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Articles 12811 - 12840 of 63014
Full-Text Articles in Computer Sciences
Distributed Spatial Data Sharing: A New Era In Sharing Spatial Data, Majid Hojati
Distributed Spatial Data Sharing: A New Era In Sharing Spatial Data, Majid Hojati
Theses and Dissertations (Comprehensive)
The advancements in information and communications technology, including the widespread adoption of GPS-based sensors, improvements in computational data processing, and satellite imagery, have resulted in new data sources, stakeholders, and methods of producing, using, and sharing spatial data. Daily, vast amounts of data are produced by individuals interacting with digital content and through automated and semi-automated sensors deployed across the environment. A growing portion of this information contains geographic information directly or indirectly embedded within it. The widespread use of automated smart sensors and an increased variety of georeferenced media resulted in new individual data collectors. This raises a new …
Using Materialized Views For Answering Graph Pattern Queries, Michael Lan
Using Materialized Views For Answering Graph Pattern Queries, Michael Lan
Dissertations
Discovering patterns in graphs by evaluating graph pattern queries involving direct (edge-to-edge mapping) and reachability (edge-to-path mapping) relationships under homomorphisms on data graphs has been extensively studied. Previous studies have aimed to reduce the evaluation time of graph pattern queries due to the potentially numerous matches on large data graphs.
In this work, the concept of the summary graph is developed to improve the evaluation of tree pattern queries and graph pattern queries. The summary graph first filters out candidate matches which violate certain reachability constraints, and then finds local matches of query edges. This reduces redundancy in the representation …
Android Security: Analysis And Applications, Raina Samuel
Android Security: Analysis And Applications, Raina Samuel
Dissertations
The Android mobile system is home to millions of apps that offer a wide range of functionalities. Users rely on Android apps in various facets of daily life, including critical, e.g., medical, settings. Generally, users trust that apps perform their stated purpose safely and accurately. However, despite the platform’s efforts to maintain a safe environment, apps routinely manage to evade scrutiny. This dissertation analyzes Android app behavior and has revealed several weakness: lapses in device authentication schemes, deceptive practices such as apps covering their traces, as well as behavioral and descriptive inaccuracies in medical apps. Examining a large corpus of …
Development Of Web-Based Project Tender Documents Application Using Extreme Programming Methods, Mustari Lamada, Aminuddin Bakry, Aulyah Zakilah Ifani, Khaerunnisa Khaerunnisa
Development Of Web-Based Project Tender Documents Application Using Extreme Programming Methods, Mustari Lamada, Aminuddin Bakry, Aulyah Zakilah Ifani, Khaerunnisa Khaerunnisa
Elinvo (Electronics, Informatics, and Vocational Education)
The application of technology is a need that is in demand in the industrial world today, especially in the field of contractors of goods and services that have implemented the use of applications to help the process of managing data and project documents in their companies. This study aims to optimize the web-based project tender document system using the extreme programming method. The extreme programming method consists of planning, design, coding, testing, and software increment. Research methods using extreme programming methods consisting of planning, design, coding, testing, and software increment. The planning stages obtain results in the form of functional …
Machine Learning-Based Data Analytics For Understanding Space Weather And Climate, Yasser Abduallah
Machine Learning-Based Data Analytics For Understanding Space Weather And Climate, Yasser Abduallah
Dissertations
This dissertation addresses multiple crucial problems in space weather and climate, presenting new machine learning-based data analytics algorithms and models for tackling the problems.
