Search results for: Centroid Algorithm
792 Avoiding Catastrophic Forgetting by a Dual-Network Memory Model Using a Chaotic Neural Network
Authors: Motonobu Hattori
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In neural networks, when new patterns are learned by a network, the new information radically interferes with previously stored patterns. This drawback is called catastrophic forgetting or catastrophic interference. In this paper, we propose a biologically inspired neural network model which overcomes this problem. The proposed model consists of two distinct networks: one is a Hopfield type of chaotic associative memory and the other is a multilayer neural network. We consider that these networks correspond to the hippocampus and the neocortex of the brain, respectively. Information given is firstly stored in the hippocampal network with fast learning algorithm. Then the stored information is recalled by chaotic behavior of each neuron in the hippocampal network. Finally, it is consolidated in the neocortical network by using pseudopatterns. Computer simulation results show that the proposed model has much better ability to avoid catastrophic forgetting in comparison with conventional models.
Keywords: catastrophic forgetting, chaotic neural network, complementary learning systems, dual-network
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2078791 Using a Semantic Self-Organising Web Page-Ranking Mechanism for Public Administration and Education
Authors: Marios Poulos, Sozon Papavlasopoulos, V. S. Belesiotis
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In the proposed method for Web page-ranking, a novel theoretic model is introduced and tested by examples of order relationships among IP addresses. Ranking is induced using a convexity feature, which is learned according to these examples using a self-organizing procedure. We consider the problem of selforganizing learning from IP data to be represented by a semi-random convex polygon procedure, in which the vertices correspond to IP addresses. Based on recent developments in our regularization theory for convex polygons and corresponding Euclidean distance based methods for classification, we develop an algorithmic framework for learning ranking functions based on a Computational Geometric Theory. We show that our algorithm is generic, and present experimental results explaining the potential of our approach. In addition, we explain the generality of our approach by showing its possible use as a visualization tool for data obtained from diverse domains, such as Public Administration and Education.Keywords: Computational Geometry, Education, e-Governance, Semantic Web.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1741790 Neural Networks for Short Term Wind Speed Prediction
Authors: K. Sreelakshmi, P. Ramakanthkumar
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Predicting short term wind speed is essential in order to prevent systems in-action from the effects of strong winds. It also helps in using wind energy as an alternative source of energy, mainly for Electrical power generation. Wind speed prediction has applications in Military and civilian fields for air traffic control, rocket launch, ship navigation etc. The wind speed in near future depends on the values of other meteorological variables, such as atmospheric pressure, moisture content, humidity, rainfall etc. The values of these parameters are obtained from a nearest weather station and are used to train various forms of neural networks. The trained model of neural networks is validated using a similar set of data. The model is then used to predict the wind speed, using the same meteorological information. This paper reports an Artificial Neural Network model for short term wind speed prediction, which uses back propagation algorithm.Keywords: Short term wind speed prediction, Neural networks, Back propagation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3048789 Finite Element Modeling of Rotating Mixing of Toothpaste
Authors: Inamullah Bhatti, Ahsanullah Baloch, Khadija Qureshi
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The objective of this research is to examine the shear thinning behaviour of mixing flow of non-Newtonian fluid like toothpaste in the dissolution container with rotating stirrer. The problem under investigation is related to the chemical industry. Mixing of fluid is performed in a cylindrical container with rotating stirrer, where stirrer is eccentrically placed on the lid of the container. For the simulation purpose the associated motion of the fluid is considered as revolving of the container, with stick stirrer. For numerical prediction, a time-stepping finite element algorithm in a cylindrical polar coordinate system is adopted based on semi-implicit Taylor-Galerkin/pressure-correction scheme. Numerical solutions are obtained for non-Newtonian fluids employing power law model. Variations with power law index have been analysed, with respect to the flow structure and pressure drop.
Keywords: finite element simulation, mixing fluid, rheology, rotating flow, toothpaste
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2245788 Error Correction Method for 2D Ultra-Wideband Indoor Wireless Positioning System Using Logarithmic Error Model
Authors: Phornpat Chewasoonthorn, Surat Kwanmuang
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Indoor positioning technologies have been evolved rapidly. They augment the Global Positioning System (GPS) which requires line-of-sight to the sky to track the location of people or objects. In this study, we developed an error correction method for an indoor real-time location system (RTLS) based on an ultra-wideband (UWB) sensor from Decawave. Multiple stationary nodes (anchor) were installed throughout the workspace. The distance between stationary and moving nodes (tag) can be measured using a two-way-ranging (TWR) scheme. The result has shown that the uncorrected ranging error from the sensor system can be as large as 1 m. To reduce ranging error and thus increase positioning accuracy, we present an online correction algorithm using the Kalman filter. The results from experiments have shown that the system can reduce ranging error down to 5 cm.
