Search results for: iterative dynamic algorithm
4886 Multiple Job Shop-Scheduling using Hybrid Heuristic Algorithm
Authors: R.A.Mahdavinejad
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In this paper, multi-processors job shop scheduling problems are solved by a heuristic algorithm based on the hybrid of priority dispatching rules according to an ant colony optimization algorithm. The objective function is to minimize the makespan, i.e. total completion time, in which a simultanous presence of various kinds of ferons is allowed. By using the suitable hybrid of priority dispatching rules, the process of finding the best solution will be improved. Ant colony optimization algorithm, not only promote the ability of this proposed algorithm, but also decreases the total working time because of decreasing in setup times and modifying the working production line. Thus, the similar work has the same production lines. Other advantage of this algorithm is that the similar machines (not the same) can be considered. So, these machines are able to process a job with different processing and setup times. According to this capability and from this algorithm evaluation point of view, a number of test problems are solved and the associated results are analyzed. The results show a significant decrease in throughput time. It also shows that, this algorithm is able to recognize the bottleneck machine and to schedule jobs in an efficient way.
Keywords: Job shops scheduling, Priority dispatching rules, Makespan, Hybrid heuristic algorithm.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16694885 Satellite Beam Handoff Detection Algorithm Based On RCST Mobility Information
Authors: Ji Nyong Jang, Min Woo Lee, Eun Kyung Kim, Ki Keun Kim, Jae Sung Lim
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Since DVB-RCS has been successively implemented, the mobile communication on the multi-beam satellite communication is attractive attention. And the DVB-RCS standard sets up to support mobility of a RCST. In the case of the spot-beam satellite system, the received signal strength does not differ largely between the center and the boundary of the beam. Thus, the RSS based handoff detection algorithm is not benefit to the satellite system as a terrestrial system. Therefore we propose an Adaptive handoff detection algorithm based on RCST mobility information. Our handoff detection algorithm not only can be used as centralized handoff detection algorithm but also removes uncertainties of handoff due to the variation of RSS. Performances were compared with RSS based handoff algorithm. Simulation results show that the proposed handoff detection algorithm not only achieved better handoff and link degradation rate, but also achieved better forward link spectral efficiency.
Keywords: DVB-RCS, satellite multi-beam handoff, mobility information, handover.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17124884 A Simple Adaptive Algorithm for Norm-Constrained Optimization
Authors: Hyun-Chool Shin
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In this paper we propose a simple adaptive algorithm iteratively solving the unit-norm constrained optimization problem. Instead of conventional parameter norm based normalization, the proposed algorithm incorporates scalar normalization which is computationally much simpler. The analysis of stationary point is presented to show that the proposed algorithm indeed solves the constrained optimization problem. The simulation results illustrate that the proposed algorithm performs as good as conventional ones while being computationally simpler.Keywords: constrained optimization, unit-norm, LMS, principle component analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21284883 Application of a New Efficient Normal Parameter Reduction Algorithm of Soft Sets in Online Shopping
Authors: Xiuqin Ma, Hongwu Qin
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A new efficient normal parameter reduction algorithm of soft set in decision making was proposed. However, up to the present, few documents have focused on real-life applications of this algorithm. Accordingly, we apply a New Efficient Normal Parameter Reduction algorithm into real-life datasets of online shopping, such as Blackberry Mobile Phone Dataset. Experimental results show that this algorithm is not only suitable but feasible for dealing with the online shopping.
Keywords: Normal parameter reduction, Online shopping, Parameter reduction, Soft sets.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18264882 A Speeded up Robust Scale-Invariant Feature Transform Currency Recognition Algorithm
Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim
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All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms.
