Search results for: Dynamic error
2255 Validation and Selection between Machine Learning Technique and Traditional Methods to Reduce Bullwhip Effects: a Data Mining Approach
Authors: Hamid R. S. Mojaveri, Seyed S. Mousavi, Mojtaba Heydar, Ahmad Aminian
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The aim of this paper is to present a methodology in three steps to forecast supply chain demand. In first step, various data mining techniques are applied in order to prepare data for entering into forecasting models. In second step, the modeling step, an artificial neural network and support vector machine is presented after defining Mean Absolute Percentage Error index for measuring error. The structure of artificial neural network is selected based on previous researchers' results and in this article the accuracy of network is increased by using sensitivity analysis. The best forecast for classical forecasting methods (Moving Average, Exponential Smoothing, and Exponential Smoothing with Trend) is resulted based on prepared data and this forecast is compared with result of support vector machine and proposed artificial neural network. The results show that artificial neural network can forecast more precisely in comparison with other methods. Finally, forecasting methods' stability is analyzed by using raw data and even the effectiveness of clustering analysis is measured.Keywords: Artificial Neural Networks (ANN), bullwhip effect, demand forecasting, Support Vector Machine (SVM).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19982254 Forecasting 24-Hour Ahead Electricity Load Using Time Series Models
Authors: Ramin Vafadary, Maryam Khanbaghi
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Forecasting electricity load is important for various purposes like planning, operation and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria namely, the Mean Absolute Error and Root Mean Square Error. The National Renewable Energy Laboratory (NREL) residential energy consumption data are used to train the models. The results of this study show that SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts we can improve the robustness of the models for 24 hour ahead electricity load forecasting.
Keywords: Bagging, Fbprophet, Holt-Winters, LSTM, Load Forecast, SARIMA, tensorflow probability, time series.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4632253 Dynamic Features Selection for Heart Disease Classification
Authors: Walid MOUDANI
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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the Coronary Heart Disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts- knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.Keywords: Multi-Classifier Decisions Tree, Features Reduction, Dynamic Programming, Rough Sets.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25232252 The Nonlinear Dynamic Elasto-Plastic Analysis for Evaluating the Controlling Effectiveness and Failure Mechanism of the MSCSS
Authors: Toi Limazie, Xun'an Zhang, Xianjie Wang
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This paper focuses on the Mega-Sub Controlled Structure Systems (MSCSS) performances and characteristics regarding the new control principle contained in MSCSS subjected to strong earthquake excitations. The adopted control scheme consists of modulated sub-structures where the control action is achieved by viscous dampers and sub-structure own configuration. The elastic-plastic time history analysis under severe earthquake excitation is analyzed base on the Finite Element Analysis Method (FEAM), and some comparison results are also given in this paper. The result shows that the MSCSS systems can remarkably reduce vibrations effects more than the mega-sub structure (MSS). The study illustrates that the improved MSCSS presents good seismic resistance ability even at 1.2g and can absorb seismic energy in the structure, thus imply that structural members cross section can be reduce and achieve to good economic characteristics. Furthermore, the elasto-plastic analysis demonstrates that the MSCSS is accurate enough regarding international building evaluation and design codes. This paper also shows that the elasto-plastic dynamic analysis method is a reasonable and reliable analysis method for structures subjected to strong earthquake excitations and that the computed results are more precise.Keywords: controlling effectiveness, Elasto-plastic dynamic analysis, Mega-Sub Controlled Structure, Plastic hinge pattern.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18272251 Highly Optimized Novel High Speed Low Power Barrel Shifter at 22nm Hi K Metal Gate Strained Si Technology Node
Authors: Shobha Sharma, Amita Dev
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This research paper presents highly optimized barrel shifter at 22nm Hi K metal gate strained Si technology node. This barrel shifter is having a unique combination of static and dynamic body bias which gives lowest power delay product. This power delay product is compared with the same circuit at same technology node with static forward biasing at ‘supply/2’ and also with normal reverse substrate biasing and still found to be the lowest. The power delay product of this barrel sifter is .39362X10-17J and is lowered by approximately 78% to reference proposed barrel shifter at 32nm bulk CMOS technology. Power delay product of barrel shifter at 22nm Hi K Metal gate technology with normal reverse substrate bias is 2.97186933X10-17J and can be compared with this design’s PDP of .39362X10-17J. This design uses both static and dynamic substrate biasing and also has approximately 96% lower power delay product compared to only forward body biased at half of supply voltage. The NMOS model used are predictive technology models of Arizona state university and the simulations to be carried out using HSPICE simulator.Keywords: Dynamic body biasing, highly optimized barrel shifter, PDP, Static body biasing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18782250 Dynamic Data Partition Algorithm for a Parallel H.264 Encoder