Keywords: Indoor positioning, ultra-wideband, error correction, Kalman filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 514787 A Real Time Collision Avoidance Algorithm for Mobile Robot based on Elastic Force
Authors: Kyung Hyun, Choi, Minh Ngoc, Nong, M. Asif Ali, Rehmani
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This present paper proposes the modified Elastic Strip method for mobile robot to avoid obstacles with a real time system in an uncertain environment. The method deals with the problem of robot in driving from an initial position to a target position based on elastic force and potential field force. To avoid the obstacles, the robot has to modify the trajectory based on signal received from the sensor system in the sampling times. It was evident that with the combination of Modification Elastic strip and Pseudomedian filter to process the nonlinear data from sensor uncertainties in the data received from the sensor system can be reduced. The simulations and experiments of these methods were carried out.Keywords: Collision avoidance, Avoidance obstacle, Elastic Strip, Real time collision avoidance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1985786 The Decentralized Nonlinear Controller of Robot Manipulator with External Load Compensation
Authors: Sun Lim, Il-Kyun Jung
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This paper describes a newly designed decentralized nonlinear control strategy to control a robot manipulator. Based on the concept of the nonlinear state feedback theory and decentralized concept is developed to improve the drawbacks in previous works concerned with complicate intelligent control and low cost effective sensor. The control methodology is derived in the sense of Lyapunov theorem so that the stability of the control system is guaranteed. The decentralized algorithm does not require other joint angle and velocity information. Individual Joint controller is implemented using a digital processor with nearly actuator to make it possible to achieve good dynamics and modular. Computer simulation result has been conducted to validate the effectiveness of the proposed control scheme under the occurrence of possible uncertainties and different reference trajectories. The merit of the proposed control system is indicated in comparison with a classical control system.Keywords: Robot manipulator control, nonlinear controller, Lyapunov based stability, Interconnection compensation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1614785 Enhanced Approaches to Rectify the Noise, Illumination and Shadow Artifacts
Authors: M. Sankari, C. Meena
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Enhancing the quality of two dimensional signals is one of the most important factors in the fields of video surveillance and computer vision. Usually in real-life video surveillance, false detection occurs due to the presence of random noise, illumination and shadow artifacts. The detection methods based on background subtraction faces several problems in accurately detecting objects in realistic environments: In this paper, we propose a noise removal algorithm using neighborhood comparison method with thresholding. The illumination variations correction is done in the detected foreground objects by using an amalgamation of techniques like homomorphic decomposition, curvelet transformation and gamma adjustment operator. Shadow is removed using chromaticity estimator with local relation estimator. Results are compared with the existing methods and prove as high robustness in the video surveillance.
Keywords: Chromaticity Estimator, Curvelet Transformation, Denoising, Gamma correction, Homomorphic, Neighborhood Assessment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1946784 Prediction of Phenolic Compound Migration Process through Soil Media using Artificial Neural Network Approach
Authors: Supriya Pal, Kalyan Adhikari, Somnath Mukherjee, Sudipta Ghosh
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This study presents the application of artificial neural network for modeling the phenolic compound migration through vertical soil column. A three layered feed forward neural network with back propagation training algorithm was developed using forty eight experimental data sets obtained from laboratory fixed bed vertical column tests. The input parameters used in the model were the influent concentration of phenol(mg/L) on the top end of the soil column, depth of the soil column (cm), elapsed time after phenol injection (hr), percentage of clay (%), percentage of silt (%) in soils. The output of the ANN was the effluent phenol concentration (mg/L) from the bottom end of the soil columns. The ANN predicted results were compared with the experimental results of the laboratory tests and the accuracy of the ANN model was evaluated.Keywords: Modeling, Neural Networks, Phenol, Soil media
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2127783 Dynamic Fast Tracing and Smoothing Technique for Geiger-Muller Dosimeter
Authors: M. Ebrahimi Shohani, S. M. Taheri, S. M. Golgoun
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Environmental radiation dosimeter is a kind of detector that measures the dose of the radiation area. Dosimeter registers the radiation and converts it to the dose according to the calibration parameters. The limit of a dose is different at each radiation area and this limit should be notified and reported to the user and health physics department. The stochastic nature of radiation is the reason for the fluctuation of any gamma detector dosimetry. In this research we investigated Geiger-Muller type of dosimeter and tried to improve the dose measurement. Geiger-Muller dosimeter is a counter that converts registered radiation to the dose. Therefore, for better data analysis, it is necessary to apply an algorithm to smooth statistical variations of registered radiation. We proposed a method to smooth these fluctuations much more and also proposed a dynamic way to trace rapid changes of radiations. Results show that our method is fast and reliable method in comparison the traditional method.