Keywords: Currency recognition, feature detection and description, SIFT algorithm, SURF algorithm, speeded up and robust features.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8644881 Dynamic Anonymity
Authors: Emin Islam Tatlı, Dirk Stegemann, Stefan Lucks
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Encryption protects communication partners from disclosure of their secret messages but cannot prevent traffic analysis and the leakage of information about “who communicates with whom". In the presence of collaborating adversaries, this linkability of actions can danger anonymity. However, reliably providing anonymity is crucial in many applications. Especially in contextaware mobile business, where mobile users equipped with PDAs request and receive services from service providers, providing anonymous communication is mission-critical and challenging at the same time. Firstly, the limited performance of mobile devices does not allow for heavy use of expensive public-key operations which are commonly used in anonymity protocols. Moreover, the demands for security depend on the application (e.g., mobile dating vs. pizza delivery service), but different users (e.g., a celebrity vs. a normal person) may even require different security levels for the same application. Considering both hardware limitations of mobile devices and different sensitivity of users, we propose an anonymity framework that is dynamically configurable according to user and application preferences. Our framework is based on Chaum-s mixnet. We explain the proposed framework, its configuration parameters for the dynamic behavior and the algorithm to enforce dynamic anonymity.Keywords: Anonymity, context-awareness, mix-net, mobile business, policy management
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17084880 Solving the Teacher Assignment-Course Scheduling Problem by a Hybrid Algorithm
Authors: Aldy Gunawan, Kien Ming Ng, Kim Leng Poh
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This paper presents a hybrid algorithm for solving a timetabling problem, which is commonly encountered in many universities. The problem combines both teacher assignment and course scheduling problems simultaneously, and is presented as a mathematical programming model. However, this problem becomes intractable and it is unlikely that a proven optimal solution can be obtained by an integer programming approach, especially for large problem instances. A hybrid algorithm that combines an integer programming approach, a greedy heuristic and a modified simulated annealing algorithm collaboratively is proposed to solve the problem. Several randomly generated data sets of sizes comparable to that of an institution in Indonesia are solved using the proposed algorithm. Computational results indicate that the algorithm can overcome difficulties of large problem sizes encountered in previous related works.
Keywords: Timetabling problem, mathematical programming model, hybrid algorithm, simulated annealing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 45734879 Complexity Reduction Approach with Jacobi Iterative Method for Solving Composite Trapezoidal Algebraic Equations
Authors: Mohana Sundaram Muthuvalu, Jumat Sulaiman
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In this paper, application of the complexity reduction approach based on half- and quarter-sweep iteration concepts with Jacobi iterative method for solving composite trapezoidal (CT) algebraic equations is discussed. The performances of the methods for CT algebraic equations are comparatively studied by their application in solving linear Fredholm integral equations of the second kind. Furthermore, computational complexity analysis and numerical results for three test problems are also included in order to verify performance of the methods.
Keywords: Complexity reduction approach, Composite trapezoidal scheme, Jacobi method, Linear Fredholm integral equations
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15944878 The Variable Step-Size Gauss-Seidel Pseudo Affine Projection Algorithm
Authors: F. Albu, C. Paleologu
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In this paper, a new pseudo affine projection (AP) algorithm based on Gauss-Seidel (GS) iterations is proposed for acoustic echo cancellation (AEC). It is shown that the algorithm is robust against near-end signal variations (including double-talk).Keywords: pseudo affine projection algorithm, acoustic echo cancellation, double-talk.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14264877 Optimization of Supersonic Ejector via Sequence-Adapted Micro-Genetic Algorithm
Authors: Kolar Jan, Dvorak Vaclav
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In this study, an optimization of supersonic air-to-air ejector is carried out by a recently developed single-objective genetic algorithm based on adaption of sequence of individuals. Adaptation of sequence is based on Shape-based distance of individuals and embedded micro-genetic algorithm. The optimal sequence found defines the succession of CFD-aimed objective calculation within each generation of regular micro-genetic algorithm. A spring-based deformation mutates the computational grid starting the initial individualvia adapted population in the optimized sequence. Selection of a generation initial individual is knowledge-based. A direct comparison of the newly defined and standard micro-genetic algorithm is carried out for supersonic air-to-air ejector. The only objective is to minimize the loose of total stagnation pressure in the ejector. The result is that sequence-adopted micro-genetic algorithm can provide comparative results to standard algorithm but in significantly lower number of overall CFD iteration steps.