Authors: Juntae Kim, Jaeyoung Park, Kyoungkun Lee, Jong Tae Kim
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The H.264/AVC standard is a highly efficient video codec providing high-quality videos at low bit-rates. As employing advanced techniques, the computational complexity has been increased. The complexity brings about the major problem in the implementation of a real-time encoder and decoder. Parallelism is the one of approaches which can be implemented by multi-core system. We analyze macroblock-level parallelism which ensures the same bit rate with high concurrency of processors. In order to reduce the encoding time, dynamic data partition based on macroblock region is proposed. The data partition has the advantages in load balancing and data communication overhead. Using the data partition, the encoder obtains more than 3.59x speed-up on a four-processor system. This work can be applied to other multimedia processing applications.Keywords: H.264/AVC, video coding, thread-level parallelism, OpenMP, multimedia
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17862249 Software Maintenance Severity Prediction for Object Oriented Systems
Authors: Parvinder S. Sandhu, Roma Jaswal, Sandeep Khimta, Shailendra Singh
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As the majority of faults are found in a few of its modules so there is a need to investigate the modules that are affected severely as compared to other modules and proper maintenance need to be done in time especially for the critical applications. As, Neural networks, which have been already applied in software engineering applications to build reliability growth models predict the gross change or reusability metrics. Neural networks are non-linear sophisticated modeling techniques that are able to model complex functions. Neural network techniques are used when exact nature of input and outputs is not known. A key feature is that they learn the relationship between input and output through training. In this present work, various Neural Network Based techniques are explored and comparative analysis is performed for the prediction of level of need of maintenance by predicting level severity of faults present in NASA-s public domain defect dataset. The comparison of different algorithms is made on the basis of Mean Absolute Error, Root Mean Square Error and Accuracy Values. It is concluded that Generalized Regression Networks is the best algorithm for classification of the software components into different level of severity of impact of the faults. The algorithm can be used to develop model that can be used for identifying modules that are heavily affected by the faults.Keywords: Neural Network, Software faults, Software Metric.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15662248 Comparison and Improvement of the Existing Cone Penetration Test Results: Shear Wave Velocity Correlations for Hungarian Soils
Authors: Ákos Wolf, Richard P. Ray
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Due to the introduction of Eurocode 8, the structural design for seismic and dynamic effects has become more significant in Hungary. This has emphasized the need for more effort to describe the behavior of structures under these conditions. Soil conditions have a significant effect on the response of structures by modifying the stiffness and damping of the soil-structural system and by modifying the seismic action as it reaches the ground surface. Shear modulus (G) and shear wave velocity (vs), which are often measured in the field, are the fundamental dynamic soil properties for foundation vibration problems, liquefaction potential and earthquake site response analysis. There are several laboratory and in-situ measurement techniques to evaluate dynamic soil properties, but unfortunately, they are often too expensive for general design practice. However, a significant number of correlations have been proposed to determine shear wave velocity or shear modulus from Cone Penetration Tests (CPT), which are used more and more in geotechnical design practice in Hungary. This allows the designer to analyze and compare CPT and seismic test result in order to select the best correlation equations for Hungarian soils and to improve the recommendations for the Hungarian geologic conditions. Based on a literature review, as well as research experience in Hungary, the influence of various parameters on the accuracy of results will be shown. This study can serve as a basis for selecting and modifying correlation equations for Hungarian soils. Test data are taken from seven locations in Hungary with similar geologic conditions. The shear wave velocity values were measured by seismic CPT. Several factors are analyzed including soil type, behavior index, measurement depth, geologic age etc. for their effect on the accuracy of predictions. The final results show an improved prediction method for Hungarian soils
