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Articles 6781 - 6810 of 11294

Full-Text Articles in Artificial Intelligence and Robotics

Knowledge Enhanced Neural Fashion Trend Forecasting, Yunshan Ma, Yujuan Ding, Xun Yang, Lizi Liao, Wai Keung Wong, Tat-Seng Chua Oct 2020

Knowledge Enhanced Neural Fashion Trend Forecasting, Yunshan Ma, Yujuan Ding, Xun Yang, Lizi Liao, Wai Keung Wong, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Fashion trend forecasting is a crucial task for both academia and industry. Although some efforts have been devoted to tackling this challenging task, they only studied limited fashion elements with highly seasonal or simple patterns, which could hardly reveal the real fashion trends. Towards insightful fashion trend forecasting, this work focuses on investigating fine-grained fashion element trends for specific user groups. We first contribute a large-scale fashion trend dataset (FIT) collected from Instagram with extracted time series fashion element records and user information. Furthermore, to effectively model the time series data of fashion elements with rather complex patterns, we propose …

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The Future Of Work Now: Automl At 84.51°And Kroger, Thomas H. Davenport, Steven M. Miller Oct 2020

The Future Of Work Now: Automl At 84.51°And Kroger, Thomas H. Davenport, Steven M. Miller

Research Collection School Of Computing and Information Systems

One of the most frequently-used phrases at business events these days is “the future of work.” It’s increasingly clear that artificial intelligence and other new technologies will bring substantial changes in work tasks and business processes. But while these changes are predicted for the future, they’re already present in many organizations for many different jobs. The job and incumbents described below are an example of this phenomenon.

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Foodbot: A Goal-Oriented Just-In-Time Healthy Eating Interventions Chatbot, Philips Kokoh Prasetyo, Palakorn Achananuparp, Ee-Peng Lim Oct 2020

Foodbot: A Goal-Oriented Just-In-Time Healthy Eating Interventions Chatbot, Philips Kokoh Prasetyo, Palakorn Achananuparp, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Recent research has identified a few design flaws in popular mobile health (mHealth) applications for promoting healthy eating lifestyle, such as mobile food journals. These include tediousness of manual food logging, inadequate food database coverage, and a lack of healthy dietary goal setting. To address these issues, we present Foodbot, a chatbot-based mHealth application for goal-oriented just-in-time (JIT) healthy eating interventions. Powered by a large-scale food knowledge graph, Foodbot utilizes automatic speech recognition and mobile messaging interface to record food intake. Moreover, Foodbot allows users to set goals and guides their behavior toward the goals via JIT notification prompts, interactive …

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Online Traffic Signal Control Through Sample-Based Constrained Optimization, Srishti Dhamija, Alolika Gon, Pradeep Varakantham, William Yeoh Oct 2020

Online Traffic Signal Control Through Sample-Based Constrained Optimization, Srishti Dhamija, Alolika Gon, Pradeep Varakantham, William Yeoh

Research Collection School Of Computing and Information Systems

Traffic congestion reduces productivity of individuals by increasing time spent in traffic and also increases pollution. To reduce traffic congestion by better handling dynamic traffic patterns, recent work has focused on online traffic signal control. Typically, the objective in traffic signal control is to minimize expected delay over all vehicles given the uncertainty associated with the vehicle turn movements at intersections. In order to ensure responsiveness in decision making, a typical approach is to compute a schedule that minimizes the delay for the expected scenario of vehicle movements instead of minimizing expected delay over the feasible vehicle movement scenarios. Such …

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Reinforcement Learning For Zone Based Multiagent Pathfinding Under Uncertainty, Jiajing Ling, Tarun Gupta, Akshat Kumar Oct 2020

Reinforcement Learning For Zone Based Multiagent Pathfinding Under Uncertainty, Jiajing Ling, Tarun Gupta, Akshat Kumar

Research Collection School Of Computing and Information Systems

We address the problem of multiple agents finding their paths from respective sources to destination nodes in a graph (also called MAPF). Most existing approaches assume that all agents move at fixed speed, and that a single node accommodates only a single agent. Motivated by the emerging applications of autonomous vehicles such as drone traffic management, we present zone-based path finding (or ZBPF) where agents move among zones, and agents' movements require uncertain travel time. Furthermore, each zone can accommodate multiple agents (as per its capacity). We also develop a simulator for ZBPF which provides a clean interface from the …

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Dual-Slam: A Framework For Robust Single Camera Navigation, Huajian Huang, Wen-Yan Lin, Siying Liu, Dong Zhang, Sai-Kit Yeung Oct 2020