Keywords: Grid deformation, Micro-genetic algorithm, shapebased sequence, supersonic ejector.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15644876 A Self-stabilizing Algorithm for Maximum Popular Matching of Strictly Ordered Preference Lists
Authors: Zhengnan Shi
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In this paper, we consider the problem of Popular Matching of strictly ordered preference lists. A Popular Matching is not guaranteed to exist in any network. We propose an IDbased, constant space, self-stabilizing algorithm that converges to a Maximum Popular Matching an optimum solution, if one exist. We show that the algorithm stabilizes in O(n5) moves under any scheduler (daemon).
Keywords: self-stabilization, popular matching, algorithm, distributed computing, fault tolerance
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11874875 Comparing Hilditch, Rosenfeld, Zhang-Suen,and Nagendraprasad -Wang-Gupta Thinning
Authors: Anastasia Rita Widiarti
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This paper compares Hilditch, Rosenfeld, Zhang- Suen, dan Nagendraprasad Wang Gupta (NWG) thinning algorithms for Javanese character image recognition. Thinning is an effective process when the focus in not on the size of the pattern, but rather on the relative position of the strokes in the pattern. The research analyzes the thinning of 60 Javanese characters. Time-wise, Zhang-Suen algorithm gives the best results with the average process time being 0.00455188 seconds. But if we look at the percentage of pixels that meet one-pixel thickness, Rosenfelt algorithm gives the best results, with a 99.98% success rate. From the number of pixels that are erased, NWG algorithm gives the best results with the average number of pixels erased being 84.12%. It can be concluded that the Hilditch algorithm performs least successfully compared to the other three algorithms.Keywords: Hilditch algorithm, Nagendraprasad-Wang-Guptaalgorithm, Rosenfeld algorithm, Thinning, Zhang-suen algorithm
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 39184874 Robustness of Hybrid Learning Acceleration Feedback Control Scheme in Flexible Manipulators
Authors: M. Z Md Zain, M. O. Tokhi, M. S. Alam
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This paper describes a practical approach to design and develop a hybrid learning with acceleration feedback control (HLC) scheme for input tracking and end-point vibration suppression of flexible manipulator systems. Initially, a collocated proportionalderivative (PD) control scheme using hub-angle and hub-velocity feedback is developed for control of rigid-body motion of the system. This is then extended to incorporate a further hybrid control scheme of the collocated PD control and iterative learning control with acceleration feedback using genetic algorithms (GAs) to optimize the learning parameters. Experimental results of the response of the manipulator with the control schemes are presented in the time and frequency domains. The performance of the HLC is assessed in terms of input tracking, level of vibration reduction at resonance modes and robustness with various payloads.Keywords: Flexible manipulator, iterative learning control, vibration suppression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18204873 Constant Factor Approximation Algorithm for p-Median Network Design Problem with Multiple Cable Types
Authors: Chaghoub Soraya, Zhang Xiaoyan
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This research presents the first constant approximation algorithm to the p-median network design problem with multiple cable types. This problem was addressed with a single cable type and there is a bifactor approximation algorithm for the problem. To the best of our knowledge, the algorithm proposed in this paper is the first constant approximation algorithm for the p-median network design with multiple cable types. The addressed problem is a combination of two well studied problems which are p-median problem and network design problem. The introduced algorithm is a random sampling approximation algorithm of constant factor which is conceived by using some random sampling techniques form the literature. It is based on a redistribution Lemma from the literature and a steiner tree problem as a subproblem. This algorithm is simple, and it relies on the notions of random sampling and probability. The proposed approach gives an approximation solution with one constant ratio without violating any of the constraints, in contrast to the one proposed in the literature. This paper provides a (21 + 2)-approximation algorithm for the p-median network design problem with multiple cable types using random sampling techniques.Keywords: Approximation algorithms, buy-at-bulk, combinatorial optimization, network design, p-median.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5954872 Increasing the Resilience of Cyber Physical Systems in Smart Grid Environments using Dynamic Cells
Authors: Andrea Tundis, Carlos García Cordero, Rolf Egert, Alfredo Garro, Max Mühlhäuser
