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Articles 1321 - 1350 of 4777
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Research On Optimization Of Airport Cargo Business Based On Deep Reinforcement Learning, Hongwei Wang, Peng Yang
Research On Optimization Of Airport Cargo Business Based On Deep Reinforcement Learning, Hongwei Wang, Peng Yang
Journal of System Simulation
Abstract: An intelligent agent technology architecture is adopted to the simulation model development of airport cargo business. Aiming at the optimization of airport cargo resources, a decision support system framework combining deep reinforcement learning (DRL) and airport cargo business simulation model is proposed. The simulated results are applied as the training data of the DRL network, and the DRL is used to optimize operation parameter of the simulation model. The mature system can be run online, which can provide optimized operation order in real time. In order to verify the effectiveness of the architecture, model development and experiments are conducted …
Research On Active Learning Method And Application Based On Covariance Matrix, Bowen Zhou, Weili Xiong
Research On Active Learning Method And Application Based On Covariance Matrix, Bowen Zhou, Weili Xiong
Journal of System Simulation
Abstract: Since the data collected from industrial processes often contain a large number of unlabeled samples, while the number of labeled samples is small and the cost of manual labeling is high, an active learning method based on covariance matrix is proposed. This method uses labeled samples to establish a Gaussian process regression model, and constructs the covariance matrix between the unlabeled samples, using the value of the determinant of the covariance matrix as an evaluation indicator. While selecting informative unlabeled samples, the similarity between samples is measured to avoid redundant addition of samples, which finally improves model prediction accuracy …
Research On Algebraic Loop Of Synchronous Generator Simulation Based On Simulink, Shuang Wang, Zhaohui Gao, Siyu Chen, Xiao Tang, Zhan Xi
Research On Algebraic Loop Of Synchronous Generator Simulation Based On Simulink, Shuang Wang, Zhaohui Gao, Siyu Chen, Xiao Tang, Zhan Xi
Journal of System Simulation
Abstract: The problem of algebraic loop is common in Simulink simulation. The existence of algebraic loop will reduce the speed and accuracy of simulation, and even lead to errors in simulation results. Taking the simulation of synchronous generator as an example, the problem of algebraic loop and its elimination method in Simulink simulation are discussed. Starting from the analysis of the basic equations of synchronous generator, the cause of algebraic loop in simulation is discussed, the influence of the algebraic loop on the system simulation is pointed out, using disassembly method and transformation method, focusing on eliminating the algebraic loop, …
An Improved Atomic Search Algorithm, Jianfeng Li, Di Lu, Hexiang Li
An Improved Atomic Search Algorithm, Jianfeng Li, Di Lu, Hexiang Li
Journal of System Simulation
Abstract: The atom search algorithm (ASO) is a new optimization algorithm proposed by imitating the movement of atoms in the natural world. An improved atomic search algorithm (IASO) is proposed to address the problems of prematureness and slow convergence of ASO in solving complex functions. IASO adds the binding force generated by the historical optimal solution of individual atoms to correct the acceleration of ASO and enhance the global search capability. The two multiplier coefficients are adaptively updated to coordinate the algorithm's global search and local development capabilities. The Gaussian mutation strategy is used to re-update the atomic position and …
Research On The Simulation Method Of Urban Rail Transit Feedback Assignment, Jianpeng Hu, Xia Luo
Research On The Simulation Method Of Urban Rail Transit Feedback Assignment, Jianpeng Hu, Xia Luo
Journal of System Simulation
Abstract: Based on the characteristics of a large number of transfer routes in rail transit network, an improved depth first search algorithm is proposed to get the effective travel time of transfer routes between stations. Based on passenger entry and exit timing obtained from the automatic fare collection (AFC) data, the connect relationship between passengers and trains in time and route is obtained from the arrival time and route selection behavior of passengers. Considering the difference of route choice behavior between departure passenger and transfer passenger, the two are distinguished from each other. The dynamically updated travel …
Simulation Of Robust Optimal Synchronization Control For Direct Drive H-Type Motion Platform, Limei Wang, Hongyan Yao, Kang Zhang
Simulation Of Robust Optimal Synchronization Control For Direct Drive H-Type Motion Platform, Limei Wang, Hongyan Yao, Kang Zhang
Journal of System Simulation
Abstract: Cell manufacturing is an important organizational form of modern production systems. In scheduling of cell manufacturing systems, machine failures or interruptions are very common in practice, meanwhile the waste due to energy consumption during machine idle time cannot be ignored. Hence the relevant research is with strong significance. This paper considers the problems of machine interruption and energy consumption in cell scheduling, and developed an integer programming model to minimize the makespan as well as the cost of energy consumption during machine idling and the interruption cost. A mixed optimization method is proposed based on improved wolf pack algorithm …