Dual-Slam: A Framework For Robust Single Camera Navigation, Huajian Huang, Wen-Yan Lin, Siying Liu, Dong Zhang, Sai-Kit Yeung

Research Collection School Of Computing and Information Systems

SLAM (Simultaneous Localization And Mapping) seeks to provide a moving agent with real-time self-localization. To achieve real-time speed, SLAM incrementally propagates position estimates. This makes SLAM fast but also makes it vulnerable to local pose estimation failures. As local pose estimation is ill-conditioned, local pose estimation failures happen regularly, making the overall SLAM system brittle. This paper attempts to correct this problem. We note that while local pose estimation is ill-conditioned, pose estimation over longer sequences is well-conditioned. Thus, local pose estimation errors eventually manifest themselves as mapping inconsistencies. When this occurs, we save the current map and activate two …

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Co-Design And Evaluation Of An Intelligent Decision Support System For Stroke Rehabilitation Assessment, Min Hun Lee, Daniel P. Siewiorek, Asim Smailagic, Alexandre Bernardino, Sergi Badia Oct 2020

Co-Design And Evaluation Of An Intelligent Decision Support System For Stroke Rehabilitation Assessment, Min Hun Lee, Daniel P. Siewiorek, Asim Smailagic, Alexandre Bernardino, Sergi Badia

Research Collection School Of Computing and Information Systems

Clinical decision support systems have the potential to improve work flows of experts in practice (e.g. therapist's evidence-based rehabilitation assessment). However, the adoption of these systems is challenging, and the gains of these systems have not fully demonstrated yet. In this paper, we identified the needs of therapists to assess patient's functional abilities (e.g. alternative perspectives with quantitative information on patient's exercise motions). As a result, we co-designed and developed an intelligent decision support system that automatically identifies salient features of assessment using reinforcement learning to assess the quality of motion and generate patient-specific analysis. We evaluated this system with …

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We Mind Your Well-Being: Preventing Depression In Uncertain Social Networks By Sequential Interventions, Aye Phye Phye Aung, Xinrun Wang, Bo An, Xiaoli Li Oct 2020

We Mind Your Well-Being: Preventing Depression In Uncertain Social Networks By Sequential Interventions, Aye Phye Phye Aung, Xinrun Wang, Bo An, Xiaoli Li

Research Collection School Of Computing and Information Systems

Mental health has become a major concern according to WHO who estimates that more than 350 million people worldwide are affected by depression. Studies have shown that interventions and social support can reduce stress and depression. However, counselling centers do not have enough resources to provide counselling and social support to all the participants in their interest. This paper helps social support organizations (e.g., university counselling centers) sequentially select the participants for interventions. Unfortunately, previous works do not consider emotion propagation from other neighbours of the influencees and initial uncertainties of mental states and influence. Moreover, they fail to scale …

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Modular Neural Networks For Low-Power Image Classification On Embedded Devices, Abhinav Goel, Sara Aghajanzadeh, Caleb Tung, Shuo-Han Chen, George K. Thiruvathukal, Yung-Hisang Lu Oct 2020

Modular Neural Networks For Low-Power Image Classification On Embedded Devices, Abhinav Goel, Sara Aghajanzadeh, Caleb Tung, Shuo-Han Chen, George K. Thiruvathukal, Yung-Hisang Lu

Computer Science: Faculty Publications and Other Works

Embedded devices are generally small, battery-powered computers with limited hardware resources. It is difficult to run deep neural networks (DNNs) on these devices, because DNNs perform millions of operations and consume significant amounts of energy. Prior research has shown that a considerable number of a DNN’s memory accesses and computation are redundant when performing tasks like image classification. To reduce this redundancy and thereby reduce the energy consumption of DNNs, we introduce the Modular Neural Network Tree architecture. Instead of using one large DNN for the classifier, this architecture uses multiple smaller DNNs (called modules) to progressively classify images …

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The Future Of Work Now: Ai-Driven Transaction Surveillance At Dbs Bank, Thomas H. Davenport, Steven M. Miller Oct 2020

The Future Of Work Now: Ai-Driven Transaction Surveillance At Dbs Bank, Thomas H. Davenport, Steven M. Miller

Research Collection School Of Computing and Information Systems

One of the most frequently-used phrases at business events these days is “the future of work.” It’s increasingly clear that artificial intelligence and other new technologies will bring substantial changes in work tasks and business processes. But while these changes are predicted for the future, they’re already present in many organizations for many different jobs. The job and incumbents described below are an example of this phenomenon. Steve Miller of Singapore Management University and I co-authored the story.

