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Articles 961 - 990 of 17307
Full-Text Articles in Engineering
Contact Graphs In Fuzzy And Neutrosophic Graphs, Takaaki Fujita
Contact Graphs In Fuzzy And Neutrosophic Graphs, Takaaki Fujita
Neutrosophic Systems with Applications
Graph Theory is a branch of mathematics dedicated to studying graphs, which depict relationships between objects through vertices and edges. A significant focus in this field is the study of contact graphs, where vertices correspond to sets, and edges represent intersections between those sets. To better model uncertainties in real-world situations, several graph types---such as fuzzy, neutrosophic, and Plithogenic graphs---have been developed. This paper investigates the concept of contact graphs within these frameworks, offering insights into their behavior under various uncertain conditions.
Revisiting Bipolar Neutrosophic Graph And Interval-Valued Neutrosophic Graph, Takaaki Fujita
Revisiting Bipolar Neutrosophic Graph And Interval-Valued Neutrosophic Graph, Takaaki Fujita
Neutrosophic Systems with Applications
Graph theory explores networks composed of nodes (vertices) and their connections (edges). A graph class is a collection of graphs that share common structural properties, defined by specific rules or constraints. This paper examines various models of uncertain graphs, including Fuzzy, Intuitionistic Fuzzy , Neutrosophic, Turiyam Neutrosophic, and Plithogenic Graphs. In particular, this study focuses on Bipolar Graphs and Interval-valued Graphs, analyzing them within the frameworks of Fuzzy, Neutrosophic, Turiyam Neutrosophic, and Plithogenic Graphs.
Appraisal Of Uncertainty-Driven Financial Performance: Bringing Multi-Criteria Decision Making Techniques With Neutrosophic Theory, Mona Mohamed, Nurhan Alaa, Eman Sayed
Appraisal Of Uncertainty-Driven Financial Performance: Bringing Multi-Criteria Decision Making Techniques With Neutrosophic Theory, Mona Mohamed, Nurhan Alaa, Eman Sayed
Neutrosophic Systems with Applications
Evaluating financial performance is essential yet challenging due to various factors, including ambiguity, insufficient information, and conflicting evaluation criteria. Conventional Multi-Criteria Decision-Making (MCDM) techniques often struggle to manage these complexities effectively. To address these limitations and enhance financial performance assessments, this research proposes an innovative approach integrating Single-Valued Neutrosophic Sets (SVNS) with established MCDM methodologies. SVNS uniquely manages uncertainty by concurrently quantifying degrees of truth, indeterminacy, and falsity within financial data. This research specifically employs entropy-based weighting methods integrated with Additive Ratio Assessment (ARAS) and Multi-Objective Optimization by Ratio Analysis (MOORA) methodologies in the SVNS environment to systematically rank enterprises …
An Approach To Model Uncertainty In Fluid Behaviour With Navier-Stokes Equations In Neutrosophic Environment, Muhammad Saeed, Attia Hameed, Neha Andaleeb Khalid, Muhammad Salman Habib
An Approach To Model Uncertainty In Fluid Behaviour With Navier-Stokes Equations In Neutrosophic Environment, Muhammad Saeed, Attia Hameed, Neha Andaleeb Khalid, Muhammad Salman Habib
Neutrosophic Systems with Applications
The complex discipline of fluid dynamics examines the behavior of fluids and their interactions with adjacent objects. The Navier-Stokes equations are very important for explaining how fluids move, but they are not linear and often give answers that depend on the starting point and the boundaries. Modeling fluid behavior is challenging due to the inherently chaotic and unpredictable character of fluid dynamics. To deal with unknown or uncertain values in this research, we used neutrosophic logic to look at the Navier-Stokes equations in a new way. Neosophic logic permits the existence of values that are partially true and partially false; …
Revisiting Bipolar Neutrosophic Graph And Interval-Valued Neutrosophic Graph, Takaaki Fujita
Revisiting Bipolar Neutrosophic Graph And Interval-Valued Neutrosophic Graph, Takaaki Fujita
Neutrosophic Systems with Applications
Graph theory explores networks composed of nodes (vertices) and their connections (edges). A graph class is a collection of graphs that share common structural properties, defined by specific rules or constraints. This paper examines various models of uncertain graphs, including Fuzzy, Intuitionistic Fuzzy , Neutrosophic, Turiyam Neutrosophic, and Plithogenic Graphs. In particular, this study focuses on Bipolar Graphs and Interval-valued Graphs, analyzing them within the frameworks of Fuzzy, Neutrosophic, Turiyam Neutrosophic, and Plithogenic Graphs.