First, the dissertation presents two new approaches to predicting solar flares. One approach, called DeepSun, predicts solar flares by utilizing a machine-learning-as-a-service (MLaaS) platform. The DeepSun system provides a friendly interface for Web users and an application programming interface (API) for remote programming users. It adopts an ensemble learning method that employs several machine learning algorithms to perform multiclass flare prediction. The other approach, named SolarFlareNet, forecasts the occurrence of solar flares within the next 24 …
Monitoring Climate Change With Machine Learning And Uncertainty Quantification, Firas Gerges
Monitoring Climate Change With Machine Learning And Uncertainty Quantification, Firas Gerges
Dissertations
The impact of climate change on the environment has become increasingly visible today. One important topic in climate change monitoring is to forecast future climate events, which relies on long-term prediction of climate variables at a local regional scale. This topic is crucial for disaster risk management and for resolving climate change at the local level. General Circulation Models (GCMs) allow for the simulation of several climate variables, decades into the future. GCM simulations, however, are at a global large scale and are too coarse to monitor climate change at the local small scale. This dissertation explores new machine learning …
Implementation Of Ahp And Black Box Testing To The Development Of An Information System For Assessing The Feasibility Of Bumdes Submissions, Hari Toha Hidayat, Husaini Husaini, Nanang Prihatin, Radhiyatammardhiyyah Radhiyatammardhiyyah
Implementation Of Ahp And Black Box Testing To The Development Of An Information System For Assessing The Feasibility Of Bumdes Submissions, Hari Toha Hidayat, Husaini Husaini, Nanang Prihatin, Radhiyatammardhiyyah Radhiyatammardhiyyah
Elinvo (Electronics, Informatics, and Vocational Education)
The existence of institutional village enterprises (BUMDES) has never been adequately monitored in terms of the growth of village-owned businesses in each village. According to the data, there are 17 BUMDES in the Muara District that have been inactive for the most part. Due to the difficulty of monitoring the progress of BUMDES, a significant number of them have become stalled or even inactive. In addition, many BUMDES managers are frequently unprepared to operate the newly opened business. Readiness in terms of the quality of human resources also affects the formation of BUMDES. Consequently, the objective of this study is …
Comparison Of Web 2.0 Use On State University Websites In Indonesia And Top World Universities Related To Webometric Ranking, Handaru Jati
Comparison Of Web 2.0 Use On State University Websites In Indonesia And Top World Universities Related To Webometric Ranking, Handaru Jati
Elinvo (Electronics, Informatics, and Vocational Education)
The present work determines the presence in the web 2.0 that twenty universities had through their educational portals. The universities are selected according to the Webometrics ranking (the ten best located in Indonesia and the best located worldwide) to identify what Web 2.0 tools they use. This study explores the educational portals of the twenty selected universities to determine which Web 2.0 tools they use and variables of the tools found will be assessed. The study only considers those Web 2.0 tools which are linked to the websites of universities. Of the two most used tools, the relevant indicators are …
Occlusion Handler Density Networks For 3d Multimodal Joint Location Of Hand Pose Hypothesis, Stanley Tito
Occlusion Handler Density Networks For 3d Multimodal Joint Location Of Hand Pose Hypothesis, Stanley Tito
Tanzania Journal of Engineering and Technology (TJET)
(HPE) process is an ill-posed challenge. This is due to severe self occluded joints of the hand. The existing approaches for predicting pose parameters of the hand, utilize a single-value mapping of an input image to generate final pose output. This way makes it difficult to handle occlusion especially when it comes from the multimodal pose hypothesis. This paper introduces an effective method of handling multimodal joint occlusion using the negative log-likelihood of a multimodal mixture-of-Gaussians through a hybrid hierarchical mixture density network (HHMDN). The proposed approach generates multiple feasible hypotheses of 3D poses with visibility, unimodal and multimodal distribution …
Design And Implementation Of Cardiopulmonary Resuscitation Simulation Model, Mbazingwa Mkiramweni
Design And Implementation Of Cardiopulmonary Resuscitation Simulation Model, Mbazingwa Mkiramweni
Tanzania Journal of Engineering and Technology (TJET)
