Multi-Uavs 3d Path Planning Method Based On Random Strategy Search,
2022
College of Information Engineering, Henan University of Science and Technology, Luoyang 471023, China;
Multi-Uavs 3d Path Planning Method Based On Random Strategy Search, Sen Zhang, Mengyan Zhang, Jingping Shao, Jiexin Pu
Journal of System Simulation
Abstract: In view of the difficulty of the traditional path planning method without energy consumption constraints to meet the emergency rescue requirements in the complex mountain operation environment, a three-dimensional path planning algorithm for multi-UAVs is proposed based on LSTM-DPPO(long short-term memory-distributed proximal policy optimization) framework. The LSTM long and short-term memory neural network is used to extract the important characteristic state information sequence of the multiple unmanned aerial vehicles in their respective flight process. After repeated iteration and updating, an optimal network parameter model is obtained. Combined with the energy consumption, the optimal 3D detection path is generated. …
Image Center Layout Optimization Method Based On Improved Genetic Algorithm,
2022
School of information and control engineering, Xi'an University of Architecture and Technology, Xi'an 710055, China;
Image Center Layout Optimization Method Based On Improved Genetic Algorithm, Zhijie Li, Haoqi Shi, Changhua Li, Jie Zhang
Journal of System Simulation
Abstract: Aiming at the layout optimization methods of image center being influenced by the subjective factors and low level of automation, a method of combining systematic layout planning(SLP) with the improved genetic algorithm is proposed. The layout scheme generated by SLP improves the initial population of the genetic algorithm and increases the diversity of the initial population. In order to improve the efficiency of optimization, the improved algorithm updates the crossover probability and mutation probability adaptively according to the evolution stages and the fitness value of the individuals. On the basis of the layout area model and multi-objective optimization mathematical …
Airport Flight Transit Support Time Collaborative Planning Modeling Based On Stn,
2022
1.College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China;2.Research Base of Aviation Ground Special Equipment, Civil Aviation University of China, Tianjin 300300, China;
Airport Flight Transit Support Time Collaborative Planning Modeling Based On Stn, Bin Chen, Yue Liu, Yalei Yang
Journal of System Simulation
Abstract: Under the constraint of resources, the collaborative planning of airport flight transit support time is one of the effective methods to improve airport operation efficiency. Based on Simple Temporal Network (STN), a planning model of flight transit support time is established. Based on the temporal decoupling, the shortest path matrix simplification, and the distance graph solving of STN task model considering resources, the method of collaborative planning of flight transit support time for airport considering resources is obtained. The comparison results of the simulation and the actual data show that STN task model considering resources can optimize the airport …
Vehicle Detection Method Based On Multi Scale Feature Fusion,
2022
College of Electronic Information Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China;
Vehicle Detection Method Based On Multi Scale Feature Fusion, Yin Wang, Feixiang Wang, Qianlai Sun
Journal of System Simulation
Abstract: Vehicle detection is the important research content and hotspot in the intelligent transportation. Aiming at the low detection accuracy and poor small-scale recognition effect of the traditional vehicle detection algorithm, an improved detection method based on YOLOv4(you only look once v4) is proposed to improve the detection performance of small target vehicles in traffic scenes. By redesigning the YOLOv4 network, the MobileNetv2 deep separable convolution module is used to replace the traditional convolution, and the convolutional block attention module (CBAM) attention module is integrated into the feature extraction network to ensure the detection accuracy of the model and reduce …
A Hybrid Algorithm Based On Seeker Optimization Algorithm And Salp Swarm Algorithm For Pid Parameters Optimization,
2022
1.The Faculty of Civil Engineering and Mechanics, Kunming University of Science and Technology, Kunming 650500, China;2.The Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China;
A Hybrid Algorithm Based On Seeker Optimization Algorithm And Salp Swarm Algorithm For Pid Parameters Optimization, Shaomi Duan, Huilong Luo, Haipeng Liu
Journal of System Simulation
