scholarly journals A Fast Computational Method for the Minimum Duration Transfer Trajectories of Space-to-Ground Vehicles

2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Qingguo Liu ◽  
Xinxue Liu ◽  
Jian Wu
Keyword(s):  
Hybrid Method ◽  
Computational Time ◽  
State Variables ◽  
Ground Vehicles ◽  
Minimum Duration ◽  
Transfer Trajectory ◽  
Initial Values ◽  
Adjoint Variables ◽  
Partial State ◽  
Transfer Trajectories

On the conditions that the spacecraft engine is in finite thrust mode and the maneuver time is given, it takes a long time to compute the minimum duration transfer trajectories of space-to-ground vehicles, which is mainly because the initial values of the adjoint variables involved in the optimization model have no definite physical meanings and the model is sensitive to them. In order to develop space-to-ground transfer trajectory programmes in real time in an uncertain environment for the decision makers, we propose a fast method for computing the minimum duration transfer trajectories of space-to-ground vehicles with the given position of the landing point and the arbitrary maneuver point. First, the optimization model based on the hybrid method is established to compute the minimum duration transfer trajectory. Then, the region composed of maneuverable points is gridded and the initial values of the adjoint variables and the values of partial state variables of the minimum duration transfer trajectories at all gridded points are computed and saved to a database. Finally, the predicted values of the initial values of the adjoint variables and the values of partial state variables at any maneuver point within the region composed of maneuverable points are computed by using a binary cubic interpolation method. Finally, the minimum duration transfer trajectory is obtained by the hybrid method which takes the neighborhood of the predicted values as the search ranges of the initial values of the adjoint variables and the values of partial state variables. Simulation results demonstrate that the proposed method, which requires only 2.93% of the computational time of the hybrid method, can improve substantially the computational time of the minimum duration transfer trajectory of a space-to-ground vehicle under the guarantee of ensuring accuracy. The methodology of converting the time domain into the space domain is well applied in this paper.

scholarly journals Hybrid Method for Detecting Duplicate Image by Using Image Retrieval Technique in Data Mining

2021 ◽  
Vol 09 (04) ◽  
Author(s):  
Dr. S. Thavamani ◽  
Keyword(s):  
Data Mining ◽  
Image Retrieval ◽  
Hybrid Method ◽  
Video Retrieval ◽  
New Method ◽  
Computational Time ◽  
Storage Space ◽  
Copy Detection ◽  
Retrieval Technique ◽  
Improved Accuracy

Duplicated images cause several problems in online sites, so these demand special attention. To address the disadvantages of frames copy detection, the Hybrid Method of Detecting Duplicate Image by Using Image Retrieval Technique in Data Mining was proposed. We use the new method of eliminating duplicates in this example. To address the disadvantages of frames copy detection, the Hybrid Method of Detecting Duplicate Image by Using Image Retrieval Technique in Data Mining was proposed. The new method of eliminating duplicates in this example has proposed. Using this method, you can get rid of frames that aren't relevant to the video. This makes for more precise and faster video retrieval with fewer duplicates. As a back end, this technique is implemented in C# and SQL. The findings are put to the test and compared to the current SIFT process. The results showed that the output improved accuracy while reducing storage space, computational time, and memory use.

Tire-Terrain Normal and Longitudinal Dynamics and Slip Power Losses of an Unmanned Ground Vehicle

2013 ◽  
Author(s):  
Mostafa Salama ◽  
Vladimir V. Vantsevich
Keyword(s):  
Rolling Resistance ◽  
Computational Time ◽  
Unmanned Ground Vehicle ◽  
Ground Vehicles ◽  
Power Losses ◽  
Ground Vehicle ◽  
Longitudinal Dynamics ◽  
Straight Line ◽  
On Line ◽  
Terrain Characteristics

Studies of the tire-terrain interaction have mostly been completed on vehicles with steered wheels, but not much work has been done regarding skid-steered Unmanned Ground Vehicles (UGV). This paper introduces a mathematical model of normal and longitudinal dynamics of a UGV with four skid-steered pneumatic tire wheels. Unlike the common approach, in which two wheels at each side are treated as one wheel (i.e., having the same rotational speeds), all four wheels in this study are independently driven. Thus the interaction of each tire with deformable terrain is introduced as holonomic constraints. The stress-strain characteristics for tire-soil interaction are analyzed based on modern Terramechanics methods and then further used to determine the circumferential wheel forces of the four tires. Contributions of three components of each tire circumferential force to tire slippages are modeled and analyzed when the tire normal loads vary during vehicle straight-line motion. The considered tire-soil characteristics are mathematically reduced to a form that allows condensing the computational time for on-line computing tire-terrain characteristics. Additionally, rolling resistance of the tires is analyzed and incorporated in the UGV dynamic equations. Moreover, the paper describes the physics of slip power losses in the tire-soil interaction of the four tires and applies it to small skid-steered UGV. This study also formulates an optimization problem of the minimization of the power losses in the tire-soil interactions due to the tire slippage.