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Gesture Enhanced Comprehension Of Ambiguous Human-To-Robot Instructions, Weerakoon Mudiyanselage Dulanga Kaveesha Weerakoon, Vigneshwaran Subbaraju, Nipuni Karumpulli, Minh Anh Tuan Tran, Qianli Xu, U-Xuan Tan, Joo Hwee Lim, Archan Misra Oct 2020

Gesture Enhanced Comprehension Of Ambiguous Human-To-Robot Instructions, Weerakoon Mudiyanselage Dulanga Kaveesha Weerakoon, Vigneshwaran Subbaraju, Nipuni Karumpulli, Minh Anh Tuan Tran, Qianli Xu, U-Xuan Tan, Joo Hwee Lim, Archan Misra

Research Collection School Of Computing and Information Systems

This work demonstrates the feasibility and benefits of using pointing gestures, a naturally-generated additional input modality, to improve the multi-modal comprehension accuracy of human instructions to robotic agents for collaborative tasks.We present M2Gestic, a system that combines neural-based text parsing with a novel knowledge-graph traversal mechanism, over a multi-modal input of vision, natural language text and pointing. Via multiple studies related to a benchmark table top manipulation task, we show that (a) M2Gestic can achieve close-to-human performance in reasoning over unambiguous verbal instructions, and (b) incorporating pointing input (even with its inherent location uncertainty) in M2Gestic results in a significant …

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Chess As A Testing Grounds For The Oracle Approach To Ai Safety, James D. Miller, Roman Yampolskiy, Olle Häggström, Stuart Armstrong Sep 2020

Chess As A Testing Grounds For The Oracle Approach To Ai Safety, James D. Miller, Roman Yampolskiy, Olle Häggström, Stuart Armstrong

Faculty and Staff Scholarship

To reduce the danger of powerful super-intelligent AIs, we might make the first such AIs oracles that can only send and receive messages. This paper proposes a possibly practical means of using machine learning to create two classes of narrow AI oracles that would provide chess advice: those aligned with the player's interest, and those that want the player to lose and give deceptively bad advice. The player would be uncertain which type of oracle it was interacting with. As the oracles would be vastly more intelligent than the player in the domain of chess, experience with these oracles might …

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Trainable Structure Tensors For Autonomous Baggage Threat Detection Under Extreme Occlusion, Taimur Hassan, Samet Akçay, Mohammed Bennamoun, Salman Khan, Naoufel Werghi Sep 2020

Trainable Structure Tensors For Autonomous Baggage Threat Detection Under Extreme Occlusion, Taimur Hassan, Samet Akçay, Mohammed Bennamoun, Salman Khan, Naoufel Werghi

Computer Vision Faculty Publications

Detecting baggage threats is one of the most difficult tasks, even for expert officers. Many researchers have developed computer-aided screening systems to recognize these threats from the baggage X-ray scans. However, all of these frameworks are limited in identifying the contraband items under extreme occlusion. This paper presents a novel instance segmentation framework that utilizes trainable structure tensors to highlight the contours of the occluded and cluttered contraband items (by scanning multiple predominant orientations), while simultaneously suppressing the irrelevant baggage content. The proposed framework has been extensively tested on four publicly available X-ray datasets where it outperforms the state-of-the-art frameworks …

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Eeg Classification Based On Multi-Domain Features And Random Subspace Ensemble, Deng Xin, Can Long, Jianxun Mi, Boxian Zhang, Kaiwei Sun, Wang Jin Sep 2020

Eeg Classification Based On Multi-Domain Features And Random Subspace Ensemble, Deng Xin, Can Long, Jianxun Mi, Boxian Zhang, Kaiwei Sun, Wang Jin

Journal of System Simulation

Abstract: Aiming at the preprocessing feature extraction and classification recognition in BCI system, a method for EEG classification of motion imagery based on random subspaces ensemble learning of multi-domain features is proposed. Based on the analysis on the ERD/ERS characteristics of motion imagery (MI) signals, the multi-domain features of best effective time and frequency bands are extracted as the feature vectors, and the scale of the random subspace ensemble with cross-validation is adaptively chosen, and the EEG classification is realized by using linear discriminant analysis (LDA) classifiers ensemble. The test results show that the accuracy of the multi-domain features and …

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The Expansion From System Simulation To Domain Simulation, Xiaogang Qiu, Yazhou Chen, Zhang Peng Sep 2020