Keywords: CPT correlation, dynamic soil properties, seismic CPT, shear wave velocity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11552247 Optimal Policy for a Deteriorating Inventory Model with Finite Replenishment Rate and with Price Dependant Demand Rate and Cycle Length Dependant Price
Authors: Hamed Sabahno
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In this paper, an inventory model with finite and constant replenishment rate, price dependant demand rate, time value of money and inflation, finite time horizon, lead time and exponential deterioration rate and with the objective of maximizing the present worth of the total system profit is developed. Using a dynamic programming based solution algorithm, the optimal sequence of the cycles can be found and also different optimal selling prices, optimal order quantities and optimal maximum inventories can be obtained for the cycles with unequal lengths, which have never been done before for this model. Also, a numerical example is used to show accuracy of the solution procedure.Keywords: Deteriorating items, Dynamic programming, Finitereplenishment rate, Inventory control, Operation Research.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13922246 Nonlinear Time-History Analysis of 3-Dimensional Semi-rigid Steel Frames
Authors: Phu-Cuong Nguyen, Seung-Eock Kim
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This paper presents nonlinear elastic dynamic analysis of 3-D semi-rigid steel frames including geometric and connection nonlinearities. The geometric nonlinearity is considered by using stability functions and updating geometric stiffness matrix. The nonlinear behavior of the steel beam-to-column connection is considered by using a zero-length independent connection element comprising of six translational and rotational springs. The nonlinear dynamic equilibrium equations are solved by the Newmark numerical integration method. The nonlinear time-history analysis results are compared with those of previous studies and commercial SAP2000 software to verify the accuracy and efficiency of the proposed procedure.Keywords: Geometric nonlinearity, nonlinear time-historyanalysis, semi-rigid connection, stability functions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 39432245 Numerical Modeling of Steel-Composite Hybrid Tubes Subject to Static and Dynamic Loading
Authors: Y. S. Tai, M. Y. Huang, H. T. Hu
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The commercial finite element program LS-DYNA was employed to evaluate the response and energy absorbing capacity of cylindrical metal tubes that are externally wrapped with composite. The effects of composite wall thickness, loading conditions and fiber ply orientation were examined. The results demonstrate that a wrapped composite can be utilized effectively to enhance the crushing characteristics and energy absorbing capacity of the tubes. Increasing the thickness of the composite increases the mean force and the specific energy absorption under both static and dynamic crushing. The ply pattern affects the energy absorption capacity and the failure mode of the metal tube and the composite material property is also significant in determining energy absorption efficiency.
Keywords: fiber-reinforced metal tubes, energy absorption, axial crushing, impact loading.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25152244 LQR and SMC Stabilization of a New Unmanned Aerial Vehicle
Authors: Kaan T. Oner, Ertugrul Cetinsoy, Efe Sirimoglu, Cevdet Hancer, Taylan Ayken, Mustafa Unel
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We present our ongoing work on the development of a new quadrotor aerial vehicle which has a tilt-wing mechanism. The vehicle is capable of take-off/landing in vertical flight mode (VTOL) and flying over long distances in horizontal flight mode. Full dynamic model of the vehicle is derived using Newton-Euler formulation. Linear and nonlinear controllers for the stabilization of attitude of the vehicle and control of its altitude have been designed and implemented via simulations. In particular, an LQR controller has been shown to be quite effective in the vertical flight mode for all possible yaw angles. A sliding mode controller (SMC) with recursive nature has also been proposed to stabilize the vehicle-s attitude and altitude. Simulation results show that proposed controllers provide satisfactory performance in achieving desired maneuvers.Keywords: UAV, VTOL, dynamic model, stabilization, LQR, SMC
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20932243 Monitoring and Fault-Recovery Capacity with Waveguide Grating-based Optical Switch over WDM/OCDMA-PON
Authors: Yao-Tang Chang, Chuen-Ching Wang, Shu-Han Hu