Modeling Time Series Using Multi-Modality Fuzzy Cognitive Maps, Guoliang Feng, Wei Lu, Jianhua Yang
Modeling Time Series Using Multi-Modality Fuzzy Cognitive Maps, Guoliang Feng, Wei Lu, Jianhua Yang
Journal of System Simulation
Abstract: A multi-modality modeling method for time series data based on fuzzy cognitive maps is proposed to address the problem that a single model is difficult to accurately reflect the multi-modal characteristics of time series.The bootstrap method is used to select multiple sub-sequences from the original time serieswhich contain the diverse modality in the original time series. The fuzzy cognitive map sub-models are constructed on each sub-sequencesrespectively. The formed sub-models are further merged by means of granular computing method and the merging performance with different weighting strategies is analyzed. The developed multi-modal model not only has prediction abilities at …
Research On Information Flow Integrated M&S Method For Project Type Manufacturing Process, Mindong Liu, Longjun Wu, Mingchao Tang, Mei Meng
Research On Information Flow Integrated M&S Method For Project Type Manufacturing Process, Mindong Liu, Longjun Wu, Mingchao Tang, Mei Meng
Journal of System Simulation
Abstract: The project type manufacturing process is quite common in shipbuilding and construction industries. Aiming at the problem that the existing discrete manufacturing system modeling and simulation method for flow shop cannot effectively express and imitate this process, taking shipyard dock shop hoisting process as an example, we analyze its components structure, propose a working network-centric, information flow and work flow integrated simulation modelling method, and design a dedicated simulation algorithm with the task process interactive idea. A prototype simulation program is developed with Python language, and the effectiveness of the proposed modelling and simulation method is verified through …
Research On Optimization Of Network Resource Utilization In Static Segment Of Flexray Bus, Xinhang He, Erkang Li, Hongchao Zhang
Research On Optimization Of Network Resource Utilization In Static Segment Of Flexray Bus, Xinhang He, Erkang Li, Hongchao Zhang
Journal of System Simulation
Abstract: In order to improve the utilization of the network resources of the FlexRay bus, the network is optimized for static segment scheduling. The FlexRay communication mechanism is analyzed, the message model is established and the calculation method of bandwidth loss is derived, while considering the protocol overhead and network idling, taking the number of static frames and the length of the static frame payload as design variables, the overall optimal packaging scheme is obtained by solving this multi-objective optimization problem. This solution is finally applied to the vehicle chassis integrated control system for simulation analysis and verification. The results …
Research On Joint Optimization Of Energy-Saving Distributed Manufacturing And Preventive Maintenance For Semiconductor Wafers, Jun Dong, Chunming Ye
Research On Joint Optimization Of Energy-Saving Distributed Manufacturing And Preventive Maintenance For Semiconductor Wafers, Jun Dong, Chunming Ye
Journal of System Simulation
Abstract: Aiming at the joint optimization problem of energy-saving distributed manufacturing and preventive maintenance for semiconductor wafers, a two-stage green scheduling model considering both the manufacturing stage and the inspection and repair stage is established to minimize the makespan, the total carbon emissions and the total preventive maintenance cost. An improved hybrid multi-objective grey wolf optimization (IHMGWO)algorithm is proposed. The decoding schemes of factory allocation strategy, machine allocation strategy and synchronous scheduling maintenance strategy considering the flexibility of maintenance workers are designed in IHMGWO. By designing the initial population fusion strategy, predation behavior search strategy, and sub-population mutation strategy, the …
Research On The Construction Method Of Simulation Evaluation Index Of Operation Effectiveness Operation Concept Traction, Ziwei Zhang, Liang Li, Zhiming Dong, Yifei Wang, Li Duan
Research On The Construction Method Of Simulation Evaluation Index Of Operation Effectiveness Operation Concept Traction, Ziwei Zhang, Liang Li, Zhiming Dong, Yifei Wang, Li Duan
Journal of System Simulation
Abstract: Agents are difficult to be directly modeled and simulated due to the complexity of their own interaction and learning behaviors. Aiming at the common problems in the discrete simulation of the agent, the event transfer mechanism of the discrete event system specification (DEVS) atomic model is applied to express the interaction and learning of an agent. Through the interaction mode of the agent, the transfer control of multi-state external events, the port connection mode, as well as the introduction of reinforcement learning event transfer representation, a discrete simulation construction method of the agent based on the DEVS atomic model …
Path-Based Model For The Heterogeneous-Fleet Electric Vehicle Routing Problem With Partial Linear Recharging, Weiquan Wang, Ding Ding, Linsha Yan
