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Articles 64021 - 64050 of 294599

Full-Text Articles in Physical Sciences and Mathematics

Parametric And Reliability Estimation Of The Kumaraswamy Generalized Distribution Based On Record Values, Mohd. Arshad, Qazi J. Azhad Jan 2022

Parametric And Reliability Estimation Of The Kumaraswamy Generalized Distribution Based On Record Values, Mohd. Arshad, Qazi J. Azhad

Journal of Modern Applied Statistical Methods

A general family of distributions, namely Kumaraswamy generalized family of (Kw-G) distribution, is considered for estimation of the unknown parameters and reliability function based on record data from Kw-G distribution. The maximum likelihood estimators (MLEs) are derived for unknown parameters and reliability function, along with its confidence intervals. A Bayesian study is carried out under symmetric and asymmetric loss functions in order to find the Bayes estimators for unknown parameters and reliability function. Future record values are predicted using Bayesian approach and non Bayesian approach, based on numerical examples and a monte carlo simulation.

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Reef Sediments Can Act As A Stony Coral Tissue Loss Disease Vector, Michael S. Studivan, Ashley M. Rossin, Ewelina Rubin, Nash Soderberg, Daniel M. Holstein, Ian C. Enochs Jan 2022

Reef Sediments Can Act As A Stony Coral Tissue Loss Disease Vector, Michael S. Studivan, Ashley M. Rossin, Ewelina Rubin, Nash Soderberg, Daniel M. Holstein, Ian C. Enochs

Faculty Publications

Stony coral tissue loss disease (SCTLD) was first observed in 2014 near Virginia Key in Miami-Dade County, Florida. Field sampling, lab experiments, and modeling approaches have suggested that reef sediments may play a role in SCTLD transmission, though a positive link has not been tested experimentally. We conducted an ex situ transmission assay using a statistically-independent disease apparatus to test whether reef sediments can transmit SCTLD in the absence of direct contact between diseased and healthy coral tissue. We evaluated two methods of sediment inoculation: batch inoculation of sediments collected from southeast Florida using whole colonies of diseased Montastraea cavernosa, …

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Intelligent Control Of Wastewater Treatment Processes Based On Adaptive Immune Optimization, Li Fei, Su Zhong Jan 2022

Intelligent Control Of Wastewater Treatment Processes Based On Adaptive Immune Optimization, Li Fei, Su Zhong

Journal of System Simulation

Abstract: In order to solve the problems of excessive energy consumption and excessive effluent quality in wastewater treatment process control, an intelligent control system based on adaptive immune optimization (AIOIC) is proposed. A hierarchical control strategy is designed, and a fast online self-organizing fuzzy neural network based on singular value decomposition (SVDFNN) is used to construct the mathematical model of wastewater treatment energy consumption and effluent quality. In order to obtain the optimal set values of dissolved oxygen and nitrate nitrogen, an adaptive hybrid evolutionary immune optimization algorithm is designed. The self-organizing recursive fuzzy neural network controller is used …

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Saving The Campus Farm: One Approach To Leveraging Institutional Support For A Campus Farm Space, Julia L. Angstmann Jan 2022

Saving The Campus Farm: One Approach To Leveraging Institutional Support For A Campus Farm Space, Julia L. Angstmann

Scholarship and Professional Work - LAS

The number of university and college campus farms have increased 13-fold since 1992 to over 300 campuses (LaCharite, 2016). According to reporting by the Association for the Advancement of Sustainability in Higher Education (AASHE) (2018), 80% of campus farm spaces are less than 5 acres in size and 86% are located on campuses with no agriculture school (AASHE, 2018). Campus farms provide a rich interdisciplinary social context of community based, sustainable agriculture that spans the entire suite of social and physical sciences as well as non-STEM fields such as business, religious studies, and communication. Yet, the majority of these farm …

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Heat, Wildfire And Energy Demand: An Examination Of Residential Buildings And Community Equity, Chrissi Argyro Antonopoulos Jan 2022