Keywords: Geiger-Muller, radiation detection, smoothing algorithms, dosimeter, dose calculation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 419782 An Optimized Virtual Scheme for Reducing Collisions in MAC Layer
Authors: M. Sivakumar, S. Saravanan
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The main function of Medium Access Control (MAC) is to share the channel efficiently between all nodes. In the real-time scenario, there will be certain amount of wastage in bandwidth due to back-off periods. More bandwidth will be wasted in idle state if the back-off period is very high and collision may occur if the back-off period is small. So, an optimization is needed for this problem. The main objective of the work is to reduce delay due to back-off period thereby reducing collision and increasing throughput. Here a method, called the virtual back-off algorithm (VBA) is used to optimize the back-off period and thereby it increases throughput and reduces collisions. The main idea is to optimize the number of transmission for every node. A counter is introduced at each node to implement this idea. Here counter value represents the sequence number. VBA is classified into two types VBA with counter sharing (VBA-CS) and VBA with no counter sharing (VBA-NCS). These two classifications of VBA are compared for various parameters. Simulation is done in NS-2 environment. The results obtained are found to be promising.
Keywords: VBA, sequence number, counter, back-off period.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1375781 Nonlinear Model Predictive Control of Water Quality in Drinking Water Distribution Systems with DBPs Objectives
Authors: Mingyu Xie, Mietek Brdys
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The paper develops a Non-Linear Model Predictive Control (NMPC) of water quality in Drinking Water Distribution Systems (DWDS) based on the advanced non-linear quality dynamics model including disinfections by-products (DBPs). A special attention is paid to the analysis of an impact of the flow trajectories prescribed by an upper control level of the recently developed two-time scale architecture of an integrated quality and quantity control in DWDS. The new quality controller is to operate within this architecture in the fast time scale as the lower level quality controller. The controller performance is validated by a comprehensive simulation study based on an example case study DWDS.Keywords: Model predictive control, hierarchical control structure, genetic algorithm, water quality with DBPs objectives.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2467780 Smart Grid Simulator
Authors: Andrei Ursachi, Dorin Bordeasu
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The Smart Grid Simulator is a computer software based on advance algorithms which has as the main purpose to lower the energy bill in the most optimized price efficient way as possible for private households, companies or energy providers. It combines the energy provided by a number of solar modules and wind turbines with the consumption of one household or a cluster of nearby households and information regarding weather conditions and energy prices in order to predict the amount of energy that can be produced by renewable energy sources and the amount of energy that will be bought from the distributor for the following day. The user of the system will not only be able to minimize his expenditures on energy factures, but also he will be informed about his hourly consumption, electricity prices fluctuation and money spent for energy bought as well as how much money he saved each day and since he installed the system. The paper outlines the algorithm that supports the Smart Grid Simulator idea and presents preliminary test results that supports the discussion and implementation of the system.
Keywords: Applied Science, Renewable energy sources, Smart Grid, Sustainable energy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3075779 Selective Forwarding Attack and Its Detection Algorithms: A Review
Authors: Sushil Sarwa, Rajeev Kumar
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The wireless mesh networks (WMNs) are emerging technology in wireless networking as they can serve large scale high speed internet access. Due to its wireless multi-hop feature, wireless mesh network is prone to suffer from many attacks, such as denial of service attack (DoS). We consider a special case of DoS attack which is selective forwarding attack (a.k.a. gray hole attack). In such attack, a misbehaving mesh router selectively drops the packets it receives rom its predecessor mesh router. It is very hard to detect that packet loss is due to medium access collision, bad channel quality or because of selective forwarding attack. In this paper, we present a review of detection algorithms of selective forwarding attack and discuss their advantage & disadvantage. Finally we conclude this paper with open research issues and challenges.