Leveraging Hypersoft Set To Optimize Livestock In The Era Of Unmanned Aerial Vehicles, Alaa Salem, Mona Mohamed, Nebojsa Bacanin, Mohamed Abouhawwash
Leveraging Hypersoft Set To Optimize Livestock In The Era Of Unmanned Aerial Vehicles, Alaa Salem, Mona Mohamed, Nebojsa Bacanin, Mohamed Abouhawwash
Neutrosophic Systems with Applications
Due to urbanization and industrialization, rapid global change and the potential loss of arable land, agricultural output must rise in production levels and harvest, distribute, and use resources more efficiently. It is believed that using technology on livestock would help meet the expanding population's demand for food. Internet of Things (IoT) and Unmanned Aerial Vehicle (UAV) integration in conventional farming has transformed operations, providing farmers with greater productivity, improved decision-making, and sustainability. We assume that there are enough UAVs to cover the entire pasture, and our goal is to identify the best UAVs. Accordingly, determining the best type of UAVs …
Contact Graphs In Fuzzy And Neutrosophic Graphs, Takaaki Fujita
Contact Graphs In Fuzzy And Neutrosophic Graphs, Takaaki Fujita
Neutrosophic Systems with Applications
Graph Theory is a branch of mathematics dedicated to studying graphs, which depict relationships between objects through vertices and edges. A significant focus in this field is the study of contact graphs, where vertices correspond to sets, and edges represent intersections between those sets. To better model uncertainties in real-world situations, several graph types---such as fuzzy, neutrosophic, and Plithogenic graphs---have been developed. This paper investigates the concept of contact graphs within these frameworks, offering insights into their behavior under various uncertain conditions.
Expanding The Horizons Of Nonagonal Neutrosophic Numbers As A Versatile Framework For Decision-Making And Scientific Applications In Covid-19, Muhammad Naveed Jafar, Kainat Muniba, Hamiden Abd El-Wahed Khalifa, Fahd Jarad
Expanding The Horizons Of Nonagonal Neutrosophic Numbers As A Versatile Framework For Decision-Making And Scientific Applications In Covid-19, Muhammad Naveed Jafar, Kainat Muniba, Hamiden Abd El-Wahed Khalifa, Fahd Jarad
Neutrosophic Systems with Applications
In this article, the concept of nonagonal neutrosophic numbers has been introducing in the disjunctive frame of reference. We also proposed the dependency and independency of membership function in regards to nonagonal neutrosophic number. We also introduce a new score function and its computation also formulated in a distinct rational viewpoint. We developed the concept of weighted arithmetic averaging operator and weighted geometric averaging operator for nonagonal neutrosophic numbers. It will open new doors for MCDM and develop the concept with new approaches. Additionally, we analyze the effect of COVID-19 for different ages.