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Resilience is an important system property that relies on the ability of a system to automatically recover from a degraded state so as to continue providing its services. Resilient systems have the means of detecting faults and failures with the added capability of automatically restoring their normal operations. Mastering resilience in the domain of Cyber-Physical Systems is challenging due to the interdependence of hybrid hardware and software components, along with physical limitations, laws, regulations and standards, among others. In order to overcome these challenges, this paper presents a modeling approach, based on the concept of Dynamic Cells, tailored to the management of Smart Grids. Additionally, a heuristic algorithm that works on top of the proposed modeling approach, to find resilient configurations, has been defined and implemented. More specifically, the model supports a flexible representation of Smart Grids and the algorithm is able to manage, at different abstraction levels, the resource consumption of individual grid elements on the presence of failures and faults. Finally, the proposal is evaluated in a test scenario where the effectiveness of such approach, when dealing with complex scenarios where adequate solutions are difficult to find, is shown.Keywords: Cyber-physical systems, energy management, optimization, smart grids, self-healing, resilience, security.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10684871 Noise Reduction in Image Sequences using an Effective Fuzzy Algorithm
Authors: Mahmoud Saeidi, Khadijeh Saeidi, Mahmoud Khaleghi
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In this paper, we propose a novel spatiotemporal fuzzy based algorithm for noise filtering of image sequences. Our proposed algorithm uses adaptive weights based on a triangular membership functions. In this algorithm median filter is used to suppress noise. Experimental results show when the images are corrupted by highdensity Salt and Pepper noise, our fuzzy based algorithm for noise filtering of image sequences, are much more effective in suppressing noise and preserving edges than the previously reported algorithms such as [1-7]. Indeed, assigned weights to noisy pixels are very adaptive so that they well make use of correlation of pixels. On the other hand, the motion estimation methods are erroneous and in highdensity noise they may degrade the filter performance. Therefore, our proposed fuzzy algorithm doesn-t need any estimation of motion trajectory. The proposed algorithm admissibly removes noise without having any knowledge of Salt and Pepper noise density.Keywords: Image Sequences, Noise Reduction, fuzzy algorithm, triangular membership function
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18804870 A New Heuristic for Improving the Performance of Genetic Algorithm
Authors: Warattapop Chainate, Peeraya Thapatsuwan, Pupong Pongcharoen
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The hybridisation of genetic algorithm with heuristics has been shown to be one of an effective way to improve its performance. In this work, genetic algorithm hybridised with four heuristics including a new heuristic called neighbourhood improvement were investigated through the classical travelling salesman problem. The experimental results showed that the proposed heuristic outperformed other heuristics both in terms of quality of the results obtained and the computational time.Keywords: Genetic Algorithm, Hybridisation, Metaheuristics, Travelling Salesman Problem.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18484869 A Cost Function for Joint Blind Equalization and Phase Recovery
Authors: Reza Berangi, Morteza Babaee, Majid Soleimanipour
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In this paper a new cost function for blind equalization is proposed. The proposed cost function, referred to as the modified maximum normalized cumulant criterion (MMNC), is an extension of the previously proposed maximum normalized cumulant criterion (MNC). While the MNC requires a separate phase recovery system after blind equalization, the MMNC performs joint blind equalization and phase recovery. To achieve this, the proposed algorithm maximizes a cost function that considers both amplitude and phase of the equalizer output. The simulation results show that the proposed algorithm has an improved channel equalization effect than the MNC algorithm and simultaneously can correct the phase error that the MNC algorithm is unable to do. The simulation results also show that the MMNC algorithm has lower complexity than the MNC algorithm. Moreover, the MMNC algorithm outperforms the MNC algorithm particularly when the symbols block size is small.Keywords: Blind equalization, maximum normalized cumulant criterion (MNC), intersymbol interference (ISI), modified MNC criterion (MMNC), phase recovery.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17644868 Design and Bandwidth Allocation of Embedded ATM Networks using Genetic Algorithm
Authors: H. El-Madbouly
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In this paper, genetic algorithm (GA) is proposed for the design of an optimization algorithm to achieve the bandwidth allocation of ATM network. In Broadband ISDN, the ATM is a highbandwidth; fast packet switching and multiplexing technique. Using ATM it can be flexibly reconfigure the network and reassign the bandwidth to meet the requirements of all types of services. By dynamically routing the traffic and adjusting the bandwidth assignment, the average packet delay of the whole network can be reduced to a minimum. M/M/1 model can be used to analyze the performance.Keywords: Bandwidth allocation, Genetic algorithm, ATMNetwork, packet delay.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13764867 An AI-Based Dynamical Resource Allocation Calculation Algorithm for Unmanned Aerial Vehicle
Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar
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As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the CPU, RAM, and ROM memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.
Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3504866 A Minimum Spanning Tree-Based Method for Initializing the K-Means Clustering Algorithm
Authors: J. Yang, Y. Ma, X. Zhang, S. Li, Y. Zhang
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The traditional k-means algorithm has been widely used as a simple and efficient clustering method. However, the algorithm often converges to local minima for the reason that it is sensitive to the initial cluster centers. In this paper, an algorithm for selecting initial cluster centers on the basis of minimum spanning tree (MST) is presented. The set of vertices in MST with same degree are regarded as a whole which is used to find the skeleton data points. Furthermore, a distance measure between the skeleton data points with consideration of degree and Euclidean distance is presented. Finally, MST-based initialization method for the k-means algorithm is presented, and the corresponding time complexity is analyzed as well. The presented algorithm is tested on five data sets from the UCI Machine Learning Repository. The experimental results illustrate the effectiveness of the presented algorithm compared to three existing initialization methods.
Keywords: Degree, initial cluster center, k-means, minimum spanning tree.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15524865 Multi-Objective Optimization of an Aerodynamic Feeding System Using Genetic Algorithm
Authors: Jan Busch, Peter Nyhuis
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Considering the challenges of short product life cycles and growing variant diversity, cost minimization and manufacturing flexibility increasingly gain importance to maintain a competitive edge in today’s global and dynamic markets. In this context, an aerodynamic part feeding system for high-speed industrial assembly applications has been developed at the Institute of Production Systems and Logistics (IFA), Leibniz Universitaet Hannover. The aerodynamic part feeding system outperforms conventional systems with respect to its process safety, reliability, and operating speed. In this paper, a multi-objective optimisation of the aerodynamic feeding system regarding the orientation rate, the feeding velocity, and the required nozzle pressure is presented.Keywords: Aerodynamic feeding system, genetic algorithm, multi-objective optimization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16674864 Lumped Parameter Models for Numerical Simulation of the Dynamic Response of Hoisting Appliances
Authors: Giovanni Incerti, Luigi Solazzi, Candida Petrogalli
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This paper describes three lumped parameters models for the study of the dynamic behavior of a boom crane. The models here proposed allows to evaluate the fluctuations of the load arising from the rope and structure elasticity and from the type of the motion command imposed by the winch. A calculation software was developed in order to determine the actual acceleration of the lifted mass and the dynamic overload during the lifting phase. Some application examples are presented, with the aim of showing the correlation between the magnitude of the stress and the type of the employed motion command.Keywords: Crane, dynamic model, overloading condition, vibration.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19644863 Algorithm of Measurement of Noise Signal Power in the Presence of Narrowband Interference
Authors: Alexey V. Klyuev, Valery P. Samarin, Viktor F. Klyuev
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A power measurement algorithm of the input mix components of the noise signal and narrowband interference is considered using functional transformations of the input mix in the postdetection processing channel. The algorithm efficiency analysis has been carried out for different interference-to-signal ratio. Algorithm performance features have been explored by numerical experiment results.
Keywords: Noise signal, continuous narrowband interference, signal power, spectrum width, detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13974862 A Weighted Least Square Algorithm for Low-Delay FIR Filters with Piecewise Variable Stopbands
Authors: Yasunori Sugita, Toshinori Yoshikawa, Naoyuki Aikawa
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Variable digital filters are useful for various signal processing and communication applications where the frequency characteristics, such as fractional delays and cutoff frequencies, can be varied. In this paper, we propose a design method of variable FIR digital filters with an approximate linear phase characteristic in the passband. The proposed variable FIR filters have some large attenuation in stopband and their large attenuation can be varied by spectrum parameters. In the proposed design method, a quasi-equiripple characteristic can be obtained by using an iterative weighted least square method. The usefulness of the proposed design method is verified through some examples.