Heat, Wildfire And Energy Demand: An Examination Of Residential Buildings And Community Equity, Chrissi Argyro Antonopoulos

Dissertations and Theses

Extreme heat and wildfire events are becoming more prolific and exacerbated by climate change, carrying significant implications for environmental and social systems. Residential buildings play a central role in protecting people from heat and pollutant exposure during extreme weather events, but the level of protection varies dramatically depending on building energy efficiency and technology availability. Low-income and communities of color have higher energy burdens compared to affluent populations, and underserved communities often do not have financial resources for, or access to, advanced building technologies. This dissertation explores the impacts of extreme heat and wildfire on residential buildings, focused specifically on …

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2022 Final Butte Priority Soils Operable Unit Interim Site-Wide Groundwater Monitoring Quality Assurance Project Plan (Qapp), Trec Inc., A Woodard And Curran Company Jan 2022

2022 Final Butte Priority Soils Operable Unit Interim Site-Wide Groundwater Monitoring Quality Assurance Project Plan (Qapp), Trec Inc., A Woodard And Curran Company

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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More Than Words: Articulating The Multisensory Experiences Of Protected Area Visitors In Southern Nevada, Sara Nicole Temme Jan 2022

More Than Words: Articulating The Multisensory Experiences Of Protected Area Visitors In Southern Nevada, Sara Nicole Temme

Dissertations and Theses

The complex sensory experiences of visitors to U.S. protected areas are not well understood. Previous research investigates visitor activities, motivations, and the ways place attachment cultivates support for conservation activities and other pro-environmental behavior. However, it is unclear how protected area visitor sensory experiences contribute to these behaviors. This study aims to articulate the multisensory experiences of visitors to the Desert National Wildlife Refuge Complex and the Spring Mountains National Recreation Area in southern Nevada, U.S.A. Specifically, it demonstrates the complexity of these experiences as present, intertwined, and embodied in all visit phases: before, during, and after. Utilizing a mixed-method …

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Survey Of Ship Detection In Video Surveillance Based On Shallow Machine Learning, Zhenbo Bi, Shiyou Zhang, Yang Hua, Yuanhong Wu Jan 2022

Survey Of Ship Detection In Video Surveillance Based On Shallow Machine Learning, Zhenbo Bi, Shiyou Zhang, Yang Hua, Yuanhong Wu

Journal of System Simulation

Abstract: At present, detection of ship targets in video surveillance based on shallow machine learning methods is still attracting attention in the fields of underwater cultural heritage protection, marine aquaculture, maritime traffic, and port management. This paper provides a review and discussion for this kind of ship detection methods. The ship target detection based on video surveillance is divided into five parts according to the key technologies involved: preprocessing, region of interest extraction, target segmentation, ship feature extraction and ship type recognition. According to different functional modules, the core problems involved in them are pointed out, and the core ideas, …

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Research On Detection Data Driven Calibration Method Of Traffic Simulation Parameters, Wenxin Ma, Ruimin Li Jan 2022

Research On Detection Data Driven Calibration Method Of Traffic Simulation Parameters, Wenxin Ma, Ruimin Li

Journal of System Simulation

Abstract: To improve the accuracy of traffic simulation model and timely response of traffic demand and driving behavior changes, dynamic calibration method of simulation parameters based on detection data is proposed. Dynamic interaction between detection data and simulation platform is proposed. Intersection of Guanghua Road/Jintong East Road in Beijing and five consecutive intersections on Youyi Street in Baotou are Selected as study cases. Sensitivity analysis is conducted on initial parameter combinations. Based on the analysis results, parameters to be calibrated are selected. Models of cases are developed in VISSIM and driving behavior parameters are calibrated. Simulation results show that …

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An Evolutionary Multi-Objective Simulation Optimization Algorithm For Supply Chain With Uncertain Demands, Hongfeng Wang, Yitian Zhang, Jingze Chen Jan 2022