Cardiopulmonary resuscitation (CPR) is a life-saving procedure that can multiply a person's chances of survival after a cardiac arrest. The effectiveness of CPR procedures is heavily influenced by the individual skills of the rescuer providing assistance. Chest compressions delivered at an appropriate depth and rate, allowing full chest recoil and with minimal interruptions, are critical for improving cardiac arrest survival. The lack of quality CPR training models in developing countries has a significant impact on the quality of CPR training and skills acquired. Therefore, in this paper, we aim at improving CPR training by designing a high-fidelity CPR training manikin. …
Design Framework Of Uav-Based Environment Sensing, Localization, And Imaging System, Yue Sun
Design Framework Of Uav-Based Environment Sensing, Localization, And Imaging System, Yue Sun
Graduate Doctoral Dissertations
In this dissertation research, we develop a framework for designing an Unmanned Aerial Vehicle or UAV-based environment sensing, localization, and imaging system for challenging environments with no GPS signals and low visibility. The UAV system relies on the various sensors that it carries to conduct accurate sensing and localization of the objects in an environment, and further to reconstruct the 3D shapes of those objects. The system can be very useful when exploring an unknown or dangerous environment, e.g., a disaster site, which is not convenient or not accessible for humans. In addition, the system can be used for monitoring …
A Neural Analysis-Synthesis Approach To Learning Procedural Audio Models, Danzel Serrano
A Neural Analysis-Synthesis Approach To Learning Procedural Audio Models, Danzel Serrano
Theses
The effective sound design of environmental sounds is crucial to demonstrating an immersive experience. Classical Procedural Audio (PA) models have been developed to give the sound designer a fast way to synthesize a specific class of environmental sounds in a physically accurate and computationally efficient manner. These models are controllable due to the choice of parameters from analyzing a class of sound. However, the resulting synthesis lacks the fidelity for the preferred immersive experience; thus, the sound designer would rather search through an extensive database for real recordings of a target sound class. This thesis proposes the Procedural audio Variational …
Famaid: A Tool For Aiding People With Disability, Mohamad Maad, Ahmad Owaydate, Mohammad Kojok, Firas Aboudaher, Layal Abu Daher, May Itani
Famaid: A Tool For Aiding People With Disability, Mohamad Maad, Ahmad Owaydate, Mohammad Kojok, Firas Aboudaher, Layal Abu Daher, May Itani
BAU Journal - Science and Technology
People with disabilities suffer from discrimination and obstacles that restrict them from participating in society on an equal basis with others every day. They are deprived of their rights to be included in ordinary school systems and even in the work market. In the process of raising awareness, facilitating dailyroutines, and developing guidance, the idea of assisting such people with handy tools/software arose and was implemented in the FamAid tool. FamAid offers people with hearing disability the opportunity to be engaged in the society through many facilities. In this work, we implemented a web application that serves as a community …
Examining Early Elementary Computer Science Identity Repertoires Within A Curriculum: Implications For Epistemologically Pluralistic Identities, Eleanor Richard, Shakhnoza Kayumova
Examining Early Elementary Computer Science Identity Repertoires Within A Curriculum: Implications For Epistemologically Pluralistic Identities, Eleanor Richard, Shakhnoza Kayumova
Journal of Computer Science Integration
As computer science (CS) enters an increasing number of elementary classrooms, researchers must investigate the representations of what kinds of people are presented as doing computer science within CS curricula. In this paper, we explore a widely used, freely accessible, web-based, early elementary CS curriculum to examine the kinds of identity repertoires (behaviors, actions, skills, and socioemotional norms) that are promoted as representative of being/becoming a CS person. More specifically, we draw on identity studies and employ critical discourse analysis to examine how the kinds of norms and repertoires of CS practice made available in the curricular materials might construct …
Short Term Energy Consumption Forecasting Using Neural Basis Expansion Analysis For Interpretable Time Series, Abdul Khalique Shaikh, Amril Nazir, Imran Khan, Abdul Salam Shah
Short Term Energy Consumption Forecasting Using Neural Basis Expansion Analysis For Interpretable Time Series, Abdul Khalique Shaikh, Amril Nazir, Imran Khan, Abdul Salam Shah
All Works
Smart grids and smart homes are getting people's attention in the modern era of smart cities. The advancements of smart technologies and smart grids have created challenges related to energy efficiency and production according to the future demand of clients. Machine learning, specifically neural network-based methods, remained successful in energy consumption prediction, but still, there are gaps due to uncertainty in the data and limitations of the algorithms. Research published in the literature has used small datasets and profiles of primarily single users; therefore, models have difficulties when applied to large datasets with profiles of different customers. Thus, a smart …