Assessing The Sustainable Blockchain-Metaverse-Iot Platform In The Healthcare Industry: An Intelligent Decision Support Model, Ibrahim M. Hezam, Ahmed M. Ali, Ibrahim A. Hameed, Karam Sallam, Mohamed Abdel-Basset
Assessing The Sustainable Blockchain-Metaverse-Iot Platform In The Healthcare Industry: An Intelligent Decision Support Model, Ibrahim M. Hezam, Ahmed M. Ali, Ibrahim A. Hameed, Karam Sallam, Mohamed Abdel-Basset
Neutrosophic Systems with Applications
Healthcare services must fulfill patients' desires for secure data sharing and high accessibility. Blockchain technology, through blockchain platforms (BPs), can overcome healthcare challenges. This study develops a decision-making methodology for selecting the best BP, by integrating blockchain with IoT and Metaverse, the proposed approach ensures data integrity, quality, privacy and security, secure data sharing, and interoperability. The decision-making methodology uses the multi-criteria decision-making (MCDM) methodology to handle conflicting criteria. Two MCDM methods are used in this study: CRiteria Importance Through Intercriteria Correlation (CRITIC) for weight computation, and Ranking of Alternatives with Weights of Criterion (RAWEC) for alternative ranking. To deal …
Appraisal Of Uncertainty-Driven Financial Performance: Bringing Multi-Criteria Decision Making Techniques With Neutrosophic Theory, Mona Mohamed, Nurhan Alaa, Eman Sayed
Appraisal Of Uncertainty-Driven Financial Performance: Bringing Multi-Criteria Decision Making Techniques With Neutrosophic Theory, Mona Mohamed, Nurhan Alaa, Eman Sayed
Neutrosophic Systems with Applications
Evaluating financial performance is essential yet challenging due to various factors, including ambiguity, insufficient information, and conflicting evaluation criteria. Conventional Multi-Criteria Decision-Making (MCDM) techniques often struggle to manage these complexities effectively. To address these limitations and enhance financial performance assessments, this research proposes an innovative approach integrating Single-Valued Neutrosophic Sets (SVNS) with established MCDM methodologies. SVNS uniquely manages uncertainty by concurrently quantifying degrees of truth, indeterminacy, and falsity within financial data. This research specifically employs entropy-based weighting methods integrated with Additive Ratio Assessment (ARAS) and Multi-Objective Optimization by Ratio Analysis (MOORA) methodologies in the SVNS environment to systematically rank enterprises …
A Novel Neutrosophic Decision-Making Approach For Optimizing Metaverse Headphone Design: Balancing Technical Performance And User Emotional Needs, Mai Mohamed, Amira Salam, Karam Sallam, Bilal Arain
A Novel Neutrosophic Decision-Making Approach For Optimizing Metaverse Headphone Design: Balancing Technical Performance And User Emotional Needs, Mai Mohamed, Amira Salam, Karam Sallam, Bilal Arain
Neutrosophic Systems with Applications
The concept of the metaverse, which combines various technologies to create a wide range of virtual experiences, has gained significant popularity in recent years. To fully engage in these metaverse environments, users rely on access devices such as virtual reality (VR) headsets and smartphones for augmented reality (AR). These devices must be lightweight, compact, and user-friendly to ensure comfort and enhance customer satisfaction. There is a growing focus on innovating and designing products that not only meet technical requirements but also address the emotional needs of users, ultimately improving the overall experience. Selecting the ideal design for Metaverse headphones is …
A Comprehensive Intelligent Traffic Monitoring System Based On A Novel Integration Of Neutrosophic Multi-Criteria Decision-Making Techniques, Mai Mohamed, Amira Salam, Rana Muhammad Zulqarnain, Muhammad Gulistan
A Comprehensive Intelligent Traffic Monitoring System Based On A Novel Integration Of Neutrosophic Multi-Criteria Decision-Making Techniques, Mai Mohamed, Amira Salam, Rana Muhammad Zulqarnain, Muhammad Gulistan
Neutrosophic Systems with Applications
With the spread of road accidents and traffic congestion that costs countries and governments a lot of money in addition to the loss of human lives, and since traditional methods of monitoring traffic have not been as effective as desired, attention has been drawn to the search for more effective solutions to the problem of monitoring and regulating traffic. With the spread of technology and the Internet of Things, UAVs have emerged as a promising tool for monitoring traffic, as they can fly for a sufficient period and operate in difficult climatic conditions, in addition to their ability to monitor …
Nash Equilibrium Solutions For Continuous Static Games Under Neutrosophic Environment, M. G. Brikaa
Nash Equilibrium Solutions For Continuous Static Games Under Neutrosophic Environment, M. G. Brikaa
Neutrosophic Systems with Applications
Neutrosophic set theory plays an important role in dealing with the impreciseness and inconsistency in data encountered in solving real life problems. This paper presents a novel approach to solving a new class of continuous static games within a neutrosophic framework. In the proposed methodology, the neutrosophic continuous static games are redefined into two separate crisp problems: the lower problem and the upper problem. The study further establishes the necessary conditions for determining equilibrium strategies in neutrosophic continuous static games. To demonstrate its effectiveness and practical applicability, the proposed method is validated through a numerical example.