Non-Negative Matrix Factorization Based Uncertainty Quantification Method for Complex Networked Systems

2015 ◽  
Author(s):  
Arpan Mukherjee ◽  
Rahul Rai ◽  
Puneet Singla ◽  
Tarunraj Singh ◽  
Abani Patra
Keyword(s):  
Matrix Factorization ◽  
Decomposition Method ◽  
Uncertainty Propagation ◽  
Networked Systems ◽  
Computational Time ◽  
State Variables ◽  
System Decomposition ◽  
Cluster Interaction ◽  
Quantifying Uncertainty ◽  
Non Negative Matrix Factorization

The behavior of large networked systems with underlying complex nonlinear dynamic are hard to predict. With increasing number of states, the problem becomes even harder. Quantifying uncertainty in such systems by conventional methods requires high computational time and the accuracy obtained in estimating the state variables can also be low. This paper presents a novel computational Uncertainty Quantifying (UQ) method for complex networked systems. Our approach is to represent the complex systems as networks (graphs) whose nodes represent the dynamical units, and whose links stand for the interactions between them. First, we apply Non-negative Matrix Factorization (NMF) based decomposition method to partition the domain of the dynamical system into clusters, such that the inter-cluster interaction is minimized and the intra-cluster interaction is maximized. The decomposition method takes into account the dynamics of individual nodes to perform system decomposition. Initial validation results on two well-known dynamical systems have been performed. The validation results show that uncertainty propagation error quantified by RMS errors obtained through our algorithms are competitive or often better, compared to existing methods.

An Efficient Parallel Hybrid Method of FEM-MLFMA for Electromagnetic Radiation and Scattering Analysis of Separated Objects

2020 ◽  
Vol 35 (10) ◽  
pp. 1127-1136
Author(s):  
Sheng Zuo ◽  
Zhongchao Lin ◽  
Zheng Yue ◽  
Daniel Garcia Donoro ◽  
Yu Zhang ◽  
...  
Keyword(s):  
Finite Element ◽  
Hybrid Method ◽  
Information Exchange ◽  
Domain Decomposition Method ◽  
Near Field ◽  
Computational Time ◽  
Excellent Performance ◽  
Parallel Hybrid ◽  
Higher Order Method ◽  
Complex Features

In order to meet the rapidly increasing demand for accurate and efficient analysis of complex radiating or scattering structures in the presence of electrically large objects, a finite element method (FEM)-multilevel fast multipole algorithm (MLFMA) hybrid method that based on the Finite Element-Iterative Integral Equation Evaluation (FE-IIEE) mesh truncation technique is proposed in this paper. The present method makes use of FEM for the regions with small and complex features and MLFMA for the analysis of the electrically large objects, which ensure the accuracy and applicability of the method are better than most commonly adopted FEM-high frequency technique (HFT) hybrid method. The mutual interactions between regions are taken into account in a fully coupled way through iterative near filed computation process. In order to achieve an excellent performance, both algorithms have been implemented together from scratch, being able to run over multi CPU cores. An efficient parallel FEM domain decomposition method (DDM) solver with exploiting geometrical repetitions is included to drastically reduce memory requirements and computational time in the calculation of large array antenna. Also, the parallel MLFMA is adopted to expedite the near-field information exchange between regions. Through numerical example, the effect of distance between regions on the convergence of the proposed hybrid method is studied, and it is shown that the proposed method converge well even if the distance is equal to 0.05λ. Through comparisons with an in-house higher order method of moments (HOMoM) code and commercial software FEKO, the accuracy and effectiveness of the implemented parallel hybrid method are validated showing excellent performance.

scholarly journals Global Synchronization in Complex Networks with Adaptive Coupling

2010 ◽  
Vol 2010 ◽  
pp. 1-10 ◽  
Author(s):  
Zhengzhong Yuan ◽  
Jianping Cai ◽  
Meili Lin
Keyword(s):  
Complex Networks ◽  
Numerical Simulations ◽  
Adaptive Controller ◽  
Asymptotically Stable ◽  
State Variables ◽  
Global Synchronization ◽  
Coupling Matrix ◽  
Unified Chaotic System ◽  
Adaptive Coupling ◽  
Partial State

Global synchronization in adaptive coupling networks is studied in this paper. A new simple adaptive controller is proposed based on a concept of asymptotically stable led by partial state variables. Under the proposed adaptive update law, the network can achieve global synchronization without calculating the eigenvalues of the outer coupling matrix. The update law is only dependent on partial state variables of individual oscillators. Numerical simulations are given to show the effectiveness of the proposed method, in which the unified chaotic system is chosen as the nodes of the network with different topologies.

scholarly journals Noise Assisted Image Encryption and Decryption using 2-D Chaotic System