Abstract: Aiming at the premature convergence of seeker optimization algorithm(SOA) during optimizing the global problems, a new SOA-SSA hybrid algorithm based on seeker optimization algorithm and salp swarm algorithm (SSA) is proposed.The SOA-SSA algorithm is based on a double population evolution strategy, in which some individuals of the population are evolved by seeker optimization algorithm and the rest are evolved from salp swarm algorithm. The individuals in SOA and SSA both employ an information sharing mechanism to realize the coevolution. These strategies increase the diversity of the population and avoid the premature convergence. The experimental results show that …
Application Of Improved Q Learning Algorithm In Job Shop Scheduling Problem,
2022
School of Artificial Intelligence, Shenyang University of Technology, Shenyang 110027, China;
Application Of Improved Q Learning Algorithm In Job Shop Scheduling Problem, Yejian Zhao, Yanhong Wang, Jun Zhang, Hongxia Yu, Zhongda Tian
Journal of System Simulation
Abstract: Aiming at the job shop scheduling in a dynamic environment, a dynamic scheduling algorithm based on an improved Q learning algorithm and dispatching rules is proposed. The state space of the dynamic scheduling algorithm is described with the concept of "the urgency of remaining tasks" and a reward function with the purpose of "the higher the slack, the higher the penalty" is disigned. In view of the problem that the greedy strategy will select the sub-optimal actions in the later stage of learning, the traditional Q learning algorithm is improved by introducing an action selection strategy based on the …
Visual Inspection Model Of Uav Cluster Based On Improved Pigeon Flock Hierarchy,
2022
1.Shantou Vocational and Technical College, Shantou 515000, China;
Visual Inspection Model Of Uav Cluster Based On Improved Pigeon Flock Hierarchy, Qi Chen, Haoyang Cui
Journal of System Simulation
Abstract: Aim at UAV being vulnerable to the environmental interference and the low efficiency of the traditional single-person-UAV model in the transmission line inspection, a visual inspection model for the power line by UAV is proposed based on the improved pigeon flock hierarchy. The initial landmark point of the UAV is generated based on GPS coordinates of the aircraft-carrying vehicle and the tower to be inspected, and the movement trajectory is planned. The return point of the UAV is used to update the initial landmark of onward UAV, which realizes the dynamic handover between the work-exchanging UAV, and the landmark …
Design Of Interactive Simulated Water Gun Fire Fighting Training System Based On Steam Vr,
2022
China People's Police University, Langfang 065000, China;
Design Of Interactive Simulated Water Gun Fire Fighting Training System Based On Steam Vr, Cheng Lu, Xuesheng Jin
Journal of System Simulation
Abstract: In order to save the fire fighting training resources and increase the immersion and experience of VR training, an interactive simulated water gun fire fighting training system based on Steam VR is designed. By using the Hall sensors and signal conversion circuit boards to collect and transmit the signal of the simulated water gun, and by using the Unity3D engine combined with the VIVE head-mounted display to build and present VR fire scene. The gun is controlled through C# programming to complete the interaction with the virtual fire scene. The system is evaluated by a post-questionnaire survey …
Application Of Observability In Performance Evaluation Of Photosynthesis Model,
2022
School of Internet of Things Engineering, Jiangnan university, Wuxi 214122, China;
Application Of Observability In Performance Evaluation Of Photosynthesis Model, Hongnai Gao, Lijiang Fu, Qian Xia, Ya Guo
Journal of System Simulation
Abstract: The photochemical reaction of photosynthesis involves a variety of physiological substances that cannot be directly measured. By modeling the control system, the state of these physiological substances can be es-timated based on the chlorophyll fluorescence, but the reliability of the state estimation is not given in all the reference documents. In response to this problem, based on the photochemical reaction kinetic model, the observability of the nonlinear system is introduced to evaluate the reliability of the state estimation. Aiming at the existing observability methods lacking the direct comparability due to the different dimensions of the components of different states, …
Fuzzy Super-Twisting Second Order Sliding Mode Trajectory Tracking Control For Robotic Manipulator,
2022
School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou 510006, China;
Fuzzy Super-Twisting Second Order Sliding Mode Trajectory Tracking Control For Robotic Manipulator, Baolin Du, Dachang Zhu, Yihua Pan
Journal of System Simulation
Abstract: A fuzzy super-twisting second order sliding mode control method is proposed for the uncertainties of the model error and external disturbance on the trajectory tracking accuracy of robotic manipulator. Based on the dynamic model of the robotic, a new non-singular terminal sliding mode manifold is designed, and an improved super-twisting algorithm is used to design the second order sliding mode controller. In order to solve the problem that the matching disturbance can only be compensated under the condition of the known disturbance boundary in the sliding mode control, the fuzzy logic algorithm is used to carryout the online compensation …