Digital Thread: Bridging Macro–Micro Services In System-Of-Systems, Joshit Mohanty
Digital Thread: Bridging Macro–Micro Services In System-Of-Systems, Joshit Mohanty
Graduate Student Government Association Research Conference
Organizations and industries increasingly rely on distributed services in decentralized environments—ranging from large-scale, system-of-system architectures to fine-grained, agent-based microservices. While this distributed paradigm offers flexibility and innovation, it presents critical challenges such as interoperability gaps, inconsistent data formats, and a lack of holistic oversight. Traditional integration approaches, including ad-hoc middleware or enterprise service buses, tend to solve these issues reactively. As a result, technical debt accumulates, stakeholder misalignments persist, and scaling to new demands becomes complex.
This research proposes digital thread (DT) as the unifying framework to create an authoritative source of truth: a continuous flow of information across the …
Meta-Clustering For Specialized Language Models: Enhancing Contextual Adaptation And Mitigating Hallucinations In Diverse Healthcare Environments, Joshit Mohanty, Vaishali Vaishali, Sandeep Kumar Nayak, Sumit Lahiri
Meta-Clustering For Specialized Language Models: Enhancing Contextual Adaptation And Mitigating Hallucinations In Diverse Healthcare Environments, Joshit Mohanty, Vaishali Vaishali, Sandeep Kumar Nayak, Sumit Lahiri
Graduate Student Government Association Research Conference
Large Language Models (LLMs) have significantly advanced conversational AI by enabling dialogic information-seeking and task execution across diverse domains. However, their extensive parameters and broad domain scope lead to “data hallucinations.” These shortcomings are particularly evident in dynamic and diverse environments like India’s healthcare sector, where myriad languages, regional practices, and cultural nuances demand specialized, localized expertise rather than one-size-fits-all generalist models. This paper introduces a meta-clustering framework that integrates Distilled Language Models (DLMs) and Small/Specialized Language Models (SLMs) with meta-learning principles to address these limitations. By drawing on evidence from works such as MedHalu and Med-HALT, the framework seeks …
Tamos: Task-Aware Multi-Agent Orchestrator System, Joshit Mohanty, Sandeep Kumar Nayak, Sumit Lahiri
Tamos: Task-Aware Multi-Agent Orchestrator System, Joshit Mohanty, Sandeep Kumar Nayak, Sumit Lahiri
Graduate Student Government Association Research Conference
Large language models (LLMs) are increasingly at the core of multi-agent systems (MAS). However, the high resource demand, error propagation, and lack of adaptive evaluation mechanisms pose significant challenges in deploying these agentic solutions at scale. To address these concerns, this research proposes a Task-Aware Multi-Agent Orchestrator System designed to refine the agentic framework, categorizing tasks autonomously, assigning specialized evaluation datasets, and balancing token usage against functional effectiveness. This approach underscores robust data management, including AsyncHow, Mosaic AI, and Synthetic Preference Optimization (PO) corpora. Each dataset targets specific dimensions of agent performance, such as dynamic task decomposition and tool integration …
Graphtreemed: A Hybrid Graph-Tree Rag Architecture For Mission-Critical Medical Applications, Joshit Mohanty, Sandeep Kumar Nayak, Sumit Lahiri
Graphtreemed: A Hybrid Graph-Tree Rag Architecture For Mission-Critical Medical Applications, Joshit Mohanty, Sandeep Kumar Nayak, Sumit Lahiri
Graduate Student Government Association Research Conference
Studies within engineering management indicate that decision-making is often based on the cognitive processing of grouped and pictographic information clusters entangled with high-level pattern recognition. Similarly, graph-based retrieval-augmented generation (RAG) architectures substantially improve diagnostic accuracy and interpretability, while tree-structured systems reduce critical misses through hierarchical reasoning. However, existing solutions often lack a unified framework that seamlessly integrates these two paradigms to address the multifaceted demands of mission-critical healthcare settings. This proposal introduces GraphTreeMed, a novel hybrid RAG architecture designed to harness the complementary strengths of graph-based and tree-based retrieval mechanisms, thereby advancing the safety and efficacy of clinical decision support …