An Evolutionary Multi-Objective Simulation Optimization Algorithm For Supply Chain With Uncertain Demands, Hongfeng Wang, Yitian Zhang, Jingze Chen

Journal of System Simulation

Abstract: During the COVID-19 pandemic, supply chain of manufacturing companies is facing more severe product demand uncertainty, which is manifested in the sharp increase in demand for certain types of products and the increased fluctuations in supply for raw materials. For this supply chain optimization problem with demand uncertainty, a multi-objective stochastic programming model is developed in order to maximize the total profit and product order fulfillment rate simultaneously in this paper. For solving the investigated problem, a new evolutionary multi-objective simulation optimization algorithm is proposed by combining the mechanism of NSGA-II and simulation computing budget allocation adaptively. Experimental …

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Real-Time Simulation Technology Of Fluid-Thermo-Solid Coupling Of Hypersonic Vehicle, Yunqin Liu, Li Ni, Luming Zhao, Jinpeng Bai, Tingjun Li, Chenguang Wang Jan 2022

Real-Time Simulation Technology Of Fluid-Thermo-Solid Coupling Of Hypersonic Vehicle, Yunqin Liu, Li Ni, Luming Zhao, Jinpeng Bai, Tingjun Li, Chenguang Wang

Journal of System Simulation

Abstract: The solution of the coupling characteristics of fluid-thermo-solid physics in the modeling of hypersonic vehicle is an unavoidable difficulty, and the real-time simulation of fluid-thermo-solid coupling is particularly challenging. Aiming at the conflicting problem of solution accuracy and solution efficiency in fluid-thermo-solid coupling real-time simulation, a CFD (Computational Fluid Dynamics)/ CSD (Computational Structural Dynamics)-based fluid-thermo-solid coupling characteristic solution method is established, which realizes the high-precision solution of the fluid, temperature, and structural deformation field coupling. According to the multi-condition offline solution set modeling method, by accumulating a large number of offline solutions as effective support for online …

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Weld Bead Size Prediction Of Wire And Arc Additive Manufacturing Based On Acs-Dbn, Dong Hai, Xiuxiu Gao, Mingqi Wei Jan 2022

Weld Bead Size Prediction Of Wire And Arc Additive Manufacturing Based On Acs-Dbn, Dong Hai, Xiuxiu Gao, Mingqi Wei

Journal of System Simulation

Abstract: Welding pass overlap is the essence of wire and arc additive manufacturing (WAAM) technology. Appropriate process parameter selection is of great significance to control the welding pass geometry and improve the dimensional accuracy of the molded parts. A prediction model of deep beilef network (DBN) optimized by adaptive cuckoo search (ACS) algorithm is constructed. The welding width and residual height of the weld pass are predicted based on the four technological parameters of the given nozzle height, welding current, welding speed and wire feeding speed. The optimal number of hidden layers and hidden elements are determined based on the …

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A Data-Driven Modeling Method For Game Adversity Agent, Zeng Bi, Fang Xiao, Deshuai Kong, Xiangxiang Song, Zhengxuan Jia, Tingyu Lin Jan 2022

A Data-Driven Modeling Method For Game Adversity Agent, Zeng Bi, Fang Xiao, Deshuai Kong, Xiangxiang Song, Zhengxuan Jia, Tingyu Lin

Journal of System Simulation

Abstract: Aiming at the problems of collaborative modeling of formation behavior and intelligent generation of decision-making in complex confrontation scenarios, based on the serious game to simulate the confrontation scenarios of complex maritime equipment against the air, this paper proposes a data-driven modeling method for game agent and uses a distributed modeling technology of parallel adversarial scenarios and opportunistic decision making technology of smart targets to achieve agent modeling. It provides support for the further exploration of multi-objective collaborative modeling in complex confrontation scenarios. The simulation results show that deep reinforcement learning algorithms can provide a basis for the modeling …