Keywords: CAD algorithm, CHEMAS, selective forwarding attack, watchdog & pathrater, wireless mesh network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2780778 Design Application Procedures of 15 Storied 3D Reinforced Concrete Shear Wall-Frame Structure
Authors: H. Nikzad, S. Yoshitomi
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This paper presents the design application and reinforcement detailing of 15 storied reinforced concrete shear wall-frame structure based on linear static analysis. Databases are generated for section sizes based on automated structural optimization method utilizing Active-set Algorithm in MATLAB platform. The design constraints of allowable section sizes, capacity criteria and seismic provisions for static loads, combination of gravity and lateral loads are checked and determined based on ASCE 7-10 documents and ACI 318-14 design provision. The result of this study illustrates the efficiency of proposed method, and is expected to provide a useful reference in designing of RC shear wall-frame structures.
Keywords: Structural optimization, linear static analysis, ETABS, MATLAB, RC shear wall-frame structures.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 928777 Modelling of Multi-Agent Systems for the Scheduling of Multi-EV Charging from Power Limited Sources
Authors: Manan’Iarivo Rasolonjanahary, Chris Bingham, Nigel Schofield, Masoud Bazargan
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This paper presents the research and application of model predictive scheduled charging of electric vehicles (EV) subject to limited available power resource. To focus on algorithm and operational characteristics, the EV interface to the source is modelled as a battery state equation during the charging operation. The researched methods allow for the priority scheduling of EV charging in a multi-vehicle regime and when subject to limited source power availability. Priority attribution for each connected EV is described. The validity of the developed methodology is shown through the simulation of different scenarios of charging operation of multiple connected EVs including non-scheduled and scheduled operation with various numbers of vehicles. Performance of the developed algorithms is also reported with the recommendation of the choice of suitable parameters.
Keywords: Model predictive control, non-scheduled, power limited sources, scheduled and stop-start battery charging.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 490776 Performance Analysis of a Series of Adaptive Filters in Non-Stationary Environment for Noise Cancelling Setup
Authors: Anam Rafique, Syed Sohail Ahmed
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One of the essential components of much of DSP application is noise cancellation. Changes in real time signals are quite rapid and swift. In noise cancellation, a reference signal which is an approximation of noise signal (that corrupts the original information signal) is obtained and then subtracted from the noise bearing signal to obtain a noise free signal. This approximation of noise signal is obtained through adaptive filters which are self adjusting. As the changes in real time signals are abrupt, this needs adaptive algorithm that converges fast and is stable. Least mean square (LMS) and normalized LMS (NLMS) are two widely used algorithms because of their plainness in calculations and implementation. But their convergence rates are small. Adaptive averaging filters (AFA) are also used because they have high convergence, but they are less stable. This paper provides the comparative study of LMS and Normalized NLMS, AFA and new enhanced average adaptive (Average NLMS-ANLMS) filters for noise cancelling application using speech signals.Keywords: AFA, ANLMS, LMS, NLMS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1924775 Concept Abduction in Description Logics with Cardinality Restrictions
Authors: Viet-Hoang Vu, Nhan Le-Thanh
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Recently the usefulness of Concept Abduction, a novel non-monotonic inference service for Description Logics (DLs), has been argued in the context of ontology-based applications such as semantic matchmaking and resource retrieval. Based on tableau calculus, a method has been proposed to realize this reasoning task in ALN, a description logic that supports simple cardinality restrictions as well as other basic constructors. However, in many ontology-based systems, the representation of ontology would require expressive formalisms for capturing domain-specific constraints, this language is not sufficient. In order to increase the applicability of the abductive reasoning method in such contexts, we would like to present in the scope of this paper an extension of the tableaux-based algorithm for dealing with concepts represented inALCQ, the description logic that extends ALN with full concept negation and quantified number restrictions.