The Expansion From System Simulation To Domain Simulation, Xiaogang Qiu, Yazhou Chen, Zhang Peng

Journal of System Simulation

Abstract: With the generalization of simulation application and complex system simulation becoming the focus, domain simulation is becoming more and more important. In 1995 United States Department of Defense (DoD) presented the master plan of modeling and simulation, which gives birth to the basic idea of domain simulation. The advances in information technology such as network technology and cloud computing help domain simulation to access to use. Taking the change of simulation research object as the basis, the development of simulation research from the aspects of model researches, simulation tools and simulation applications are summarized. The goal of domain simulation …

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Review On Agv Scheduling Optimization, Jianlin Fu, Hengzhi Zhang, Zhang Jian, Liangkui Jiang Sep 2020

Review On Agv Scheduling Optimization, Jianlin Fu, Hengzhi Zhang, Zhang Jian, Liangkui Jiang

Journal of System Simulation

Abstract: AGV scheduling plays an important role in improving the efficiency and reducing manufacturing cost, but it is also a very complex combinatorial optimization procedure. AGV scheduling optimization is divided into three types, AGV static scheduling, AGV dynamic scheduling and AGV simultaneous scheduling with other resources scheduling. Various methods are summarized and listed, including traditional analysis method, modeling and simulation method, intelligent optimization algorithm and hybrid optimization method, and the advantages and disadvantages of each method are also analyzed. The deficiencies of AGV scheduling research are pointed out and the research directions for future are presented.

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Evaluation On Geo-Registration Accuracy Of Outdoor Augmented Reality, Deng Chen, You Xiong, Meixia Zhi Sep 2020

Evaluation On Geo-Registration Accuracy Of Outdoor Augmented Reality, Deng Chen, You Xiong, Meixia Zhi

Journal of System Simulation

Abstract: Geo-registration technology is a key technology for the combination of augmented reality and geographic information systems, and its registration accuracy has a significant impact on the availability of ARGIS. Aiming at this application, the basic concepts and principles of augmented reality geo-registration technology are analyzed, and the method for quantitative evaluation of geo-registration accuracy is proposed. Combined with the pre-acquired high-precision geographic information data, a variety of outdoor geo-registration experiments are carried out by using the different hardware devices, and the quantitative accuracy of different geo-registration methods is evaluated. The geo-registration errors and the problems existing in the practical …

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Research On Recursive Variable Sampling Period Scheduling Algorithm Based On Two-Parameter Priority, Weiguo Shi, Xu Chao, Wang Xun, Xiangtai Wang Sep 2020

Research On Recursive Variable Sampling Period Scheduling Algorithm Based On Two-Parameter Priority, Weiguo Shi, Xu Chao, Wang Xun, Xiangtai Wang

Journal of System Simulation

Abstract: A recursive variable sampling periodic dynamic scheduling algorithm based on two-parameter priority is proposed for the resource-constrained network control system. The network demand degree and network urgency double parameter of the control loop are calculated, and the two-parameter weight is established by the two-square root mapping function which is created by the absolute value of the control loop error to realize the scheduling of the sensor priority. The comprehensive analysis of the control loop performance recursively adjusts the sampling period of each control loop, and completes the scheduling adjustment under the premise of ensuring the stability of the …

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Finite Element Method Evaluation On Chest Blunt Injury By Rubber Projectile, Wang Song, Renjun Zhan, Xiongyi Duan Sep 2020

Finite Element Method Evaluation On Chest Blunt Injury By Rubber Projectile, Wang Song, Renjun Zhan, Xiongyi Duan

Journal of System Simulation

Abstract: In order to reveal the non-lethal injury mechanism of rubber projectile and improve its safety service level, the 18.4 mm rubber projectile finite element model and the improved chest blunt injury assessment model are constructed and verified. The virtual impact test experiments under different loads are carried out, and the stress-time response and deformation-time response data are obtained. The results show that the time to reach the peak stress (less than 0.2 ms) is much shorter than the time to reach the maximum deformation variable (4~5 ms), which means the damage is not caused by the impact itself …

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Simulation Analysis On Penetration To Aircraft Carrier Of Image Homing Rocket, Shidong Fang, Chen Dong, Quanli Ning, Zhang Jie, Li Yong Sep 2020

Simulation Analysis On Penetration To Aircraft Carrier Of Image Homing Rocket, Shidong Fang, Chen Dong, Quanli Ning, Zhang Jie, Li Yong

