision-making of directed energy system based on joint deep Q network (DQN) is proposed. The state space is constructed from the state of directed energy system, UAV cluster and the directed energy system deployment area. The joint mechanism is used to share the state information of each equipment and the …

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Research On Modeling, Optimization And Application Of Aeroengine Oil System, Shijie Huang, Zhensheng Zhang, Jing Cai, Rui Zhang May 2025

Research On Modeling, Optimization And Application Of Aeroengine Oil System, Shijie Huang, Zhensheng Zhang, Jing Cai, Rui Zhang

Journal of System Simulation

Abstract: In response to the high cost and long cycle of using experimental methods for monitoring, diagnosing, and predicting lubricating oil system, a simulation model for oil system is constructed and optimized, and the application of the model in health management of oil system is proposed. Based on the physical characteristics of the components in the oil system, subsystem models for ventilation, oil supply, thermodynamics, and oil return are constructed using a certain engine oil system as an example, and the whole oil system model is constructed and solved iteratively. The model is optimized by combining particle swarm optimization and …

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Ultimate Limit State Reliability-Based Approach Life Prediction Of An Existing Frame Structure Under Seismic Hazard In Indonesia, Wira Herucakra, Luh Putri Adnyani May 2025

Ultimate Limit State Reliability-Based Approach Life Prediction Of An Existing Frame Structure Under Seismic Hazard In Indonesia, Wira Herucakra, Luh Putri Adnyani

Journal of Materials Exploration and Findings

Life assessment integrated with Structural Integrity Management (SIM) has been implemented in the oil and gas industry for the past decade to maintain the integrity and safety of an in-service structure used to support hydrocarbon exploration, production, and processing activity. Current structural life assessment, as ruled by the American Petroleum Institute (API), uses a fatigue-based approach for offshore structures subjected to wave loading. As the general principle of SIM is not limited to offshore structures, this study offers an alternative life assessment method for onshore structures, especially steel frame structures subjected to earthquake loads. Reliability analysis, combined with the effect …

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Adaptive Multi-Scale Feature Pyramid Network For Occlusion Pedestrian Detection, Huaping Zhou, Tao Wu, Kelei Sun May 2025

Adaptive Multi-Scale Feature Pyramid Network For Occlusion Pedestrian Detection, Huaping Zhou, Tao Wu, Kelei Sun

Journal of System Simulation

Abstract: To address the issue of current pedestrian detectors, which struggle to extract complete features in occlusion-heavy environments and consequently have low detection accuracy. A novel adaptive multiscale feature pyramid network is proposed. A multi-scale feature enhancement module (MFEM) is developed. It captures the visible area of pedestrians at different scales through a multi-branch network with different receptive fields. An AFM (adaptive fusion module) is proposed. It calculates the importance of different pixels by optimizing the mean variance at the spatial and feature levels. It enhances the texture and semantic features of pedestrians and fuses the features of different scales …

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Design And Realization Of Integrated Energy System Dynamic Stability Simulation And Steady-State Simulation System, Guixiong He, Xiaoqiang Jia, Shufeng Dong, Yonglu Han, Yonghua Chen, Yiming Zheng May 2025

Design And Realization Of Integrated Energy System Dynamic Stability Simulation And Steady-State Simulation System, Guixiong He, Xiaoqiang Jia, Shufeng Dong, Yonglu Han, Yonghua Chen, Yiming Zheng

Journal of System Simulation

Abstract: Aiming for“carbon peak”and“carbon neutrality”, the energy sector is undergoing significant reform. To address energy flow and planning optimization in integrated energy systems, a comprehensive simulation platform is developed. This platform combines physical and digital simulations with real-world validation and is modular in design, It includes an integrated energy model library, energy flow optimization, modeling management, real-time simulation, and energy monitoring. The platform enhances system safety, stability, and economic efficiency, While also improving planning and energy management. The paper analyzes the platform′s functional and physical architecture, introduces key modules, establishes dynamic and steady-state model libraries, and optimizes energy flow using …