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In order to implement flexibility as well as survivable capacities over passive optical network (PON), a new automatic random fault-recovery mechanism with array-waveguide-grating based (AWG-based) optical switch (OSW) is presented. Firstly, wavelength-division-multiplexing and optical code-division multiple-access (WDM/OCDMA) scheme are configured to meet the various geographical locations requirement between optical network unit (ONU) and optical line terminal (OLT). The AWG-base optical switch is designed and viewed as central star-mesh topology to prohibit/decrease the duplicated redundant elements such as fiber and transceiver as well. Hence, by simple monitoring and routing switch algorithm, random fault-recovery capacity is achieved over bi-directional (up/downstream) WDM/OCDMA scheme. When error of distribution fiber (DF) takes place or bit-error-rate (BER) is higher than 10-9 requirement, the primary/slave AWG-based OSW are adjusted and controlled dynamically to restore the affected ONU groups via the other working DFs immediately.Keywords: Random fault recovery mechanism, Array-waveguide-grating based optical switch (AWG- based OSW), wavelength-division-multiplexing and optical code-divisionmultiple-access (WDM/ OCDMA)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16312242 Fitness Action Recognition Based on MediaPipe
Authors: Zixuan Xu, Yichun Lou, Yang Song, Zihuai Lin
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MediaPipe is an open-source machine learning computer vision framework that can be ported into a multi-platform environment, which makes it easier to use it to recognize human activity. Based on this framework, many human recognition systems have been created, but the fundamental issue is the recognition of human behavior and posture. In this paper, two methods are proposed to recognize human gestures based on MediaPipe, the first one uses the Adaptive Boosting algorithm to recognize a series of fitness gestures, and the second one uses the Fast Dynamic Time Warping algorithm to recognize 413 continuous fitness actions. These two methods are also applicable to any human posture movement recognition.
Keywords: Computer Vision, MediaPipe, Adaptive Boosting, Fast Dynamic Time Warping.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8022241 The Extent of Land Use Externalities in the Fringe of Jakarta Metropolitan: An Application of Spatial Panel Dynamic Land Value Model
Authors: Rahma Fitriani, Eni Sumarminingsih, Suci Astutik
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In a fast growing region, conversion of agricultural lands which are surrounded by some new development sites will occur sooner than expected. This phenomenon has been experienced by many regions in Indonesia, especially the fringe of Jakarta (BoDeTaBek). Being Indonesia’s capital city, rapid conversion of land in this area is an unavoidable process. The land conversion expands spatially into the fringe regions, which were initially dominated by agricultural land or conservation sites. Without proper control or growth management, this activity will invite greater costs than benefits. The current land use is the use which maximizes its value. In order to maintain land for agricultural activity or conservation, some efforts are needed to keep the land value of this activity as high as possible. In this case, the knowledge regarding the functional relationship between land value and its driving forces is necessary. In a fast growing region, development externalities are the assumed dominant driving force. Land value is the product of the past decision of its use leading to its value. It is also affected by the local characteristics and the observed surrounded land use (externalities) from the previous period. The effect of each factor on land value has dynamic and spatial virtues; an empirical spatial dynamic land value model will be more useful to capture them. The model will be useful to test and to estimate the extent of land use externalities on land value in the short run as well as in the long run. It serves as a basis to formulate an effective urban growth management’s policy. This study will apply the model to the case of land value in the fringe of Jakarta Metropolitan. The model will be used further to predict the effect of externalities on land value, in the form of prediction map. For the case of Jakarta’s fringe, there is some evidence about the significance of neighborhood urban activity – negative externalities, the previous land value and local accessibility on land value. The effects are accumulated dynamically over years, but they will fully affect the land value after six years.
Keywords: Growth management, land use externalities, land value, spatial panel dynamic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9902240 Discrete Polyphase Matched Filtering-based Soft Timing Estimation for Mobile Wireless Systems
Authors: Thomas O. Olwal, Michael A. van Wyk, Barend J. van Wyk
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In this paper we present a soft timing phase estimation (STPE) method for wireless mobile receivers operating in low signal to noise ratios (SNRs). Discrete Polyphase Matched (DPM) filters, a Log-maximum a posterior probability (MAP) and/or a Soft-output Viterbi algorithm (SOVA) are combined to derive a new timing recovery (TR) scheme. We apply this scheme to wireless cellular communication system model that comprises of a raised cosine filter (RCF), a bit-interleaved turbo-coded multi-level modulation (BITMM) scheme and the channel is assumed to be memory-less. Furthermore, no clock signals are transmitted to the receiver contrary to the classical data aided (DA) models. This new model ensures that both the bandwidth and power of the communication system is conserved. However, the computational complexity of ideal turbo synchronization is increased by 50%. Several simulation tests on bit error rate (BER) and block error rate (BLER) versus low SNR reveal that the proposed iterative soft timing recovery (ISTR) scheme outperforms the conventional schemes.