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Research On Usv Navigation Simulation Key Technologies, Jianhai Jin, Zexing Zhou, Zhang Bo, Yihong Chen, Xizhong Wei Jan 2022

Research On Usv Navigation Simulation Key Technologies, Jianhai Jin, Zexing Zhou, Zhang Bo, Yihong Chen, Xizhong Wei

Journal of System Simulation

Abstract: In order to solve the problems of long test time, high cost and high risk, a general framework of simulation system for autonomous navigation test and verification of USV(Unmanned Surface Vessel) has been developed, and some key simulation technologies such as complex scenario simulation, intelligent perception, navigation simulation and environmental effect modeling are researched. the dynamic equation, kinematics equation, wind load modeling, wave surface modeling, wave drift force modeling and ocean current modeling are designed and realized. The simulation system is proved to have high accuracy and fidelity by the real ship test on the lake, which can greatly …

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Kinematics Analysis And Simulation Of Automatically Tracking Dental Surgery Lamp, Zerui Jiang, Lijun Yang, Li Jun, Xiaolong Jiao, Zheng Hang Jan 2022

Kinematics Analysis And Simulation Of Automatically Tracking Dental Surgery Lamp, Zerui Jiang, Lijun Yang, Li Jun, Xiaolong Jiao, Zheng Hang

Journal of System Simulation

Abstract: In order to solve the problem that the oral surgical lamp cannot automatically adjust the irradiation posture of the surgical lamp according to the face direction and oral cavity position, a six-degree-of-freedom automatic tracking visual manipulator solution is proposed. Coordinate conversion is achieved through binocular vision to obtain three-dimensional information of oral cavity position and face normal vector. The geometric method is introduced into the kinematics calculation, and the closed solution of the inverse kinematics is obtained. The correctness is verified by the Maltab programming and the introduction of numerical values. Five-degree polynomial motion planning is performed …

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Research On Digital Twin-Based Modeling And Monitoring Of Five-Axis Grinder, Xiao Tong, Haifan Jiang, Guofu Ding, Jiang Lei, Shuwen Ma Jan 2022

Research On Digital Twin-Based Modeling And Monitoring Of Five-Axis Grinder, Xiao Tong, Haifan Jiang, Guofu Ding, Jiang Lei, Shuwen Ma

Journal of System Simulation

Abstract: Aiming at the poor virtual-real interaction ability, single data presentation mode, and hysteretic abnormality handling in CNC machine tool status monitoring, a visual monitoring method for machine tool process based on digital twin is proposed, Which realizes the mapping of three subsystems of machine tool, machinery, control and electrical to the information space from three dimensions of geometry, logic and data. The verification of instructions and CNC programs, real-time status monitoring and abnormality handling during operation are carried out. A digital twin-based machine tool modeling and monitoring system is designed and developed. Taking a five-axis CNC …

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Research On Cloud Tool Integration And Management Methods, Tianying Zhang, Ji Hang, Junhua Zhou, Tao Luan Jan 2022

Research On Cloud Tool Integration And Management Methods, Tianying Zhang, Ji Hang, Junhua Zhou, Tao Luan

Journal of System Simulation

Abstract: In response to the application needs of using professional tools to develop complex products in the fields of aerospace, aviation, weapons, ships, etc., it is urgent to implement centralized management of cloud tools and cross-professional sharing of tools through tool service-oriented methods, so as to solve issues such as inconsistent tool versions, cross-professional resource barriers, and high thresholds for tool mastery during the traditional model development process. By studying the integration and calling methods of cross-professional and different versions of self-developed tools, as well as methods of tool server operation control, authority management, etc., and taking the local …

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Special Vehicle Driving Training Simulation System Based On Integration Of Virtuality And Reality, Xiangyang Li, Wang Xiao, Zhili Zhang, Yihao Li, Long Yong Jan 2022