Keywords: Abductive reasoning, description logics, semantic matchmaking, non-monotonic inference, tableaux-based method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1546774 Genetic-based Anomaly Detection in Logs of Process Aware Systems
Authors: Hanieh Jalali, Ahmad Baraani
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Nowaday-s, many organizations use systems that support business process as a whole or partially. However, in some application domains, like software development and health care processes, a normative Process Aware System (PAS) is not suitable, because a flexible support is needed to respond rapidly to new process models. On the other hand, a flexible Process Aware System may be vulnerable to undesirable and fraudulent executions, which imposes a tradeoff between flexibility and security. In order to make this tradeoff available, a genetic-based anomaly detection model for logs of Process Aware Systems is presented in this paper. The detection of an anomalous trace is based on discovering an appropriate process model by using genetic process mining and detecting traces that do not fit the appropriate model as anomalous trace; therefore, when used in PAS, this model is an automated solution that can support coexistence of flexibility and security.Keywords: Anomaly Detection, Genetic Algorithm, ProcessAware Systems, Process Mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1905773 Energy Distribution of EEG Signals: EEG Signal Wavelet-Neural Network Classifier
Authors: I. Omerhodzic, S. Avdakovic, A. Nuhanovic, K. Dizdarevic
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In this paper, a wavelet-based neural network (WNN) classifier for recognizing EEG signals is implemented and tested under three sets EEG signals (healthy subjects, patients with epilepsy and patients with epileptic syndrome during the seizure). First, the Discrete Wavelet Transform (DWT) with the Multi-Resolution Analysis (MRA) is applied to decompose EEG signal at resolution levels of the components of the EEG signal (δ, θ, α, β and γ) and the Parseval-s theorem are employed to extract the percentage distribution of energy features of the EEG signal at different resolution levels. Second, the neural network (NN) classifies these extracted features to identify the EEGs type according to the percentage distribution of energy features. The performance of the proposed algorithm has been evaluated using in total 300 EEG signals. The results showed that the proposed classifier has the ability of recognizing and classifying EEG signals efficiently.
Keywords: Epilepsy, EEG, Wavelet transform, Energydistribution, Neural Network, Classification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1959772 Five-axis Strip Machining with Barrel Cutter Based On Tolerance Constraint for Sculptured Surfaces
Authors: YaoAn Lu, QingZhen Bi, BaoRui Du, ShuLin Chen, LiMin Zhu, Kai Huang
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Taking the design tolerance into account, this paper presents a novel efficient approach to generate iso-scallop tool path for five-axis strip machining with a barrel cutter. The cutter location is first determined on the scallop surface instead of the design surface, and then the cutter is adjusted to locate the optimal tool position based on the differential rotation of the tool axis and satisfies the design tolerance simultaneously. The machining strip width and error are calculated with the aid of the grazing curve of the cutter. Based on the proposed tool positioning algorithm, the tool paths are generated by keeping the scallop height formed by adjacent tool paths constant. An example is conducted to confirm the validity of the proposed method.
Keywords: Strip machining, barrel cutter, iso-scallop tool path, sculptured surfaces, differential motion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2516771 Dynamic Construction Site Layout Using Ant Colony Optimization
Authors: Y. Abdelrazig
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Evolutionary optimization methods such as genetic algorithms have been used extensively for the construction site layout problem. More recently, ant colony optimization algorithms, which are evolutionary methods based on the foraging behavior of ants, have been successfully applied to benchmark combinatorial optimization problems. This paper proposes a formulation of the site layout problem in terms of a sequencing problem that is suitable for solution using an ant colony optimization algorithm. In the construction industry, site layout is a very important planning problem. The objective of site layout is to position temporary facilities both geographically and at the correct time such that the construction work can be performed satisfactorily with minimal costs and improved safety and working environment. During the last decade, evolutionary methods such as genetic algorithms have been used extensively for the construction site layout problem. This paper proposes an ant colony optimization model for construction site layout. A simple case study for a highway project is utilized to illustrate the application of the model.Keywords: Construction site layout, optimization, ant colony.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3095770 The Design of Self-evolving Artificial Immune System II for Permutation Flow-shop Problem
Authors: Meng-Hui Chen, Pei-Chann Chang, Wei-Hsiu Huang