Methods For Drone Trajectory Analysis Of Bottlenose Dolphins (Tursiops Truncatus), Jillian D. Bliss
Methods For Drone Trajectory Analysis Of Bottlenose Dolphins (Tursiops Truncatus), Jillian D. Bliss
Theses and Dissertations
With the increase in the use of UAS (Unmanned Aerial Systems) for marine mammal research, there is a need for the development of methods of analysis to transform UAS high resolution video into quantitative data. This study sought to develop a preliminary method of analysis that would quantify and present a way to visualize the dynamics and relative spatial distribution and changes in distribution of bottlenose dolphins (Tursiops truncatus) in the waters of Turneffe Atoll, Belize. This approach employs a previously developed video tracking program ‘Keypoint Tracking’ that enables manual tracking of individual dolphins and the creation of …
Emulating Future Neurotechnology Using Magic, Jay A. Olson, Mariève Cyr, Despina Z. Artenie, Thomas Strandberg, Lars Hall, Matthew L. Tompkins, Amir Raz, Petter Johansson
Emulating Future Neurotechnology Using Magic, Jay A. Olson, Mariève Cyr, Despina Z. Artenie, Thomas Strandberg, Lars Hall, Matthew L. Tompkins, Amir Raz, Petter Johansson
Psychology Faculty Articles and Research
Recent developments in neuroscience and artificial intelligence have allowed machines to decode mental processes with growing accuracy. Neuroethicists have speculated that perfecting these technologies may result in reactions ranging from an invasion of privacy to an increase in self-understanding. Yet, evaluating these predictions is difficult given that people are poor at forecasting their reactions. To address this, we developed a paradigm using elements of performance magic to emulate future neurotechnologies. We led 59 participants to believe that a (sham) neurotechnological machine could infer their preferences, detect their errors, and reveal their deep-seated attitudes. The machine gave participants randomly assigned positive …
Realizing Molecular Machine Learning Through Communications For Biological Ai: Future Directions And Challenges, Sasitharan Balasubramaniam, Samitha Somathilaka, Sehee Sun, Adrian Ratwatte, Massimiliano Pierobon
Realizing Molecular Machine Learning Through Communications For Biological Ai: Future Directions And Challenges, Sasitharan Balasubramaniam, Samitha Somathilaka, Sehee Sun, Adrian Ratwatte, Massimiliano Pierobon
School of Computing: Faculty Publications
Artificial Intelligence (AI) and Machine Learning (ML) are weaving their way into the fabric of society, where they are playing a crucial role in numerous facets of our lives. As we witness the increased deployment of AI and ML in various types of devices, we benefit from their use into energy-efficient algorithms for low powered devices. In this paper, we investigate a scale and medium that is far smaller than conventional devices as we move towards molecular systems that can be utilized to perform machine learning functions, i.e., Molecular Machine Learning (MML). Fundamental to the operation of MML is the …
Investigation, Detection And Prevention Of Online Child Sexual Abuse Material: A Comprehensive Survey, Vuong Ngo, Christina Thorpe, Cach N. Dang, Susan Mckeever
Investigation, Detection And Prevention Of Online Child Sexual Abuse Material: A Comprehensive Survey, Vuong Ngo, Christina Thorpe, Cach N. Dang, Susan Mckeever
Conference papers
Child sexual abuse inflicts lifelong devastating consequences for victims and is a growing social concern. In most countries, child sexual abuse material (CSAM) distribution is illegal. As a result, there are many research papers in the literature which proposed technologies to detect and investigate CSAM. In this survey, a comprehensive search of the peer reviewed journal and conference paper databases (including preprints) is conducted to identify high-quality literature. We use the PRISMA methodology to refine our search space to 2,761 papers published by Springer, Elsevier, IEEE and ACM. After iterative reviews of title, abstract and full text for relevance to …
Overview Of Research And Application On Autonomous Vehicle Oriented Perception System Simulation, Ruoxuan Wang, Jianping Wu, Hui Xu
Overview Of Research And Application On Autonomous Vehicle Oriented Perception System Simulation, Ruoxuan Wang, Jianping Wu, Hui Xu
Journal of System Simulation
Abstract: Following the rapid progress of science and technology, vehicles with autonomous driving or auxiliary driving function enter into vehicle market. However, in the past decade, traffic accidents still occurred frequently, and the safety of these functions become the focus. Simulation technology provides a good platform to test the perception system of autonomous vehicle. Focus on the sensor simulation modeling of autonomous vehicle perception system, from the perspective of single sensor simulation, multi-sensor simulation and classic simulation platform including millimeter wave radar, lidar and camera, the existing research are reviewed, and the shortcomings and development trends of simulation modeling of …