Special Vehicle Driving Training Simulation System Based On Integration Of Virtuality And Reality, Xiangyang Li, Wang Xiao, Zhili Zhang, Yihao Li, Long Yong

Journal of System Simulation

Abstract: Aiming at the actual demands of special vehicle driving training, special vehicle driving training simulation system is designed and developed based on the integration of virtuality and reality mode. Through building all kinds of mathematical models, functional modules, workflows and control software, and applying the cab that same as actual equipment with manipulating device, central control instrument and driving seat, immersive driving training environment with integration of virtuality and reality is established based on 6-DoF motion platform and its control system as well as multi-channel visual display device. It can provide the integrated support platform with “educating, training and …

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Research On Semi-Physical Simulation Model Of Special Vehicle Cockpit With Force Feedback, Liang Feng, Zhili Zhang, Xiangyang Li, Yihao Li, Wang Bei, Long Yong Jan 2022

Research On Semi-Physical Simulation Model Of Special Vehicle Cockpit With Force Feedback, Liang Feng, Zhili Zhang, Xiangyang Li, Yihao Li, Wang Bei, Long Yong

Journal of System Simulation

Abstract: To improve the interaction and immersion of cockpit simulation training system, a semi-physical model of special vehicle cockpit with force feedback is studied. The important force feedback parts of the semi-physical simulation model are designed to provide more real operation experience for operators. The simulation training method of special vehicle cockpit based on dynamic model is studied to match the action input of operators with scene changes and provide a high fidelity visual experience. The driving simulation operation process of special vehicle is analyzed and verified. Simulation experiments show that the model has the characteristics of high precision, fast …

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Simulation Research On U-Automated Container Terminal, Ding Yi, Tiantian Li Jan 2022

Simulation Research On U-Automated Container Terminal, Ding Yi, Tiantian Li

Journal of System Simulation

Abstract: To analyze the new U-layout effect on the handling operation efficiency in automated container terminal, the U-automated container terminal simulation model is established by FlexTerm software to visualize the handling operation process. The traditional automated terminal simulation model is established to compare the working efficiency under different working modes. The working ability of terminal handling equipment such as AGV（Automated Guided Vehicle）, yard cranes and rail-mounted gantry cranes are compared by simulation tests. Simulation results show that due to the creation of yard layout and handling technology, the superiority of U-layout is proved when the working efficiency of each handling …

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Predictive Control Method Of Peak Hour Passenger Flow At Urban Rail Station, Xiaohe Li, Jianping Wu, Depin Peng Jan 2022

Predictive Control Method Of Peak Hour Passenger Flow At Urban Rail Station, Xiaohe Li, Jianping Wu, Depin Peng

Journal of System Simulation

Abstract: With the rapid development of subway in China, the urban rail station, especially the transfer station, is prone to generate passenger congestion in the peak period. After analyzing the types of passenger flow in and out of the platform, a predictive control model of passenger flow is established based on the discrete linear quadratic optimal control theory. Taking Fuxingmen Station as an example, the simulation environment of the station is built by using the simulation software of Anylogic. The historical passenger flow data in peak period and the optimal passenger flow control sequence obtained by solving the passenger flow …

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Study And Effect Evaluation On The Setting Of Contraflow Left-Turn At Intersections, Zhao Dan, Xuejun Niu, Shuhao Zhang, Jiaxu Wei Jan 2022

Study And Effect Evaluation On The Setting Of Contraflow Left-Turn At Intersections, Zhao Dan, Xuejun Niu, Shuhao Zhang, Jiaxu Wei

Journal of System Simulation

Abstract: Contraflow left-turn is one of the traffic organization ways at intersections. By analyzing the setting parameters of the contraflow left-turn, the length and the range of the contraflow left-turn lane, the constrained conditions of the contraflow left-turn are determined, and the applicable conditions are determined from the road, traffic and signal control. VISSIM software is used to analyze a road intersection, simulate and evaluate the indicators related to the intersection entrance, optimize the timing plan of contraflow left-turn lane, and validate the feasibility and advantages of contraflow left-turn lane. The results show that the intersection delays are reduced by …