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Artificial Immune System is adopted as a Heuristic Algorithm to solve the combinatorial problems for decades. Nevertheless, many of these applications took advantage of the benefit for applications but seldom proposed approaches for enhancing the efficiency. In this paper, we continue the previous research to develop a Self-evolving Artificial Immune System II via coordinating the T and B cell in Immune System and built a block-based artificial chromosome for speeding up the computation time and better performance for different complexities of problems. Through the design of Plasma cell and clonal selection which are relative the function of the Immune Response. The Immune Response will help the AIS have the global and local searching ability and preventing trapped in local optima. From the experimental result, the significant performance validates the SEAIS II is effective when solving the permutation flows-hop problems.Keywords: Artificial Immune System, Clonal Selection, Immune Response, Permutation Flow-shop Scheduling Problems
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1594769 Concepts Extraction from Discharge Notes using Association Rule Mining
Authors: Basak Oguz Yolcular
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A large amount of valuable information is available in plain text clinical reports. New techniques and technologies are applied to extract information from these reports. In this study, we developed a domain based software system to transform 600 Otorhinolaryngology discharge notes to a structured form for extracting clinical data from the discharge notes. In order to decrease the system process time discharge notes were transformed into a data table after preprocessing. Several word lists were constituted to identify common section in the discharge notes, including patient history, age, problems, and diagnosis etc. N-gram method was used for discovering terms co-Occurrences within each section. Using this method a dataset of concept candidates has been generated for the validation step, and then Predictive Apriori algorithm for Association Rule Mining (ARM) was applied to validate candidate concepts.Keywords: association rule mining, otorhinolaryngology, predictive apriori, text mining
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1603768 3A Distributed Method Algorithm for Exact Side Load Managing Smart Grid Using LABVIEW
Authors: N. Ravi Kumar, R. Kamalakannan
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The advancement of hybrid energy resources such as solar and wind power leading to the emergence of customer owned grid. It provides an opportunity to regulars to obtain low energy costs as well as enabling the power supplier to regulate the utility grid. There is a need to develop smart systems that will automatically submit energy demand schedule and monitors energy price signals in real-time without the prompt of customers. In this paper, a demand side energy management for a grid connected household and also smart preparation of electrical appliance have been presented. It also reduces electricity bill for the consumers in the grid. In addition to this, when production is high, the surplus energy fashioned in the customer owned grid is given to main grid or neighboring micro grids. The simulation of the entire system is presented using LabVIEW software.
Keywords: Distributed renewable energy resource, power storage devices, scheduling, smart meters, smart micro grid, electric vehicle.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1075767 Determining Earthquake Performances of Existing Reinforced Concrete Buildings by Using ANN
Authors: Musa H. Arslan, Murat Ceylan, Tayfun Koyuncu
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In this study, an Artificial Neural Network (ANN) analytical method has been developed for analyzing earthquake performances of the Reinforced Concrete (RC) buildings. 66 RC buildings with four to ten storeys were subjected to performance analysis according to the parameters which are the existing material, loading and geometrical characteristics of the buildings. The selected parameters have been thought to be effective on the performance of RC buildings. In the performance analyses stage of the study, level of performance possible to be shown by these buildings in case of an earthquake was determined on the basis of the 4-grade performance levels specified in Turkish Earthquake Code-2007 (TEC-2007). After obtaining the 4-grade performance level, selected 23 parameters of each building have been matched with the performance level. In this stage, ANN-based fast evaluation algorithm mentioned above made an economic and rapid evaluation of four to ten storey RC buildings. According to the study, the prediction accuracy of ANN has been found about 74%.Keywords: Artificial neural network, earthquake, performance, reinforced concrete.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2644766 The Optimized Cascade PI Controllers of the Generator Control Unit in the Aircraft Power System
Authors: W. Chayinthu, K-N. Areerak, K-L. Areerak, A. Srikaew
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This paper presents the optimal controller design of the generator control unit in the aircraft power system. The adaptive tabu search technique is applied to tune the controller parameters until the best terminal output voltage of generator is achieved. The output response from the system with the controllers designed by the proposed technique is compared with those from the conventional method. The transient simulations using the commercial software package show that the controllers designed from the adaptive tabu search algorithm can provide the better output performance compared with the result from the classical method. The proposed design technique is very flexible and useful for electrical aircraft engineers.Keywords: Cascade PI controllers, DQ method, Adaptive tabusearch, Generator control unit, Aircraft power system, Modeling, Simulation, Artificial Intelligence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2641765 A Post Processing Method for Quantum Prime Factorization Algorithm based on Randomized Approach