Path-Based Model For The Heterogeneous-Fleet Electric Vehicle Routing Problem With Partial Linear Recharging, Weiquan Wang, Ding Ding, Linsha Yan
Journal of System Simulation
Abstract: The heterogeneous-fleet electric vehicle routing problem with partial linear recharging is studied for realistic logistics distribution scenarios using multiple electric vehicle fleets with different transport capacities, driving ranges and acquisition costs. A path-based mixed integer linear model is proposed. The model enumerates the paths visited by all vehicle types between any non-charging nodes, eliminates the infeasible paths through capacity constraints and time window constraints, and eliminates the dominated paths by the dominance criterion. Compared with the traditional charging station replica-based model, this model eliminates the need to set the number of charging station replicas. The results show that the …
Identifying Characteristics For Success Of Robotic Process Automations, Charles M. Unkrich
Identifying Characteristics For Success Of Robotic Process Automations, Charles M. Unkrich
Theses and Dissertations
In the pursuit of digital transformation, the Air Force creates digital airmen. Digital airmen are robotic process automations designed to eliminate the repetitive high-volume low-cognitive tasks that absorb so much of our Airmen's time. The automation product results in more time to focus on tasks that machines cannot sufficiently perform data analytics and improving the Air Force's informed decision-making. This research investigates the assessment of potential automation cases to ensure that we choose viable tasks for automation and applies multivariate analysis to determine which factors indicate successful projects. The data is insufficient to provide significant insights.
Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds, Noah M. Miller
Bayesian Convolutional Neural Network With Prediction Smoothing And Adversarial Class Thresholds, Noah M. Miller
Theses and Dissertations
Using convolutional neural networks (CNNs) for image classification for each frame in a video is a very common technique. Unfortunately, CNNs are very brittle and have a tendency to be over confident in their predictions. This can lead to what we will refer to as “flickering,” which is when the predictions between frames jump back and forth between classes. In this paper, new methods are proposed to combat these shortcomings. This paper utilizes a Bayesian CNN which allows for a distribution of outputs on each data point instead of just a point estimate. These distributions are then smoothed over multiple …
Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice
Team Air Combat Using Model-Based Reinforcement Learning, David A. Mottice
Theses and Dissertations
We formulate the first generalized air combat maneuvering problem (ACMP), called the MvN ACMP, wherein M friendly AUCAVs engage against N enemy AUCAVs, developing a Markov decision process (MDP) model to control the team of M Blue AUCAVs. The MDP model leverages a 5-degree-of-freedom aircraft state transition model and formulates a directed energy weapon capability. Instead, a model-based reinforcement learning approach is adopted wherein an approximate policy iteration algorithmic strategy is implemented to attain high-quality approximate policies relative to a high performing benchmark policy. The ADP algorithm utilizes a multi-layer neural network for the value function approximation regression mechanism. One-versus-one …
The Impact Of Visual Feedback And Control Configuration On Pilot-Aircraft Interface Using Head Tracking Technology, Christopher M. Arnold
The Impact Of Visual Feedback And Control Configuration On Pilot-Aircraft Interface Using Head Tracking Technology, Christopher M. Arnold
Theses and Dissertations
Traditional control mechanisms restrict human input on the displays in 5th generation aircraft. This research explored methods for enhancing pilot interaction with large, information dense cockpit displays; specifically, the effects of visual feedback and control button configuration when augmenting cursor control with head tracking technology. Previous studies demonstrated that head tracking can be combined with traditional cursor control to decrease selection times but can increase pilot mental and physical workload. A human subject experiment was performed to evaluate two control button configurations and three visual feedback conditions. A Fitts Law analysis was performed to create predictive models of selection time …
A Thematic And Reference Analysis Of Touchless Technologies, Eric R. Curia
A Thematic And Reference Analysis Of Touchless Technologies, Eric R. Curia
Theses and Dissertations
The purpose of this research is to explore the utility and current state of touchless technologies. Five categories of technologies are identified as a result of collecting and reviewing literature: facial/biometric recognition, gesture recognition, touchless sensing, personal devices, and voice recognition. A thematic analysis was conducted to evaluate the advantages and disadvantages of the five categories. A reference analysis was also conducted to determine the similarities between articles in each category. Touchless sensing showed to have the most advantages and least similar references. Gesture recognition was the opposite. Comparing analyses shows more reliable technology types are more beneficial and diverse.