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Variety Recognition Based On Deep Learning And Double-Sided Characteristics Of Maize Kernel, Feng Xiao, Zhang Hui, Zhou Rui, Qiao Lu, Wei Dong, Dandan Li, Yuyao Zhang, Guoqing Zheng Jan 2022

Variety Recognition Based On Deep Learning And Double-Sided Characteristics Of Maize Kernel, Feng Xiao, Zhang Hui, Zhou Rui, Qiao Lu, Wei Dong, Dandan Li, Yuyao Zhang, Guoqing Zheng

Journal of System Simulation

Abstract: In order to construct a maize kernel variety recognition model with high recognition accuracy and suitable for mobile phone application, a mobile phone is used to obtain maize kernel double-sided (embryonic and non-embryonic) images. Based on the lightweight convolutional neural network MobileNetV2 and transfer learning, a maize kernel image variety recognition model is constructed. In view of the existing research methods are mainly for single-sided recognition of maize kernel variety, the performance of single-sided and double-sided characteristics modeling and recognition is compared. The results show that the double-sided recognition accuracy of maize kernel double-sided characteristics modeling is 99.83%, which …

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Track Deception Modeling Method Based On Multi-Jammer Cooperation, Wang Rui, Xiangyang Li, Zhili Zhang, Hongguang Ma Jan 2022

Track Deception Modeling Method Based On Multi-Jammer Cooperation, Wang Rui, Xiangyang Li, Zhili Zhang, Hongguang Ma

Journal of System Simulation

Abstract: The false track generated by the jammer formation is an effective interference measure against networked radars. This paper starts from the basic principle of false track generation and presents the model of the measurement error of the radar for the false track and the control error of the jammer formation. It also presents an analysis of the effects of these errors on the false track. The effectiveness of the false track is further analyzed through the confrontation scenario between the rectangular front formation of a certain type of equipment and networked radars. The simulation results show that the false …

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Low Power Visual Odometry Technology Based On Monocular Depth Estimation, Ma Rong, Qiurui Chen, Zhang Han, Mei Zheng, Wang Rui, Wei Wei Jan 2022

Low Power Visual Odometry Technology Based On Monocular Depth Estimation, Ma Rong, Qiurui Chen, Zhang Han, Mei Zheng, Wang Rui, Wei Wei

Journal of System Simulation

Abstract: With the development of artificial intelligence, precision machinery and computing technology, micro-unmanned system will play an important role in the future battlefield. To solve the lack of monocular visual odometry scale, micro robot power consumption and load limits, the monocular depth estimation technology is introduced and a low view dataset is collected. A convolutional neural network to predict depth information from a single image is built, and the structure of neural network model is optimized. The depth estimation with monocular visual odometry are combined and deployed on JetsonNano. Experiments show that the combined monocular visual odometry can recover scale …

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Research On Supply Chain Recovery Strategy Under Disruption Risks, Yang Yi, Peng Chen, Yujiu Yang, Yulong Wang Jan 2022

Research On Supply Chain Recovery Strategy Under Disruption Risks, Yang Yi, Peng Chen, Yujiu Yang, Yulong Wang

Journal of System Simulation

Abstract: Aiming at supply chain disruptions, two effective supply chain recovery strategies are proposed, namely, a supplier’s preset emergency inventory strategy and a manufacturer’s product change strategy, meanwhile, emergency inventory storage cost and products return rate after change are also taken into consideration. In order to maximize the manufacturer’s profit and customer satisfaction, a single-objective model and a bi-objective model are established, respectively. The optimization problems in the two models are transformed into mixed integer programming problems, moreover, corresponding solution algorithms are presented based on ILOG CPLEX. The simulation results show that the disruption recovery strategies proposed can not only …