From Equal-Mass To Extreme-Mass-Ratio Binary Inspirals: Simulation Tools For Next Generation Gravitational Wave Detectors,
2022
Louisiana State University and Agricultural and Mechanical College
From Equal-Mass To Extreme-Mass-Ratio Binary Inspirals: Simulation Tools For Next Generation Gravitational Wave Detectors, Samuel Douglas Cupp
LSU Doctoral Dissertations
Current numerical codes can successfully evolve similar-mass binary black holes systems, and these numerical waveforms contributed to the success of the LIGO Collaboration's detection of gravitational waves. LIGO requires high resolution numerical waveforms for detection and parameter estimation of the source. Great effort was expended over several decades to produce the numerical methods used today. However, future detectors will require further improvements to numerical techniques to take full advantage of their detection capabilities. For example, the Laser Interferometer Space Antenna (LISA) will require higher resolution simulations of similar-mass-ratio systems than LIGO. LISA will also be able to detect extreme-mass-ratio inspiral …
Monofacial Vs Bifacial Solar Photovoltaic Systems In Snowy Environments,
2022
Western University
Monofacial Vs Bifacial Solar Photovoltaic Systems In Snowy Environments, Koami Soulemane Hayibo, Aliaksei Petsiuk, Pierce Mayville, Laura Brown, Joshua M. Pearce
Electrical and Computer Engineering Publications
There has been a recent surge in interest in the more accurate snow loss estimates for solar photovoltaic (PV) systems as large-scale deployments move into northern latitudes. Preliminary results show bifacial modules may clear snow faster than monofacial PV. This study analyzes snow losses on these two types of systems using empirical hourly data including energy, solar irradiation and albedo, and open-source image processing methods from images of the arrays in a northern environment in the winter. Projection transformations based on reference anchor points and snowless ground truth images provide reliable masking and optical distortion correction with fixed surveillance cameras. …
Decomposing Generation Networks With Structure Prediction For Recipe Generation,
2022
Singapore Management University
Decomposing Generation Networks With Structure Prediction For Recipe Generation, Hao Wang, Guosheng Lin, Steven C. H. Hoi, Chunyan Miao
Research Collection School Of Computing and Information Systems
Recipe generation from food images and ingredients is a challenging task, which requires the interpretation of the information from another modality. Different from the image captioning task, where the captions usually have one sentence, cooking instructions contain multiple sentences and have obvious structures. To help the model capture the recipe structure and avoid missing some cooking details, we propose a novel framework: Decomposing Generation Networks (DGN) with structure prediction, to get more structured and complete recipe generation outputs. Specifically, we split each cooking instruction into several phases, and assign different sub-generators to each phase. Our approach includes two novel ideas: …
Deep Learning For Person Re-Identification: A Survey And Outlook,
2022
Wuhan University
Deep Learning For Person Re-Identification: A Survey And Outlook, Mang Ye, Jianbing Shen, Gaojie Lin, Tao Xiang, Ling Shao, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-overlapping cameras. With the advancement of deep neural networks and increasing demand of intelligent video surveillance, it has gained significantly increased interest in the computer vision community. By dissecting the involved components in developing a person Re-ID system, we categorize it into the closed-world and open-world settings. We first conduct a comprehensive overview with in-depth analysis for closed-world person Re-ID from three different perspectives, including deep feature representation learning, deep metric learning and ranking optimization. With the performance saturation under closed-world setting, the research focus for person Re-ID …
You Have Earned A Trophy: Characterize In-Game Achievements And Their Completions,
2022
Singapore Management University
You Have Earned A Trophy: Characterize In-Game Achievements And Their Completions, Haewoon Kwak
Research Collection School Of Computing and Information Systems
Achievement systems have been actively adopted in gaming platforms to maintain players’ interests. Among them, trophies in PlayStation games are one of the most successful achievement systems. While the importance of trophy design has been casually discussed in many game developers’ forums, there has been no systematic study of the historical dataset of trophies yet. In this work, we construct a complete dataset of PlayStation games and their trophies and investigate them from both the developers’ and players’ perspectives.