Analysis Of Generalized Artificial Intelligence Potential Through Reinforcement And Deep Reinforcement Learning Approaches, Jonathan Turner
Analysis Of Generalized Artificial Intelligence Potential Through Reinforcement And Deep Reinforcement Learning Approaches, Jonathan Turner
Theses and Dissertations
Artificial Intelligence is the next competitive domain; the first nation to develop human level artificial intelligence will have an impact similar to the development of the atomic bomb. To maintain the security of the United States and her people, the Department of Defense has funded research into the development of artificial intelligence and its applications. This research uses reinforcement learning and deep reinforcement learning methods as proxies for current and future artificial intelligence agents and to assess potential issues in development. Agent performance were compared across two games and one excursion: Cargo Loading, Tower of Hanoi, and Knapsack Problem, respectively. …
Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price
Applying Models Of Circadian Stimulus To Explore Ideal Lighting Configurations, Alexander J. Price
Theses and Dissertations
Increased levels of time are spent indoors, decreasing human interaction with nature and degrading photoentrainment, the synchronization of circadian rhythms with daylight variation. Military imagery analysts, among other professionals, are required to work in low light level environments to limit power consumption or increase contrast on display screens to improve detail detection. Insufficient exposure to light in these environments results in inadequate photoentrainment which is associated with degraded alertness and negative health effects. Recent research has shown that both the illuminance (i.e., perceived intensity) and wavelength of light affect photoentrainment. Simultaneously, modern lighting technologies have improved our ability to construct …
Approximate Dynamic Programming For An Unmanned Aerial Vehicle Routing Problem With Obstacles And Stochastic Target Arrivals, Kassie M. Gurnell
Approximate Dynamic Programming For An Unmanned Aerial Vehicle Routing Problem With Obstacles And Stochastic Target Arrivals, Kassie M. Gurnell
Theses and Dissertations
The United States Air Force is investing in artificial intelligence (AI) to speed analysis in efforts to modernize the use of autonomous unmanned combat aerial vehicles (AUCAVs) in strike coordination and reconnaissance (SCAR) missions. This research examines an AUCAVs ability to execute target strikes and provide reconnaissance in a SCAR mission. An orienteering problem is formulated as anMarkov decision process (MDP) model wherein a single AUCAV must optimize its target route to aid in eliminating time-sensitive targets and collect imagery of requested named areas of interest while evading surface-to-air missile (SAM) battery threats imposed as obstacles. The AUCAV adjusts its …
Coordinated Delivery To Shopping Malls With Limited Docking Capacity, Ruidian Song, Hoong Chuin Lau, Xue Luo, Lei Zhao
Coordinated Delivery To Shopping Malls With Limited Docking Capacity, Ruidian Song, Hoong Chuin Lau, Xue Luo, Lei Zhao
Research Collection School Of Computing and Information Systems
Shopping malls are densely located in major cities such as Singapore and Hong Kong. Tenants in these shopping malls generate a large number of freight orders to their contracted logistics service providers, who independently plan their own delivery schedules. These uncoordinated deliveries and limited docking capacity jointly cause congestion at the shopping malls. A delivery coordination platform centrally plans the vehicle routes for the logistics service providers and simultaneously schedules the dock time slots at the shopping malls for the delivery orders. Vehicle routing and dock scheduling decisions need to be made jointly against the backdrop of travel time and …
The Impact Of Ride-Hail Surge Factors On Taxi Bookings, Sumit Agarwal, Ben Charoenwong, Shih-Fen Cheng, Jussi Keppo
The Impact Of Ride-Hail Surge Factors On Taxi Bookings, Sumit Agarwal, Ben Charoenwong, Shih-Fen Cheng, Jussi Keppo
Research Collection School Of Computing and Information Systems