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Radar Emitter Signal Identification Via Distance Features, Yingkun Huang, Weidong Jin, Yan Kang, Jiehao Zhu Jan 2022

Radar Emitter Signal Identification Via Distance Features, Yingkun Huang, Weidong Jin, Yan Kang, Jiehao Zhu

Journal of System Simulation

Abstract: Aiming at the problem that traditional recognition methods of radar emitter signal have low accuracy in low signal to noise ratio (SNR) environment, and are usually suitable for only several specific radar signals, an identification approach of radar signal based on distance features is proposed. Several cluster centers are extracted via the k-means algorithm, and the Dynamic Time Warping (DTW) values between the radar signal and the cluster center are calculated respectively, which are combined as the input features of k-Nearest Neighbor (k-NN) algorithm. The simulation results show that when the SNR is 3 dB, the identification rate …

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Study On Prediction Of Crystal Properties Based On Deep Learning, Buwei Wang, Wang Min, Fan Qian, Ya'nan Wang, Hanwen Zhang, Yunliang Yue Jan 2022

Study On Prediction Of Crystal Properties Based On Deep Learning, Buwei Wang, Wang Min, Fan Qian, Ya'nan Wang, Hanwen Zhang, Yunliang Yue

Journal of System Simulation

Abstract: Predicting crystal properties using traditional machine learning methods requires complex feature engineering. In order to bypass time-consuming feature engineering, element network (ElemNet), representation learning from stoichiometry (Roost), compositionally-restricted attention-based network (CrabNet) and crystal graph convolution neural network (CGCNN) based on deep learning technology are used to simulate the formation energy, total energy per atom, band gap, and Fermi energy of crystal. The residual learning is introduced into CGCNN, and a crystal graph convolution residual neural network (CGCRN) is proposed. In the CGCRN, the number of hidden layers and the number of nodes in the hidden layers are increased, …

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Improved Ant Colony Optimization Algorithm For Jamming Resource Allocation, Qingyun Wang, Dezhong Jiao, Shi Shuo, Genyan Peng, Junhua Sun, Yuxin Duan Jan 2022

Improved Ant Colony Optimization Algorithm For Jamming Resource Allocation, Qingyun Wang, Dezhong Jiao, Shi Shuo, Genyan Peng, Junhua Sun, Yuxin Duan

Journal of System Simulation

Abstract: Ant Colony Optimization (ACO) is a new intelligence optimization algorithm. When applied to jamming resource allocation, the velocity of convergence in optimization process is slow and the probability of obtaining the global optimal solution is low. In order to raise the efficiency of jamming resource allocation and the probability of getting global optimal solution, the attenuation factor is improved to a variable that changes according to the exponential function in optimization process. The attenuation factor is taken as a relatively small value in the initial search phase, and increases monotonically and exponentially as the number of iterations increases. Simulation …

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Brief Review On Applying Reinforcement Learning To Job Shop Scheduling Problems, Xiaohan Wang, Zhang Lin, Ren Lei, Kunyu Xie, Kunyu Wang, Ye Fei, Chen Zhen Jan 2022

Brief Review On Applying Reinforcement Learning To Job Shop Scheduling Problems, Xiaohan Wang, Zhang Lin, Ren Lei, Kunyu Xie, Kunyu Wang, Ye Fei, Chen Zhen

Journal of System Simulation

Abstract: Reinforcement Learning (RL) achieves lower time response and better model generalization in Job Shop Scheduling Problem (JSSP). To explain the current overall research status of JSSP based on RL, summarize the current scheduling framework based on RL, and lay the foundation for follow-up research, the backgrounds of JSSP and RL are introduced. Two simulation techniques commonly used in JSSP are analyzed and two commonly used frameworks for RL to solve JSSP are given. In addition, some existing challenges are pointed out, and related research progress is introduced from three aspects: direct scheduling, feature representation-based scheduling, and parameter search-based scheduling.

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