Keywords: discrete polyphase matched filters, maximum likelihood estimators, soft timing phase estimation, wireless mobile systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16842239 Scenario and Decision Analysis for Solar Energy in Egypt by 2035 Using Dynamic Bayesian Network
Authors: Rawaa H. El-Bidweihy, Hisham M. Abdelsalam, Ihab A. El-Khodary
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Bayesian networks are now considered to be a promising tool in the field of energy with different applications. In this study, the aim was to indicate the states of a previous constructed Bayesian network related to the solar energy in Egypt and the factors affecting its market share, depending on the followed data distribution type for each factor, and using either the Z-distribution approach or the Chebyshev’s inequality theorem. Later on, the separate and the conditional probabilities of the states of each factor in the Bayesian network were derived, either from the collected and scrapped historical data or from estimations and past studies. Results showed that we could use the constructed model for scenario and decision analysis concerning forecasting the total percentage of the market share of the solar energy in Egypt by 2035 and using it as a stable renewable source for generating any type of energy needed. Also, it proved that whenever the use of the solar energy increases, the total costs decreases. Furthermore, we have identified different scenarios, such as the best, worst, 50/50, and most likely one, in terms of the expected changes in the percentage of the solar energy market share. The best scenario showed an 85% probability that the market share of the solar energy in Egypt will exceed 10% of the total energy market, while the worst scenario showed only a 24% probability that the market share of the solar energy in Egypt will exceed 10% of the total energy market. Furthermore, we applied policy analysis to check the effect of changing the controllable (decision) variable’s states acting as different scenarios, to show how it would affect the target nodes in the model. Additionally, the best environmental and economical scenarios were developed to show how other factors are expected to be, in order to affect the model positively. Additional evidence and derived probabilities were added for the weather dynamic nodes whose states depend on time, during the process of converting the Bayesian network into a dynamic Bayesian network.
Keywords: Bayesian network, Chebyshev, decision variable, dynamic Bayesian network, Z-distribution
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4882238 The Evaluation of Gravity Anomalies Based on Global Models by Land Gravity Data
Authors: M. Yilmaz, I. Yilmaz, M. Uysal
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The Earth system generates different phenomena that are observable at the surface of the Earth such as mass deformations and displacements leading to plate tectonics, earthquakes, and volcanism. The dynamic processes associated with the interior, surface, and atmosphere of the Earth affect the three pillars of geodesy: shape of the Earth, its gravity field, and its rotation. Geodesy establishes a characteristic structure in order to define, monitor, and predict of the whole Earth system. The traditional and new instruments, observables, and techniques in geodesy are related to the gravity field. Therefore, the geodesy monitors the gravity field and its temporal variability in order to transform the geodetic observations made on the physical surface of the Earth into the geometrical surface in which positions are mathematically defined. In this paper, the main components of the gravity field modeling, (Free-air and Bouguer) gravity anomalies are calculated via recent global models (EGM2008, EIGEN6C4, and GECO) over a selected study area. The model-based gravity anomalies are compared with the corresponding terrestrial gravity data in terms of standard deviation (SD) and root mean square error (RMSE) for determining the best fit global model in the study area at a regional scale in Turkey. The least SD (13.63 mGal) and RMSE (15.71 mGal) were obtained by EGM2008 for the Free-air gravity anomaly residuals. For the Bouguer gravity anomaly residuals, EIGEN6C4 provides the least SD (8.05 mGal) and RMSE (8.12 mGal). The results indicated that EIGEN6C4 can be a useful tool for modeling the gravity field of the Earth over the study area.