Anomaly Detection Method Of Electrical Power Consumption Based On Deep Autoencoder, Ningke Sun, Yan Wang, Zhicheng Ji
Anomaly Detection Method Of Electrical Power Consumption Based On Deep Autoencoder, Ningke Sun, Yan Wang, Zhicheng Ji
Journal of System Simulation
Abstract: Aiming at the nonlinear and non-stationary characteristics of electrical power consumption data, an abnormal electrical power consumption detection model based on deep autoencoder is proposed. Gated recurrent unit (GRU) network of the deep learning is combined with autoencoder structure, and the encoder and decoder parts of traditional autoencoder are realized by gated recurrent unit network, which gives full play to the data feature extraction capability of gated recurrent unit and the data reconstruction function of autoencoder structure. Based on the reconstruction error between original data and reconstructed data, abnormal data points of the electrical power consumption are detected. By …
Short-Term Prediction Method Of Wind Power Based On Blp-Alo-Svm, Yefeng Jiao, Yan Wang, Zhicheng Ji
Short-Term Prediction Method Of Wind Power Based On Blp-Alo-Svm, Yefeng Jiao, Yan Wang, Zhicheng Ji
Journal of System Simulation
Abstract: To effectively predict the short-term wind power and its fluctuation range, a prediction method based on hybrid algorithm-optimized support vector machine is proposed. Exploratory data analysis is used to preprocess the original wind speed data to improve the data quality. Chaotic map, Levy flight strategy and particle swarm optimization are used to improve the ant lion algorithm. The support vector machine model optimized by hybrid algorithm is used to predict the wind power. The experimental results show that, compared with the new wind power prediction model, the prediction error of the output results of the method is lower, and …
Long-Term Resilience Simulation On Low-Carbon Urban Grid Based On Evolutionary Game, Zhengda Cui, Weiqiang Yao, Qin Xu, Chen Fang, Ying Chen
Long-Term Resilience Simulation On Low-Carbon Urban Grid Based On Evolutionary Game, Zhengda Cui, Weiqiang Yao, Qin Xu, Chen Fang, Ying Chen
Journal of System Simulation
Abstract: Because of the more frequent extreme disasters, the resilience of urban grid becomes more important. In the background of carbon neutralization policy, the decarbonization transition of urban grid also affects the development of grid resilience. An evolutionary game is used to simulate the resilience evolution of low-carbon urban grid and the evolution model is constructed. The decision to install photovoltaic and energy storage system for residents and to upgrade the grid for resilience is considered in the model and the stability conditions of equilibriums of the evolutionary game are analyzed. The resilience evolution simulation model considering disaster stochasticity is …
Simulation-Driven Based Utility Evaluation And Recommendation Of Expressway Proactive Speed Limit, Geqi Qi, Sijin Liu, Yikang He, Meng Wang, Ailing Huang
Simulation-Driven Based Utility Evaluation And Recommendation Of Expressway Proactive Speed Limit, Geqi Qi, Sijin Liu, Yikang He, Meng Wang, Ailing Huang
Journal of System Simulation
Abstract: Outside the specific punishment area, the traditional roadside passive speed limit mode lacks traffic management, and thus which indirectly leads to the inconsistency or even sudden change of vehicle behaviors in time and space, thereby affects the traffic efficiency and safety. Focusing on the proactive speed limit mode at vehicle side, a utility evaluation and recommendation method is proposed, which carries out the multi-scenario traffic simulation for varied proactive and passive speed limit considering road line types, traffic flow and vehicle type proportion. From the two perspectives of safety and efficiency, the utility evaluation indicators and weights are extracted …
Simulation On Flood Disaster In Urban Building Complex System Based On Lbm, Shen Zhang, Zewang Yang, Yifan Wang, Liang Sun, Ming Cheng, Fankai Meng, Ting Li
Simulation On Flood Disaster In Urban Building Complex System Based On Lbm, Shen Zhang, Zewang Yang, Yifan Wang, Liang Sun, Ming Cheng, Fankai Meng, Ting Li
Journal of System Simulation
Abstract: Because of the extreme climate change, the potential flood disaster risk in the southeast coastal areas of China can not be ignored. Based on lattice Boltzmann computational fluid dynamics method, a three-dimensional simulation study of waterlogging process in tsunami impact scenario is carried out for a coastal city building complex system, and the reliability and accuracy of the numerical simulation method for the flood impact test of an ideal building complex are verified. The results show that the buildings along rivers and coastlines have obvious cloaking effect, while the buildings inside the city are less affected by floods. The …