Consensus Formation On Heterogeneous Networks,
2022
Singapore Management University
Consensus Formation On Heterogeneous Networks, Edoardo Fadda, Junda He, Claudia J. Tessone, Paolo Barucca
Research Collection School Of Computing and Information Systems
Reaching consensus-a macroscopic state where the system constituents display the same microscopic state-is a necessity in multiple complex socio-technical and techno-economic systems: their correct functioning ultimately depends on it. In many distributed systems-of which blockchain-based applications are a paradigmatic example-the process of consensus formation is crucial not only for the emergence of a leading majority but for the very functioning of the system. We build a minimalistic network model of consensus formation on blockchain systems for quantifying how central nodes-with respect to their average distance to others-can leverage on their position to obtain competitive advantage in the consensus process. We …
Effect Of Monetary Policy Rate On Market Interest Rates In Nigeria: A Threshold And Nardl Approach,
2022
Nigerian Institute of Social and Economic Research (NISER)
Effect Of Monetary Policy Rate On Market Interest Rates In Nigeria: A Threshold And Nardl Approach, Oluwafemi E. Awopegba, Joseph O. Afolabi, Lydia T. Adeoye, Godwin O. Akpokodje
CBN Journal of Applied Statistics (JAS)
This study examines the effect of monetary policy rate (MPR) on market interest rates in Nigeria. For parsimony, we develop two indexes called the short-term interest rate (SINT) and Lending interest rate (LINT) to represent deposit and lending rates respectively. The nonlinear autoregressive distributed lag (NARDL) and threshold regression models are adopted. The study uses monthly data from 2002:M1 to 2019:M12. The results of the threshold regression model indicate that the degree of the effect of MPR on SINT and LINT above the estimated threshold of 11 and 13 percent respectively is greater and significant than if MPR were to …
Social Dimension Of Inclusive Growth In Ecowas: Implication For Poverty Reduction,
2022
: Department of Economics, Olabisi Onabanjo University, Ago-Iwoye, Nigeria.
Social Dimension Of Inclusive Growth In Ecowas: Implication For Poverty Reduction, Toriola K. Anu, Goerge O. Emmanuel, Ajayi O. Felix
CBN Journal of Applied Statistics (JAS)
This study investigates the implication of the social dimension of inclusive growth on poverty reduction in Economic Community of West African States (ECOWAS) countries. It specifically examines how social indices of inclusive growth comprising of income inequality, education, and health outcomes affect poverty reduction. The study uses a panel dataset of the six (6) lower-middle income countries in ECOWAS which was analysed via panel Difference Generalised Method of Moment (D-GMM). The results show that GDP per capita exerts significant negative effect on poverty while inequality, education and health outcomes do not show significant effect on poverty. Although, the estimates of …
Effect Of Fdi Inflows On Employment Generation In Selected Ecowas Countries: Heterogeneous Panel Analysis,
2022
Central Bank of Nigeria
Effect Of Fdi Inflows On Employment Generation In Selected Ecowas Countries: Heterogeneous Panel Analysis, Timothy A. Aderemi, Olawunmi Omitogun, Bukonla G. Osisanwo
CBN Journal of Applied Statistics (JAS)
The aim of this study is to examine the effect of FDI on employment in ECOWAS sub region between 1990 and 2019. The study utilizes a panel autoregressive distributed lag model to analyse the short run and long run relationship between FDI and employment across ECOWAS sub region. In the short run, the impact of FDI on employment is negative and statistically not significant. Meanwhile, in the long run FDI has a positive and statistically significant impact on employment rate. This implies that FDI has the capacity to generate employment in countries in ECOWAS sub region. Therefore, this study recommends …
Impact Of Covid-19 Pandemic On The Nigeria Stock Market: A Sectoral Stock Prices Analysis,
2022
Central Bank of Nigeria
Impact Of Covid-19 Pandemic On The Nigeria Stock Market: A Sectoral Stock Prices Analysis, Peter A. Adekunle, Yakubu A. Bello, Udochukwu G. Nwachukwu
CBN Journal of Applied Statistics (JAS)
This study examines the impact of the COVID-19 pandemic on sectoral stock prices in Nigeria stock market using daily data covering from February 28, 2020 to June 26, 2020. Applying the autoregressive distributed lag (ARDL) bounds test, the study finds that COVID-19 pandemic had adverse impact on the stock market indices in the short run. Furthermore, the study documents negative response of sectoral stock prices to the pandemic while the stock prices of the banking sub-sector are the worst hit. Compared to the consumer goods, and industrial subsector indices, the speed of adjustment to long run equilibrium is faster for …