Journal of System Simulation

Abstract: The effect of image homing rocket projectile penetrating aircraft carrier is the important basis for its operation. According to the characteristics of projectile and aircraft carrier, the geometric equivalent model and simulation model are established, and the penetration process is simulated by LS-DYNA. Simulation results are verified by the failure form and penetration limit velocity, and show the correctness of the model. Using the established models, the penetration processes are simulated under the different conditions. The overall force on the projectile is analyzed according to the extreme acceleration value of projectile. Based on the analysis of some collected key …

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Simulation On Vehicles Mandatory Lane Changing And Merging Process In Case Of Road Bottleneck, Lü Wei, Feizhou Huo Sep 2020

Simulation On Vehicles Mandatory Lane Changing And Merging Process In Case Of Road Bottleneck, Lü Wei, Feizhou Huo

Journal of System Simulation

Abstract: A microscopic dynamic traffic flow model based on vehicle's mandatory lane changing behavior is established. Under the condition of road bottleneck, three macroscopic traffic flow characteristics of traffic flow, lane speed distribution and space-time diagram, and two microscopic traffic flow characteristics of merging distance and vehicle's travel time are analyzed. The simulation results show that, the total flow of arbitrary cross section of the bottleneck road can represent the overall traffic capacity, and the road bottleneck can reduce the total traffic flow by 10% to 35%, and cause a delay of 17% to 42% to the vehicle travel time …

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Operation Loss Reduction Control For Large-Scale Wind Farm Based On Hybrid Modeling Simulation, Yunqi Xiao, Wang Yi Sep 2020

Operation Loss Reduction Control For Large-Scale Wind Farm Based On Hybrid Modeling Simulation, Yunqi Xiao, Wang Yi

Journal of System Simulation

Abstract: Due to the large number of transformers and collection lines in large-scale wind farms, the losses of collecting system is serious in actual operation. A reactive power/voltage control strategy is proposed, which takes wind turbines as the distributed reactive power sources to optimize the power flow in wind farm and reduce the overall losses of collector system. To improve the efficiency of wind farm modeling and multi-scene loss reduction simulation, a hybrid modeling and simulation scheme based on combining object model configuration and control algorithm programming is proposed. The wind farm model consists of module configuration, and can be …

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Delay Model Of Vehicles At Urban Road Drop-Off Area, Lifan Zhang, Pengpeng Jiao, Mingkai Si Sep 2020

Delay Model Of Vehicles At Urban Road Drop-Off Area, Lifan Zhang, Pengpeng Jiao, Mingkai Si

Journal of System Simulation

Abstract: A model for calculating the delay of the drop-off vehicles at urban road drop-off area is proposed. The traffic organization modes of the independent drop-off area and the road drop-off area are analysed. The “queue up to drop off” mode process is divided into two stages, a delay model of drop-off vehicle based on queuing theory and gap theory is established, and an optimization algorithm is presented. Taking the entrance section of Anzhen Hospital in Beijing as the test object, the model is tested by VISSIM simulation software and real survey data. The influence of drop-off rate and drop-off …

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Design Of Fragment Warhead Simulation System Based On Mvc Distributed Framework, He Miao, Wang Hao, Huang Yong, Xue Shao, Yinqing Shen Sep 2020

Design Of Fragment Warhead Simulation System Based On Mvc Distributed Framework, He Miao, Wang Hao, Huang Yong, Xue Shao, Yinqing Shen

Journal of System Simulation

Abstract: Numerical computation and visualization simulation are carried out for the whole physical process from the explosion of warhead to the fragments impacting target. The whole system is designed and implemented by using MVC architecture, Framework component library and JSON data format computer software technology, which make the system scalable, cross-platform and easy to maintain. The distributed computing architecture is designed according to the high computation, large data volume and multi-user concurrency in user scenarios. The simulation experiment results show that the distributed simulation of the system can satisfy the concurrent needs of multi-users, and the visual simulation effect …

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Combat Effectiveness Simulation Evaluation Framework Of Complex Weapon System, Yonglin Lei, Zhu Zhi, Bin Gan, Lei Sen, Chen Yong Sep 2020

Combat Effectiveness Simulation Evaluation Framework Of Complex Weapon System, Yonglin Lei, Zhu Zhi, Bin Gan, Lei Sen, Chen Yong

Journal of System Simulation

Abstract: Combat effectiveness evaluation of complex weapon system is a scientific issue both military departments and defense industry concern. Current researches on simulation-based weapon system combat effectiveness evaluation lack the specificity to complex weapon system and a simulation-based formal combat effectiveness evaluation framework is especially desired. A framework is created and formalized on three measure layers of performance-outcome-effectiveness. Within the framework, simulation inputs are classified into different categories different outcome measure layers and different effectiveness measure layers are considered. An example of combat effectiveness evaluation framework for typical ballistic missiles is presented to demonstrate the proposed framework.