Authors: Mir Shahriar Emami, Mohammad Reza Meybodi
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Prime Factorization based on Quantum approach in two phases has been performed. The first phase has been achieved at Quantum computer and the second phase has been achieved at the classic computer (Post Processing). At the second phase the goal is to estimate the period r of equation xrN ≡ 1 and to find the prime factors of the composite integer N in classic computer. In this paper we present a method based on Randomized Approach for estimation the period r with a satisfactory probability and the composite integer N will be factorized therefore with the Randomized Approach even the gesture of the period is not exactly the real period at least we can find one of the prime factors of composite N. Finally we present some important points for designing an Emulator for Quantum Computer Simulation.Keywords: Quantum Prime Factorization, RandomizedAlgorithms, Quantum Computer Simulation, Quantum Computation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1482764 The Performance Analysis of Error Saturation Nonlinearity LMS in Impulsive Noise based on Weighted-Energy Conservation
Authors: T Panigrahi, G Panda, Mulgrew
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This paper introduces a new approach for the performance analysis of adaptive filter with error saturation nonlinearity in the presence of impulsive noise. The performance analysis of adaptive filters includes both transient analysis which shows that how fast a filter learns and the steady-state analysis gives how well a filter learns. The recursive expressions for mean-square deviation(MSD) and excess mean-square error(EMSE) are derived based on weighted energy conservation arguments which provide the transient behavior of the adaptive algorithm. The steady-state analysis for co-related input regressor data is analyzed, so this approach leads to a new performance results without restricting the input regression data to be white.Keywords: Error saturation nonlinearity, transient analysis, impulsive noise.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1770763 Multiscale Modelization of Multilayered Bi-Dimensional Soils
Authors: I. Hosni, L. Bennaceur Farah, N. Saber, R Bennaceur
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Soil moisture content is a key variable in many environmental sciences. Even though it represents a small proportion of the liquid freshwater on Earth, it modulates interactions between the land surface and the atmosphere, thereby influencing climate and weather. Accurate modeling of the above processes depends on the ability to provide a proper spatial characterization of soil moisture. The measurement of soil moisture content allows assessment of soil water resources in the field of hydrology and agronomy. The second parameter in interaction with the radar signal is the geometric structure of the soil. Most traditional electromagnetic models consider natural surfaces as single scale zero mean stationary Gaussian random processes. Roughness behavior is characterized by statistical parameters like the Root Mean Square (RMS) height and the correlation length. Then, the main problem is that the agreement between experimental measurements and theoretical values is usually poor due to the large variability of the correlation function, and as a consequence, backscattering models have often failed to predict correctly backscattering. In this study, surfaces are considered as band-limited fractal random processes corresponding to a superposition of a finite number of one-dimensional Gaussian process each one having a spatial scale. Multiscale roughness is characterized by two parameters, the first one is proportional to the RMS height, and the other one is related to the fractal dimension. Soil moisture is related to the complex dielectric constant. This multiscale description has been adapted to two-dimensional profiles using the bi-dimensional wavelet transform and the Mallat algorithm to describe more correctly natural surfaces. We characterize the soil surfaces and sub-surfaces by a three layers geo-electrical model. The upper layer is described by its dielectric constant, thickness, a multiscale bi-dimensional surface roughness model by using the wavelet transform and the Mallat algorithm, and volume scattering parameters. The lower layer is divided into three fictive layers separated by an assumed plane interface. These three layers were modeled by an effective medium characterized by an apparent effective dielectric constant taking into account the presence of air pockets in the soil. We have adopted the 2D multiscale three layers small perturbations model including, firstly air pockets in the soil sub-structure, and then a vegetable canopy in the soil surface structure, that is to simulate the radar backscattering. A sensitivity analysis of backscattering coefficient dependence on multiscale roughness and new soil moisture has been performed. Later, we proposed to change the dielectric constant of the multilayer medium because it takes into account the different moisture values of each layer in the soil. A sensitivity analysis of the backscattering coefficient, including the air pockets in the volume structure with respect to the multiscale roughness parameters and the apparent dielectric constant, was carried out. Finally, we proposed to study the behavior of the backscattering coefficient of the radar on a soil having a vegetable layer in its surface structure.
Keywords: Multiscale, bi-dimensional, wavelets, SPM, backscattering, multilayer, air pockets, vegetable.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 596