Keywords: Weighted Least Squares Approximation, Variable FIR Filters, Low-Delay, Quasi-Equiripple
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16584861 Detection of Actuator Faults for an Attitude Control System using Neural Network
Authors: S. Montenegro, W. Hu
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The objective of this paper is to develop a neural network-based residual generator to detect the fault in the actuators for a specific communication satellite in its attitude control system (ACS). First, a dynamic multilayer perceptron network with dynamic neurons is used, those neurons correspond a second order linear Infinite Impulse Response (IIR) filter and a nonlinear activation function with adjustable parameters. Second, the parameters from the network are adjusted to minimize a performance index specified by the output estimated error, with the given input-output data collected from the specific ACS. Then, the proposed dynamic neural network is trained and applied for detecting the faults injected to the wheel, which is the main actuator in the normal mode for the communication satellite. Then the performance and capabilities of the proposed network were tested and compared with a conventional model-based observer residual, showing the differences between these two methods, and indicating the benefit of the proposed algorithm to know the real status of the momentum wheel. Finally, the application of the methods in a satellite ground station is discussed.Keywords: Satellite, Attitude Control, Momentum Wheel, Neural Network, Fault Detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19924860 System Identification Based on Stepwise Regression for Dynamic Market Representation
Authors: Alexander Efremov
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A system for market identification (SMI) is presented. The resulting representations are multivariable dynamic demand models. The market specifics are analyzed. Appropriate models and identification techniques are chosen. Multivariate static and dynamic models are used to represent the market behavior. The steps of the first stage of SMI, named data preprocessing, are mentioned. Next, the second stage, which is the model estimation, is considered in more details. Stepwise linear regression (SWR) is used to determine the significant cross-effects and the orders of the model polynomials. The estimates of the model parameters are obtained by a numerically stable estimator. Real market data is used to analyze SMI performance. The main conclusion is related to the applicability of multivariate dynamic models for representation of market systems.Keywords: market identification, dynamic models, stepwise regression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16184859 Detecting the Nonlinearity in Time Series from Continuous Dynamic Systems Based on Delay Vector Variance Method
Authors: Shumin Hou, Yourong Li, Sanxing Zhao
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Much time series data is generally from continuous dynamic system. Firstly, this paper studies the detection of the nonlinearity of time series from continuous dynamics systems by applying the Phase-randomized surrogate algorithm. Then, the Delay Vector Variance (DVV) method is introduced into nonlinearity test. The results show that under the different sampling conditions, the opposite detection of nonlinearity is obtained via using traditional test statistics methods, which include the third-order autocovariance and the asymmetry due to time reversal. Whereas the DVV method can perform well on determining nonlinear of Lorenz signal. It indicates that the proposed method can describe the continuous dynamics signal effectively.
Keywords: Nonlinearity, Time series, continuous dynamics system, DVV method
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16264858 A Preliminary Study for Design of Automatic Block Reallocation Algorithm with Genetic Algorithm Method in the Land Consolidation Projects
Authors: Tayfun Çay, Yaşar İnceyol, Abdurrahman Özbeyaz
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Land reallocation is one of the most important steps in land consolidation projects. Many different models were proposed for land reallocation in the literature such as Fuzzy Logic, block priority based land reallocation and Spatial Decision Support Systems. A model including four parts is considered for automatic block reallocation with genetic algorithm method in land consolidation projects. These stages are preparing data tables for a project land, determining conditions and constraints of land reallocation, designing command steps and logical flow chart of reallocation algorithm and finally writing program codes of Genetic Algorithm respectively. In this study, we designed the first three steps of the considered model comprising four steps.Keywords: Genetic algorithm, land consolidation, landholding, land reallocation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19074857 Noise Reduction in Web Data: A Learning Approach Based on Dynamic User Interests
Authors: Julius Onyancha, Valentina Plekhanova
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One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.Keywords: Web log data, web user profile, user interest, noise web data learning, machine learning.
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