Keywords: Free-air gravity anomaly, Bouguer gravity anomaly, global model, land gravity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9622237 Frequency-Dependent and Full Range Tunable Phase Shifter
Authors: Yufu Yin, Tao Lin, Shanghong Zhao, Zihang Zhu, Xuan Li, Wei Jiang, Qiurong Zheng, Hui Wang
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In this paper, a frequency-dependent and tunable phase shifter is proposed and numerically analyzed. The key devices are the dual-polarization binary phase shift keying modulator (DP-BPSK) and the fiber Bragg grating (FBG). The phase-frequency response of the FBG is employed to determine the frequency-dependent phase shift. The simulation results show that a linear phase shift of the recovered output microwave signal which depends on the frequency of the input RF signal is achieved. In addition, by adjusting the power of the RF signal, the full range phase shift from 0° to 360° can be realized. This structure shows the spurious free dynamic range (SFDR) of 70.90 dB·Hz2/3 and 72.11 dB·Hz2/3 under different RF powers.
Keywords: Microwave photonics, phase shifter, spurious free dynamic range, frequency-dependent.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10562236 Simulation of Dynamics of a Permanent Magnet Linear Actuator
Authors: Ivan Yatchev, Ewen Ritchie
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Comparison of two approaches for the simulation of the dynamic behaviour of a permanent magnet linear actuator is presented. These are full coupled model, where the electromagnetic field, electric circuit and mechanical motion problems are solved simultaneously, and decoupled model, where first a set of static magnetic filed analysis is carried out and then the electric circuit and mechanical motion equations are solved employing bi-cubic spline approximations of the field analysis results. The results show that the proposed decoupled model is of satisfactory accuracy and gives more flexibility when the actuator response is required to be estimated for different external conditions, e.g. external circuit parameters or mechanical loads.Keywords: Coupled problems, dynamic models, finite elementanalysis, linear actuators, permanent magnets.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 27512235 Optimal Maintenance and Improvement Policies in Water Distribution System: Markov Decision Process Approach
Authors: Jong Woo Kim, Go Bong Choi, Sang Hwan Son, Dae Shik Kim, Jung Chul Suh, Jong Min Lee
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The Markov decision process (MDP) based methodology is implemented in order to establish the optimal schedule which minimizes the cost. Formulation of MDP problem is presented using the information about the current state of pipe, improvement cost, failure cost and pipe deterioration model. The objective function and detailed algorithm of dynamic programming (DP) are modified due to the difficulty of implementing the conventional DP approaches. The optimal schedule derived from suggested model is compared to several policies via Monte Carlo simulation. Validity of the solution and improvement in computational time are proved.
Keywords: Markov decision processes, Dynamic Programming, Monte Carlo simulation, Periodic replacement, Weibull distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28062234 DEA-Based Variable Structure Position Control of DC Servo Motor
Authors: Ladan Maijama’a, Jibril D. Jiya, Ejike C. Anene
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This paper presents Differential Evolution Algorithm (DEA) based Variable Structure Position Control (VSPC) of Laboratory DC servomotor (LDCSM). DEA is employed for the optimal tuning of Variable Structure Control (VSC) parameters for position control of a DC servomotor. The VSC combines the techniques of Sliding Mode Control (SMC) that gives the advantages of small overshoot, improved step response characteristics, faster dynamic response and adaptability to plant parameter variations, suppressed influences of disturbances and uncertainties in system behavior. The results of the simulation responses of the VSC parameters adjustment by DEA were performed in Matlab Version 2010a platform and yield better dynamic performance compared with the untuned VSC designed.Keywords: Differential evolution algorithm, laboratory DC servomotor, sliding mode control, variable structure control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15532233 Nonlinear Dynamic Analysis of Base-Isolated Structures Using a Partitioned Solution Approach and an Exponential Model
Authors: Nicolò Vaiana, Filip C. Filippou, Giorgio Serino
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The solution of the nonlinear dynamic equilibrium equations of base-isolated structures adopting a conventional monolithic solution approach, i.e. an implicit single-step time integration method employed with an iteration procedure, and the use of existing nonlinear analytical models, such as differential equation models, to simulate the dynamic behavior of seismic isolators can require a significant computational effort. In order to reduce numerical computations, a partitioned solution method and a one dimensional nonlinear analytical model are presented in this paper. A partitioned solution approach can be easily applied to base-isolated structures in which the base isolation system is much more flexible than the superstructure. Thus, in this work, the explicit conditionally stable central difference method is used to evaluate the base isolation system nonlinear response and the implicit unconditionally stable Newmark’s constant average acceleration method is adopted to predict the superstructure linear response with the benefit in avoiding iterations in each time step of a nonlinear dynamic analysis. The proposed mathematical model is able to simulate the dynamic behavior of seismic isolators without requiring the solution of a nonlinear differential equation, as in the case of widely used differential equation model. The proposed mixed explicit-implicit time integration method and nonlinear exponential model are adopted to analyze a three dimensional seismically isolated structure with a lead rubber bearing system subjected to earthquake excitation. The numerical results show the good accuracy and the significant computational efficiency of the proposed solution approach and analytical model compared to the conventional solution method and mathematical model adopted in this work. Furthermore, the low stiffness value of the base isolation system with lead rubber bearings allows to have a critical time step considerably larger than the imposed ground acceleration time step, thus avoiding stability problems in the proposed mixed method.