We study the role of ride-hailing surge factors on the allocative efficiency of taxis by combining a reduced-form estimation with structural analyses using machine-learning-based demand predictions. Where other research study the effect of entry on incumbent taxis, we use higher frequency granular data to study how location-time-specific surge factors affect taxi bookings to bound the effect of customer decisions while accounting for various confounding variables. We find that even in a unique market like Singapore, where incumbent taxi companies have app-based booking systems similar to those from ride-hailing companies like Uber, the estimated upper bound on the cross-platform substitution between …
Hybrid Tabu Search Algorithm For Unrelated Parallel Machine Scheduling In Semiconductor Fabs With Setup Times, Job Release, And Expired Times, Changyu Chen, Madhi Fathi, Marzieh Khakifirooz, Kan Wu
Hybrid Tabu Search Algorithm For Unrelated Parallel Machine Scheduling In Semiconductor Fabs With Setup Times, Job Release, And Expired Times, Changyu Chen, Madhi Fathi, Marzieh Khakifirooz, Kan Wu
Research Collection School Of Computing and Information Systems
This research is motivated by a scheduling problem arising in the ion implantation process of wafer fabrication. The ion implementation scheduling problem is modeled as an unrelated parallel machine scheduling (UPMS) problem with sequence-dependent setup times that are subject to job release time and expiration time of allowing a job to be processed on a specific machine, defined as: R|rj,eij,STsd|Cmax. The objective is first to maximize the number of processed jobs, then minimize the maximum completion time (makespan), and finally minimize the maximum completion times of the non-bottleneck machines. A mixed-integer programming (MIP) model is proposed as a solution approach …
Advancing Ubiquitous Collaboration For Telehealth - A Framework To Evaluate Technology-Mediated Collaborative Workflow For Telehealth, Hypertension Exam Workflow Study, Christopher Bondy Ph.D., Linlin Chen Ph.D, Pamela Grover Md, Pengcheng Shi Ph.D
Advancing Ubiquitous Collaboration For Telehealth - A Framework To Evaluate Technology-Mediated Collaborative Workflow For Telehealth, Hypertension Exam Workflow Study, Christopher Bondy Ph.D., Linlin Chen Ph.D, Pamela Grover Md, Pengcheng Shi Ph.D
Articles
Healthcare systems are under siege globally regarding technology adoption; the recent pandemic has only magnified the issues. Providers and patients alike look to new enabling technologies to establish real-time connectivity and capability for a growing range of remote telehealth solutions. The migration to new technology is not as seamless as clinicians and patients would like since the new workflows pose new responsibilities and barriers to adoption across the telehealth ecosystem. Technology-mediated workflows (integrated software and personal medical devices) are increasingly important in patient-centered healthcare; software-intense systems will become integral in prescribed treatment plans [1]. My research explored the path to …
Job Scheduling And Simulation In Cloud Based On Deep Reinforcement Learning, Qirui Li, Xinyi Peng
Job Scheduling And Simulation In Cloud Based On Deep Reinforcement Learning, Qirui Li, Xinyi Peng
Journal of System Simulation
Abstract: To solve the difficulty in job scheduling in the complex and transient multi-user, multi-queue, and multi-data-center cloud computing environment, this paper proposed a job scheduling method based on deep reinforcement learning. A system model of cloud job scheduling and its mathematical model were built, and an optimization goal consisting of transmission time, waiting time, and execution time was obtained. A job scheduling algorithm based on deep reinforcement learning was designed, and its state space, action space, and reward function were given. A simulated cloud job scheduler was designed and developed, and simulated scheduling experiments were conducted on it. The …
Multi-Floor Evacuation Model Based On Wavelet Neural Network, Juan Wei, Lei You, Yangyong Guo, Zhihai Tang
Multi-Floor Evacuation Model Based On Wavelet Neural Network, Juan Wei, Lei You, Yangyong Guo, Zhihai Tang
Journal of System Simulation