2021 ◽  
Author(s):  
Namrata Biswas ◽  
I. Raja Mohamed
Keyword(s):  
Image Encryption ◽  
Chaotic System ◽  
Color Image ◽  
Image Transmission ◽  
Noise Signal ◽  
State Variables ◽  
Initial Values ◽  
Xor Operation ◽  
Encryption And Decryption ◽  
Information Image

Abstract In this paper, a new two-dimensional (2-D) chaos-based color image encryption and decryption scheme is proposed in which the noise signal is selected randomly to set the initial values for a chaotic system which also enhances the security of the system. The 256-bit hash value of noise is transformed into one-time initial values for the state variables of this proposed chaotic system. XOR operation is further carried out to diffuse the pixels. Finally, statistical and security analyses are performed for understanding the effectiveness of the proposed system. Experimental results confirm that the proposed chaos-based cryptosystem is efficient and suitable for information (image) transmission in a highly secured way.

scholarly journals A Multi-Agent Based Optimization Model for Microgrid Operation with Hybrid Method Using Game Theory Strategy

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 603
Author(s):  
Ji-Won Lee ◽  
Mun-Kyeom Kim ◽  
Hyung-Joon Kim
Keyword(s):  
Game Theory ◽  
Hybrid Method ◽  
Storage System ◽  
Pso Algorithm ◽  
Energy Storage System ◽  
Computational Time ◽  
Position Vector ◽  
Solution Quality ◽  
The Game Theory ◽  
Multi Agent

Owing to the increases of energy loads and penetration of renewable energy with variability, it is essential to determine the optimum capacity of the battery energy storage system (BESS) and demand response (DR) within the microgrid (MG). To accomplish the foregoing, this paper proposes an optimal MG operation approach with a hybrid method considering the game theory for a multi-agent system. The hybrid method operation includes both BESS and DR methods. The former is presented to reduce the sum of the MG operation and BESS costs using the game theory, resulting in the optimal capacity of BESS. Similarly, the DR method determines the optimal DR capacity based on the trade-off between the incentive value and capacity. To improve optimization operation, multi-agent guiding particle swarm optimization (MAG-PSO) is implemented by adjusting the best global position and position vector. The results demonstrate that the proposed approach not only affords the most economical decision among agents but also reduces the utilization cost by approximately 8.5%, compared with the base method. Furthermore, it has been revealed that the proposed MAG-PSO algorithm has superiority in terms of solution quality and computational time with respect to other algorithms. Therefore, the optimal hybrid method operation obtains a superior solution with the game theory strategy.

scholarly journals ANALYSIS OF AN ANTI-PARALLEL MEMRISTOR CIRCUIT

2018 ◽  
Vol 8 (2) ◽  
pp. 9-14
Author(s):  
Valeri Mladenov ◽  
Stoyan Kirilov
Keyword(s):  
Boundary Condition ◽  
Computer Analysis ◽  
Finite Differences ◽  
The State ◽  
The Other ◽  
State Variables ◽  
Initial Values ◽  
Finite Differences Method ◽  
Basic Purpose ◽  
Supply Current

The basic purpose of the present paper is to propose an extended investigation and computer analysis of an anti-parallel memristor circuit with two equivalent memristor elements with different initial values of the state variables using a modified Boundary Condition Memristor (BCM) Model and the finite differences method. The memristor circuit is investigated for sinusoidal supply current at different magnitudes – for soft-switching and hard-switching modes, respectively. The influence of the initial values of the state variables on the circuit’s behaviour is presented as well. The equivalent i-v and memristance-flux and the other important relationshipsof the memristor circuit are also analyzed.

Semantic Enrichment for Geospatial Information in a Tourism Recommender System

2013 ◽  
pp. 2208-2229
Author(s):  
Joan de la Flor ◽  
Joan Borràs ◽  
David Isern ◽  
Aida Valls ◽  
Antonio Moreno ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Recommender System ◽  
Hybrid Method ◽  
Spatial Data ◽  
Recommendation System ◽  
Geographic Information ◽  
Computational Time ◽  
Limited Information ◽  
Geospatial Information ◽  
Visitor Satisfaction

Geospatial information is commonly used in tourism to facilitate activity planning, especially in a context of limited information on the territory, as it is common in the case of complex and heterogeneous tourism destination regions where the constrained spatial activity of visitor is likely to generate inefficiencies in the use of assets and resources, and hinder visitor satisfaction. Because of the large amount of spatial and non-spatial data associated with different resources and activities, it is a logical choice to use geographic information systems (GIS) for storing, managing, analyzing, and visualizing the data. Nevertheless, in order to facilitate personalized recommendations to visitors, interaction with Artificial Intelligence is needed. This chapter presents SigTur/E-Destination, a tourism recommender system based on a semantically-enriched GIS that provides regional tourist organizations and the industry with a new powerful tool for the sustainable management of their destinations. The recommendation system uses innovative Artificial Intelligence techniques, such as a hybrid method that integrates content-based and collaborative filtering and clustering methodologies that improve computational time.

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