Keywords: Base-isolated structures, earthquake engineering, mixed time integration, nonlinear exponential model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15692232 Modeling of a UAV Longitudinal Dynamics through System Identification Technique
Authors: Asadullah I. Qazi, Mansoor Ahsan, Zahir Ashraf, Uzair Ahmad
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System identification of an Unmanned Aerial Vehicle (UAV), to acquire its mathematical model, is a significant step in the process of aircraft flight automation. The need for reliable mathematical model is an established requirement for autopilot design, flight simulator development, aircraft performance appraisal, analysis of aircraft modifications, preflight testing of prototype aircraft and investigation of fatigue life and stress distribution etc. This research is aimed at system identification of a fixed wing UAV by means of specifically designed flight experiment. The purposely designed flight maneuvers were performed on the UAV and aircraft states were recorded during these flights. Acquired data were preprocessed for noise filtering and bias removal followed by parameter estimation of longitudinal dynamics transfer functions using MATLAB system identification toolbox. Black box identification based transfer function models, in response to elevator and throttle inputs, were estimated using least square error technique. The identification results show a high confidence level and goodness of fit between the estimated model and actual aircraft response.
Keywords: Black box modeling, fixed wing aircraft, least square error, longitudinal dynamics, system identification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11212231 Complex-Valued Neural Network in Signal Processing: A Study on the Effectiveness of Complex Valued Generalized Mean Neuron Model
Authors: Anupama Pande, Ashok Kumar Thakur, Swapnoneel Roy
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A complex valued neural network is a neural network which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in signal processing. In Neural networks, generalized mean neuron model (GMN) is often discussed and studied. The GMN includes a new aggregation function based on the concept of generalized mean of all the inputs to the neuron. This paper aims to present exhaustive results of using Generalized Mean Neuron model in a complex-valued neural network model that uses the back-propagation algorithm (called -Complex-BP-) for learning. Our experiments results demonstrate the effectiveness of a Generalized Mean Neuron Model in a complex plane for signal processing over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error required on a Generalized Mean neural network model. Some inherent properties of this complex back propagation algorithm are also studied and discussed.Keywords: Complex valued neural network, Generalized Meanneuron model, Signal processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17202230 A New Approach to Design Policies for the Adoption of Alternative Fuel-Technology Powertrains
Authors: Reza Fazeli, Vitor Leal, Jorge Pinho de Sousa
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Planning the transition period for the adoption of alternative fuel-technology powertrains is a challenging task that requires sophisticated analysis tools. In this study, a system dynamic approach was applied to analyze the bi-directional interaction between the development of the refueling station network and vehicle sales. Besides, the developed model was used to estimate the transition cost to reach a predefined target (share of alternative fuel vehicles) in different scenarios. Several scenarios have been analyzed to investigate the effectiveness and cost of incentives on the initial price of vehicles, and on the evolution of fuel and refueling stations. Obtained results show that a combined set of incentives will be more effective than just a single specific type of incentives.Keywords: adoption of Alternative Fuel Vehicles, System Dynamic Analysis, Plug-in Hybrid Vehicles
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14572229 Intelligent Temperature Controller for Water-Bath System
Authors: Om Prakash Verma, Rajesh Singla, Rajesh Kumar
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Conventional controller’s usually required a prior knowledge of mathematical modelling of the process. The inaccuracy of mathematical modelling degrades the performance of the process, especially for non-linear and complex control problem. The process used is Water-Bath system, which is most widely used and nonlinear to some extent. For Water-Bath system, it is necessary to attain desired temperature within a specified period of time to avoid the overshoot and absolute error, with better temperature tracking capability, else the process is disturbed.