Survey On Intelligent Planning Methods From Large Language Models Perspective, Yanzhong Zhou, Junren Luo, Xueqiang Gu, Wanpeng Zhang
Survey On Intelligent Planning Methods From Large Language Models Perspective, Yanzhong Zhou, Junren Luo, Xueqiang Gu, Wanpeng Zhang
Journal of System Simulation
Abstract: Starting from the perspective of large language models, this paper gives an overview of the definition and development of intelligent planning, and briefly introduces the traditional methods of intelligent planning; based on the close relationship between large language model intelligent agents and intelligent planning, introduces the architecture of large language models and typical large model intelligent agents; focusing on the intelligent planning for large language models, combs through the learning of planning languages, chain of thought, feedback optimization, and process automation; combining with the current challenges and difficulties, introduces the outlook of cutting-edge research on intelligent planning with large …
Simulation Environment Construction Of Track Segment Association And Algorithm Performance Evaluation, Dian Ding, Guangfen Wei, Zheng Cao, Shaohui Wen
Simulation Environment Construction Of Track Segment Association And Algorithm Performance Evaluation, Dian Ding, Guangfen Wei, Zheng Cao, Shaohui Wen
Journal of System Simulation
Abstract: In order to study the applicability of Track Segment Association (TSA) algorithms in actual radar working environment , a TSA simulation environment which can simulate the real movement of the target is constructed. By constructing a rich set of target motion sets, the state switching process of target motion is described based on Markov state transition matrix, and the density is flexibly controlled through track translation. The simulation results show that this environment can evaluate the performance of the current classical TSA algorithms. The evaluation results provide a good reference for the practical engineering application of interrupted track association.
Research On The Resilience Of Integrated Urban Passenger Transport Network In Urban Agglomerations Considering The Intra-Urban Service Network, Shida Nie, Chengbing Li, Bowei He, Xintao Li
Research On The Resilience Of Integrated Urban Passenger Transport Network In Urban Agglomerations Considering The Intra-Urban Service Network, Shida Nie, Chengbing Li, Bowei He, Xintao Li
Journal of System Simulation
Abstract: In order to solve the problem of insufficient comprehensiveness and refinement of the urban agglomeration passenger transport network model, Space L modelling method in complex network theory is adopted to construct a comprehensive urban passenger transport network model considering the urban internal service network. A comprehensive urban passenger transport network composed of intercity networks and intra-city service networks is built, and time-dependent edge weights in the network is considered. A time-weighted network efficiency model is proposed to evaluate the network resilience. The results show that under a random attack strategy, the relative time efficiency of the network fluctuates less, …
A Multi-Robot Collaborative Path Planning Algorithm With Chain Working Mode, Zhigang He, Dayan Li, Niya Wang, Jianlin Mao, Ning Wang
A Multi-Robot Collaborative Path Planning Algorithm With Chain Working Mode, Zhigang He, Dayan Li, Niya Wang, Jianlin Mao, Ning Wang
Journal of System Simulation
Abstract: In order to solve the problem that the traditional MAPF algorithms can lead to a large number of repeated paths and thus non-essential energy loss in application scenarios where multiple robots have a common goal point, a multi-robot chain work mode with a tractor is proposed, which divides the robots with common target points into subgroups for multi robot collaborative path planning, and a collaborative dynamic priority SIPP with tractor (Co-DPtSIPP) algorithm is given. The polygonal Fermat point principle and other methods are used to obtain the serial connection areas of each collaborative group robot; considering the sequence of …
Traffic Signal Detection Based On Improved Yolov7, Lanyue Zheng, Yujie Zhang
Traffic Signal Detection Based On Improved Yolov7, Lanyue Zheng, Yujie Zhang