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Research On Modeling Methods For Industrial Core Capability Architecture Based On The Dodaf Framework, Xiaoqiang Dou, Yan Liu, Zhilong Zhao, Chao Fu, Fulin Zhang, Shanshan Zou May 2025

Research On Modeling Methods For Industrial Core Capability Architecture Based On The Dodaf Framework, Xiaoqiang Dou, Yan Liu, Zhilong Zhao, Chao Fu, Fulin Zhang, Shanshan Zou

Journal of System Simulation

Abstract: Against the backdrop of the industrial sector actively pursuing digital capability building, this paper describes the necessity and current status of architecture theory methods guiding industrial core capability construction. It proposes the conceptual connotation of industrial core capability architecture and four key modeling elements. Based on DoDAF, it conducts the overall design of industrial core capability architecture. By integrating systems engineering principles, it establishes a five-stage process model for capability-building activities, embedding critical elements such as capability/business/ application/data/technology architecture viewpoint, and explains data model design, and logical compositions of various viewpoints. By selecting a capability building project in a …

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Survey On Large Language Agent Technologies For Intelligent Game Theoretic Decision-Making, Xueqiang Gu, Junren Luo, Yanzhong Zhou, Wanpeng Zhang May 2025

Survey On Large Language Agent Technologies For Intelligent Game Theoretic Decision-Making, Xueqiang Gu, Junren Luo, Yanzhong Zhou, Wanpeng Zhang

Journal of System Simulation

Abstract: The development of artificial intelligence technology has greatly promoted the transformation of the solving paradigm of intelligent game decision problems. From optimal solution, equilibrium solution to adaptive variable solution, how to build an intelligent game adaptive decision agent based on generative large model is full of challenges. The force distribution and multi-entity coordination in the game strong confrontation environment are the core issues in the study of troop deployment and operational coordination. Based on the methods of strategy reinforcement learning, strategy game tree search and strategy preference voting based on skill, ranking and preference meta-game model construction, a large …

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Modeling And Simulation Of Intelligent Underwater Acoustic Countermeasure Based On The Matrix Game, Huijin Zhao, Yu Chen May 2025

Modeling And Simulation Of Intelligent Underwater Acoustic Countermeasure Based On The Matrix Game, Huijin Zhao, Yu Chen

Journal of System Simulation

Abstract: Due to the great threat of torpedo against surface warships, an efficient hydroacoustic countermeasure system must output real-time strategies to accommodate varied antagonizing scenarios. Aiming at the decision-making problem in the anti-torpedo hydroacoustic countermeasure cases, an intelligent adversarial strategy is proposed based on the game theory. By discretizing the strategy space of both sides, a matrix game model is established where the payoff is characterised by the capture probability of attacking torpedo. An improved simplex algorithm is then developed to get the mixedstrategy Nash equilibrium of the game model, which can be used to obtain preferred avoidance strategies to …

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Optimal Scheduling Of Virtual Power Plant With Coupled Operation Of Ccs-P2g Considering Wind And Photovoltaic Uncertainty, Xurong Jin, Jiang Yin, Guohua Yang, Wei Li, Guobin Wang, Lele Wang, Na Yang, Xuenian Zhou May 2025

Optimal Scheduling Of Virtual Power Plant With Coupled Operation Of Ccs-P2g Considering Wind And Photovoltaic Uncertainty, Xurong Jin, Jiang Yin, Guohua Yang, Wei Li, Guobin Wang, Lele Wang, Na Yang, Xuenian Zhou

Journal of System Simulation

Abstract: In order to solve the problem that the uncertainty of wind power and photovoltaic power generation output easily affects the scheduling of virtual power plant, a new optimal scheduling model of virtual power plant is proposed based on information gap decision theory (IGDT) . In order to reduce the carbon emission of the system, carbon capture and storage (CCS) is installed on the combined heat and power units; in order to improve the utilization rate of renewable energy, the power to gas (P2G) device is introduced into the system, and the operation mode of CCS-P2G coupling is proposed; based …

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