Abstract: Crowd evacuation in a multi-floor environment is a popular social concern, while the stagnation phenomenon easily occurs when simulating a multi-floor complex environment with the traditional social force model. Therefore, An improved social force model is proposed by a wavelet neural network, and a new multi-floor evacuation model is built. In the model, a pedestrian's direction of movement is obtained by the field model, which is used as the self-driving direction of the social force model. Meanwhile, the evaluation indexes of the exit congestion degree, path congestion degree, and average velocity in a multi-floor environment are given, and a …
Research On Semantic Segmentation Of Natural Landform Based On Edge Detection Module, Qizong Shen, Chunyan Gao
Research On Semantic Segmentation Of Natural Landform Based On Edge Detection Module, Qizong Shen, Chunyan Gao
Journal of System Simulation
Abstract: To classify pixels of natural landform edges in remote sensing images, this paper proposes a multi-channel fusion model and a decoder-side module model both integrating an edge detection module. The edge detection module takes the Canny operator as the base to perform closed operations and mean filtering, as a result of which accurate image edges can be achieved. Based on DeepLabV3+, the semantic segmentation network is connected with an edge planning module in parallel at encoder and decoder sides respectively. The experimental results show that the two improved networks can achieve a better segmentation effect on a high-resolution natural …
Zoomfft-Based Demodulation Algorithm For Underwater Acoustic Ofdm Signals, Qing Guo, Angdi Li, Jing Wu, Haitao Su
Zoomfft-Based Demodulation Algorithm For Underwater Acoustic Ofdm Signals, Qing Guo, Angdi Li, Jing Wu, Haitao Su
Journal of System Simulation
Abstract: The picket fence effect of fast Fourier transform (FFT) restricts the demodulation performance of the underwater acoustic(UWA) communication systemusing orthogonal frequency division multiplexing (OFDM). To solve this problem, we propose a demodulation algorithm based on ZoomFFT. Specifically, the received signal is processed by frequency shifting and downsampling forarefined spectrum, which improves the spectralresolution and weakens the picketfence effect.Meanwhile, the channel response is refined, and the channel equalization algorithm is constructed on the basis of the minimum mean square error (MMSE) principle to eliminate the channel influence. Simulations show that the performance of underwater acoustic OFDM demodulation algorithm based on …
Design Of Fatigue Driving Detection System Based On Cascaded Neural Network, Bangqian Ao, Sha Yang, Jinqing Linghu, Zhenhuan Ye
Design Of Fatigue Driving Detection System Based On Cascaded Neural Network, Bangqian Ao, Sha Yang, Jinqing Linghu, Zhenhuan Ye
Journal of System Simulation
Abstract: An algorithm is proposed to greatly improves the face detection rate and ensures the accuracy by adjusting the size of input images, expanding the minimum face size, and reducing the scaling ratio between layers of the detection window. The detection efficiency of this algorithm is 18 times higher than that of the original MTCNN. By building a new CNN structure model for the detection of eyes and mouths, we can achieve network detection accuracy of 95.6%. The proposed network is cascaded with the original MTCNN to continue classifying and locating the eyes and mouth in the formerly …
Segmentation Line Detection In Dental Model Based On Target Region Constraint, Tian Ma, Yun Li, Jiaojiao Li, Yuancheng Li
Segmentation Line Detection In Dental Model Based On Target Region Constraint, Tian Ma, Yun Li, Jiaojiao Li, Yuancheng Li
Journal of System Simulation
Abstract: It is an important pretreatment of a virtual orthodontic system to accurately segment teeth from a dental model. In the present methods, all patches are computed directly. To solve this problem, this paper proposes a segmentation line detection method based on target region constraint, which narrows down the detection range to the area around the actual segmentation line. In this method, the cutting plane and the cutting line are automatically formed according to the positions of seed points. The detection range is determined by the search for the position with the greatest negative curvature on the cutting line. The …