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A Continuous Non-Invasive Blood Pressure Prediction Method Based On Improved Svr Learning, Haixia Fan, Xiaohui Chen Sep 2020

A Continuous Non-Invasive Blood Pressure Prediction Method Based On Improved Svr Learning, Haixia Fan, Xiaohui Chen

Journal of System Simulation

Abstract: Aiming at the accuracy of continuous non-invasmive monitoring of blood pressure by photoelectric method based on the photoplethysmography (PPG) signal and the electrocardiography (ECG) signal, is influenced by the differences of human characteristics, a blood pressure prediction method based on principal component analysis (PCA) and genetic algorithm (GA) to optimize machine learning model is proposed. The method processes the PPG signal, ECG signal and human body features to form a feature matrix, and uses an improved SVR learning model to perform regression training on the feature matrix and the real-time blood pressure value measured by the mercury sphygmomanometer. …

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Research On Geographical Battlefield Environment Model Facing Autonomous Platform, You Xiong, Jiangpeng Tian Sep 2020

Research On Geographical Battlefield Environment Model Facing Autonomous Platform, You Xiong, Jiangpeng Tian

Journal of System Simulation

Abstract: Battlefield environment model is an abstraction and description of the complex battlefield environment for specific needs. It supports the research and application of the nature and evolution of the battlefield environment. However, the existing battlefield environment model is mainly oriented to human war activities to describe the battlefield environment,and lacks the design for unmanned autonomous platforms. A multi-level battlefield environment model structure which couples the advantages of humans and machines is proposed, which can give full play to the machine's rapid numerical calculation capabilities at the geometric and feature levels, as well as human cognitive experience at the element, …

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Design And Simulation On Autonomous Landing Of A Quad Tilt Rotor, Supu Xiu, Yuanqiao Wen, Changshi Xiao, Haiwen Yuan, Wenqiang Zhan Sep 2020

Design And Simulation On Autonomous Landing Of A Quad Tilt Rotor, Supu Xiu, Yuanqiao Wen, Changshi Xiao, Haiwen Yuan, Wenqiang Zhan

Journal of System Simulation

Abstract: Aiming at the under-actuation of general quadrotors, a novel quad tilt rotor model is proposed. The model decouples the y-direction translation and roll rotation of a quadrotor by the four servos used respectively for the tilting control of the four propellers to realized the tilt hover and tilt flight of the UAV, the UAV can keep a tilt attitude which increases the maneuverability and the precise pose position and attitude control of the tilt UAV and ensures a good performance on the trajectory tracking and landing. A 5-degree polynomial optimization is used in UAV trajectory planning for the strong …

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Numerical Research On Ballistic Limit Of Whipple Shield In High-Velocity Range, Yixiao Li, Shengjie Wang Sep 2020

Numerical Research On Ballistic Limit Of Whipple Shield In High-Velocity Range, Yixiao Li, Shengjie Wang

Journal of System Simulation

Abstract: Limited by the acceleration ability of two-stage light gas guns, few hypervelocity impact experiment of Whipple shield with projectile speed higher than 8 km/s has been performed. The ballistic limit equations can't fully describe the protection ability of Whipple shield in high-velocity range because of the lack of experimental data. GRAY three-phase equation of state is used in the material point method calculation program to simulate the penetration of thick target plate and the high-velocity impact of Whipple shield. The numerical result of Whipple shield ballistic limit shows that the ballistic limit in high-velocity range is higher than the …

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Research On A Novel Biogeography-Based Optimization Algorithm Based On Ga, Wang Ning, Lisheng Wei Sep 2020

Research On A Novel Biogeography-Based Optimization Algorithm Based On Ga, Wang Ning, Lisheng Wei

Journal of System Simulation

Abstract: In order to further improve the optimization ability of biogeography-based optimization algorithm, a new genetic algorithm is proposed. The selection operation is added before the migration operation, and the migration individual is selected by the method of "roulette", so that the individuals with higher fitness can be preferentially migrated. The mutation operation combines the genetic gaussian mutation method, and the optimization performance of the algorithm is improved. The convergence condition of the method is derived in theory. Five test functions are used in the experiments, and the results prove that the ameliorated algorithm is better at the results of …

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