Journal of System Simulation
Abstract: An improved YOLOv7 is proposed to address the problem of low recognition accuracy in general object detection algorithms for traffic signal detection. The algorithm removes the 20×20 detection scale and adds a 160×160 detection scale to increase shallow features while making the model lightweight. It combines the bi-level routing attention (BRA) proposed in BiFormer with axial attention, and innovatively proposes axially-guided BRA (ABRA). This module is specifically designed for the characteristics of traffic signal positions. To address the issue of object size sensitivity to the IoU metric, the normalized wasserstein distance (NWD) measurement is introduced to improve object location …
Research On Dual-Layer Path Planning Method For Lunar Rover Based On Slip Prediction, Zhang Xingyu, Baolei Wu, Jun Wang, Miaoying Hong, Jiahui Wang, Yongqiang Qi
Research On Dual-Layer Path Planning Method For Lunar Rover Based On Slip Prediction, Zhang Xingyu, Baolei Wu, Jun Wang, Miaoying Hong, Jiahui Wang, Yongqiang Qi
Journal of System Simulation
Abstract: In response to the challenges faced by lunar rovers in the process of path planning, such as safe obstacle avoidance and target deviation caused by complex terrain, a dual-layer path planning based on slip prediction is proposed. In this approach, flat terrain is adaptively selected to reduce the wheel slip of the lunar rover. The overall complexity of the terrain is calculated using digital elevation information, and a Q-learning algorithm with a three-level reward mechanism is designed to navigate around highslip areas, achieving global path planning. A depth camera is used to perceive obstacles, a dynamic window method based …
Design Of Distributed Multi-Functional Integrated Signal-Level Confrontation Simulation System In Local Area, Weiqian Li, Tianyu Yang, Zongyang Li, Jianjun Chen
Design Of Distributed Multi-Functional Integrated Signal-Level Confrontation Simulation System In Local Area, Weiqian Li, Tianyu Yang, Zongyang Li, Jianjun Chen
Journal of System Simulation
Abstract: In order to study the resources management and self-organized collaborative application method of multiple multi-functional integrated electronic equipment in the region, we build a signal-level digital simulation system that supports multiple distributed multi-functional integrated electronic equipment within a region to carry out cooperation or confrontation. A joint time advancing mechanism named "variable-step time advancing method based on frame scheduling" and "independent event driven time advancing method " is proposed. It can not only ensure the integrity of each frame of radar simulation data for each equipment, but also enable multiple equipment in the simulation system to advance simultaneously and …
Uav Path Planning Based On Improved Deep Deterministic Policy Gradients, Sen Zhang, Qiangqiang Dai
Uav Path Planning Based On Improved Deep Deterministic Policy Gradients, Sen Zhang, Qiangqiang Dai
Journal of System Simulation
Abstract: Aiming at the problems of poor convergence and invalid exploration when UAVs perform path planning in complex environments, an improved deep deterministic policy gradient(DDPG) algorithm is proposed. Using a dual experience pooling mechanism to store success and failure experiences separately, the algorithm is able to use the success experience to strengthen the strategy optimization and learn from the failure experience to avoid the wrong path; an APF method is introduced to add a bootstrap term to the planning, which is combined with the exploration of noisy actions in a randomized sampling process to dynamically integrate the selected actions; multi-objective …
Optimization Of Vehicle Routing For Cross-Infection Risk In The Epidemic, Xiaodong Shi, Yongcheng Guo, Mingqi Ma, Jiarui Pan
Optimization Of Vehicle Routing For Cross-Infection Risk In The Epidemic, Xiaodong Shi, Yongcheng Guo, Mingqi Ma, Jiarui Pan
Journal of System Simulation
Abstract: In view of the safety risks associated with logistics distribution route optimization during public health emergencies, this paper investigates the vehicle routing problem by incorporating the risk of cross-infection, integrates the cross-infection risk caused by logistics activities in the epidemic area into the logistics distribution model, and establishes a logistics vehicle distribution model with the goal of cross-infection risk and cost. An improved genetic algorithm is designed for model optimization and solution. Based on the integration of chaos initialization population and adaptive crossover and mutation operations, a neighbor exclusion operator is further proposed to enhance the global search ability …