To overcome above difficulties intelligent controllers, Fuzzy Logic (FL) and Adaptive Neuro-Fuzzy Inference System (ANFIS), are proposed in this paper. The Fuzzy controller is designed to work with knowledge in the form of linguistic control rules. But the translation of these linguistic rules into the framework of fuzzy set theory depends on the choice of certain parameters, for which no formal method is known. To design ANFIS, Fuzzy-Inference-System is combined with learning capability of Neural-Network.
It is analyzed that ANFIS is best suitable for adaptive temperature control of above system. As compared to PID and FLC, ANFIS produces a stable control signal. It has much better temperature tracking capability with almost zero overshoot and minimum absolute error.
Keywords: PID Controller, FLC, ANFIS, Non-Linear Control System, Water-Bath System, MATLAB-7.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 55372228 An Improved Scheduling Strategy in Cloud Using Trust Based Mechanism
Authors: D. Sumathi, P. Poongodi
Abstract:
Cloud Computing refers to applications delivered as services over the internet, and the datacenters that provide those services with hardware and systems software. These were earlier referred to as Software as a Service (SaaS). Scheduling is justified by job components (called tasks), lack of information. In fact, in a large fraction of jobs from machine learning, bio-computing, and image processing domains, it is possible to estimate the maximum time required for a task in the job. This study focuses on Trust based scheduling to improve cloud security by modifying Heterogeneous Earliest Finish Time (HEFT) algorithm. It also proposes TR-HEFT (Trust Reputation HEFT) which is then compared to Dynamic Load Scheduling.Keywords: Software as a Service (SaaS), Trust, Heterogeneous Earliest Finish Time (HEFT) algorithm, Dynamic Load Scheduling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21852227 Study of Asphaltene Precipitation İnduced Formation Damage During CO2 Injection for a Malaysian Light Oil
Authors: Sima Sh. Alian, Abdul Aziz Omar, Ali F. Alta'ee, Irzie Hani
Abstract:
In this work, the precipitation of asphaltene from a Malaysian light oil reservoir was studies. A series of experiments were designed and carried out to examine the effect of CO2 injection on asphaltene precipitation. Different pressures of injections were used in Dynamic flooding experiment in order to investigate the effect of pressure versus injection pore volume of CO2. These dynamic displacement tests simulate reservoir condition. Results show that by increasing the pore volume of injected gas asphaltene precipitation will increases, also rise in injection pressure causes less precipitation. Sandstone core plug was used to represent reservoir formation during displacement test; therefore it made it possible to study the effect of present of asphaltene on formation. It is found out that the precipitated asphaltene can reduce permeability and porosity which is not favorable during oil production.
Keywords: Asphaltene, asphaltene precipitation, enhanced oil recovery.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 38332226 New Dynamic Constitutive Model for OFHC Copper Film
Authors: Jin Sung Kim, Hoon Huh
Abstract:
The material properties of OFHC copper film was investigated with the High-Speed Material Micro Testing Machine (HSMMTM) at the high strain rates. The rate-dependent stress-strain curves from the experiment and the Johnson−Cook curve fitting showed large discrepancies as the plastic strain increases since the constitutive model implies no rate-dependent strain hardening effect. A new constitutive model was proposed in consideration of rate-dependent strain hardening effect. The strain rate hardening term in the new constitutive model consists of the strain rate sensitivity coefficients of the yield strength and strain hardening.
Keywords: Rate dependent material properties, Dynamic constitutive model, OFHC copper film, Strain rate.
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