Research On Modeling And Simulation Technology Of Microwave Radar High Precision Tracking Loop, Jiaji Lou, Jing Ma, Xiaowei Li, Yue Zhao, Youbin Song
Research On Modeling And Simulation Technology Of Microwave Radar High Precision Tracking Loop, Jiaji Lou, Jing Ma, Xiaowei Li, Yue Zhao, Youbin Song
Journal of System Simulation
Abstract: Aiming at the key problem of high-precision tracking loop design of a measurement radar for the weak signal (low carrier to noise ratio signal) in dynamic environment, the design and optimization methods of carrier tracking loop and code tracking loop are focused on. A signal structure with a single carrier as a pilot is proposed, and the loop structure of the frequency-locked loop and the phase-locked loop working together is studied. The modeling and simulation on the two structures show that for the week signal tracking in a dynamic environment, the loop combination structure of the frequency-serial auxiliary …
Research On Parameter Construction Method Of Blue Army Equipment Model Based On A Deep Network, Boyuan Zhang, Guanghong Gong, Ze Wang, Ni Li
Research On Parameter Construction Method Of Blue Army Equipment Model Based On A Deep Network, Boyuan Zhang, Guanghong Gong, Ze Wang, Ni Li
Journal of System Simulation
Abstract: The modeling of blue army equipment is an indispensable part of adversarial simulation environment construction. Aiming at the limited available parameters of "information-poor" and "small sample" characteristics to the blue system, a deep network-based method is proposed to generate the parameters of blue army equipment model. By injecting the information into the simulation model of the blue army equipment, the simulation data is generated and trained in the deep neural network. The obtained network has a certain generalization ability to the unknown parameters prediction of the same type of equipment and can be used directly in prediction or be …
Multi-Robot Path Planning Based On Cbs Algorithm, Qiao Qiao, Yan Wang, Zhicheng Ji
Multi-Robot Path Planning Based On Cbs Algorithm, Qiao Qiao, Yan Wang, Zhicheng Ji
Journal of System Simulation
Abstract: Aiming at the long multi-robot planning path and long one-way search running time of conflict-based search(CBS) in the multi-agent path finding(MAPF), an improved CBS algorithm is proposed, which in a two-way A* focus search is used to optimize the search direction and search method. The suboptimal factorωis introduced into the underlying search function of the CBS algorithm to improve the efficiency of path search. The one-way search in the conflict search algorithm is optimized to a two-way A* search. The experimental results show that the path cost of the improved CBS algorithm is shortened …
Research On Emotional Contagion And Intervention Strategy Of Indoor Evacuation Based On Risk Perception, Yang Zeng, Jinling Li, Haixiang Guo, Weiming Chen
Research On Emotional Contagion And Intervention Strategy Of Indoor Evacuation Based On Risk Perception, Yang Zeng, Jinling Li, Haixiang Guo, Weiming Chen
Journal of System Simulation
Abstract: Aiming at the panic emotion contagion in the indoor emergency evacuation with multi-exit and multi-obstacle, an emotional contagion model is constructed on personality traits, risk perception differences of age and gender, and consciousness regulation. The simulation is carried out by using AnyLogic, which combines individual emotions with evacuation speed to realize the real-time updating of emotional state and speed. That personnel intervention in the process of evacuation can effectively alleviate the spread of panic emotion, is verified and can provide the theoretical basis for panic contagion in the process of emergency evacuation. The results show that the degree of …
Research On Complex Combat Network Dynamic Evolution Based On Information Entropy, Lianyi Zhang, Xisheng Shen, Duzheng Qing, Han Zhang, Min Zhou, Xifu Wang
Research On Complex Combat Network Dynamic Evolution Based On Information Entropy, Lianyi Zhang, Xisheng Shen, Duzheng Qing, Han Zhang, Min Zhou, Xifu Wang
Journal of System Simulation
Abstract: Network-centric warfare, distributed and decentralized command and control gradually replace separately the traditional platform-centric warfare and centralized command and control, and information has become a combat capability. Based on the new information weapon equipment system operation loop, a complex combat network model based on information entropy is constructed, and the combat capability measurement method is proposed. On the basis of the combat capability upgrade being the network driving force, the dynamic evolution rule of the complex combat network is designed and the preferential evolution and stochastic evolution models are constructed. According to a typical system combat example, the influence …