Remote Sensing Small Object Detection Based On Cross-Stage Two-Branch Feature Aggregation, Jie Li, Yang Liu, Liang Li, Bengan Su, Jialong Wei, Guangda Zhou, Yanmin Shi, Zhen Zhao
Remote Sensing Small Object Detection Based On Cross-Stage Two-Branch Feature Aggregation, Jie Li, Yang Liu, Liang Li, Bengan Su, Jialong Wei, Guangda Zhou, Yanmin Shi, Zhen Zhao
Journal of System Simulation
Abstract: Aiming at YOLOv8's leakage and false detection problems caused by target scale difference and complex background in remote sensing small target detection, this paper proposes a remote sensing image small target detection method based on cross-stage two-branch feature aggregation. The global shared weights in the convolution operator and the context-aware weights of specific tokens in the attention are fused to obtain high-frequency local information and low-frequency global information; the global remote dependencies are captured using a lightweight MLP, and the parallel cross-stage learnable vision center mechanism is designed to capture the information of the local corner regions of the …
A Radar Countermeasure Modeling Method Incorporating Cognitive Bias, Rui Wang, Xiangyang Li, Dong Wang, Hongguang Ma, Zhili Zhang
A Radar Countermeasure Modeling Method Incorporating Cognitive Bias, Rui Wang, Xiangyang Li, Dong Wang, Hongguang Ma, Zhili Zhang
Journal of System Simulation
Abstract: Cognitive bias, stemming from electronic measurement error and variability in human perception, exists in cognitive electronic warfare and affects the outcomes of conflicts. In this paper, the dynamic game approach is employed to develop a model for cognitive bias induced by incomplete information and measurement errors in cognitive radar countermeasures. The payoffs for both parties are calculated using the radar's anti-jamming strategy matrix A and the jammer's jamming strategy matrix B. With perfect Bayesian equilibrium, a dynamic radar countermeasure model is established, and the impact of cognitive bias is analyzed. Drawing inspiration from the cognitive bias analysis method used …
Digital Twin Framework For The Generation And Optimization Of Security Policies For Tsn Industrial Control Systems, Huimai Zhang, Xiaoya Hu, Chunjie Zhou
Digital Twin Framework For The Generation And Optimization Of Security Policies For Tsn Industrial Control Systems, Huimai Zhang, Xiaoya Hu, Chunjie Zhou
Journal of System Simulation
Abstract: The characteristic of multi-service flow integration in TSN industrial control systems makes it very difficult to establish an accurate mathematical model. In order to ensure the coordination between the security policy and the real-time operation of the system, a four-layer double-closed-loop digital twin framework of "physical layer-data layer-twin layer-service layer" serving the generation and optimization of security policies is proposed. The optimal security policy generation is achieved through the internal closed loop composed of iterative optimization between the initial security policy generation at the service layer and the deployment verification at the twin layer. The deterministic communication process between …
A Transfer Learning-Based Hybrid Model For Pm2.5 Concentration Prediction, Xinbiao Lu, Chunlin Ye, Yisen Chen, Wen Wu, Yudan Chen
A Transfer Learning-Based Hybrid Model For Pm2.5 Concentration Prediction, Xinbiao Lu, Chunlin Ye, Yisen Chen, Wen Wu, Yudan Chen
Journal of System Simulation
Abstract: In order to solve the problems of increased computational cost due to irrelevant features and decreased prediction accuracy due to the difference in probability distribution caused by the change of data distribution over time in PM2.5 concentration prediction, this paper constructs a hybrid deep learning model TraTCN-LSTM-BiGRU based on migration learning. The meteorological factors related to PM2.5 concentration are selected as the model input using the mean-value heat map algorithm features; the source domain data and target domain data are divided by KL scatter and an adaptive layer is introduced into the model to achieve inter-domain distribution adaptation; the …