Search results for: Adaptive Network based Fuzzy Inference System (ANFIS)

Authors: Mohamed Akrout, Douglas Tweed

Abstract:

The great success of deep learning relies on efficient optimizers, which are the algorithms that decide how to adjust network weights and biases based on gradient information. One of the most effective and widely used optimizers in recent years has been the method of adaptive moments, or Adam, but the mathematical reasons behind its effectiveness are still unclear. Attempts to analyse its behaviour have remained incomplete, in part because they hinge on a conjecture which has never been proven, regarding ratios of powers of the first and second moments of the gradient. Here we show that this conjecture is in fact false, but that a modified version of it is true, and can take its place in analyses of Adam.

Keywords: Adam optimizer, Bock’s conjecture, stochastic optimization, average regret.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 333

Authors: W. Phanwanich, O. Kumdee, P. Ritthipravat, Y. Wongsawat

Abstract:

In order to alleviate the mental and physical problems of persons with disabilities, animal-assisted therapy (AAT) is one of the possible modalities that employs the merit of the human-animal interaction. Nevertheless, to achieve the purpose of AAT for persons with severe disabilities (e.g. spinal cord injury, stroke, and amyotrophic lateral sclerosis), real-time animal language interpretation is desirable. Since canine behaviors can be visually notable from its tail, this paper proposes the automatic real-time interpretation of canine tail language for human-canine interaction in the case of persons with severe disabilities. Canine tail language is captured via two 3-axis accelerometers. Directions and frequencies are selected as our features of interests. The novel fuzzy rules based on Gaussian-Trapezoidal model and center of gravity (COG)-based defuzzification method are proposed in order to interpret the features into four canine emotional behaviors, i.e., agitate, happy, scare and neutral as well as its blended emotional behaviors. The emotional behavior model is performed in the simulated dog and has also been evaluated in the real dog with the perfect recognition rate.

Keywords: Animal-assisted therapy (AAT), Persons with disabilities, Canine tail language, Fuzzy emotional behavior model

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1990

Authors: Yasser k. Ali, Hesham N. Elmahdy, Sanaa El Olla Hanfy Ahmed

Abstract:

Mobile agents are a powerful approach to develop distributed systems since they migrate to hosts on which they have the resources to execute individual tasks. In a dynamic environment like a peer-to-peer network, Agents have to be generated frequently and dispatched to the network. Thus they will certainly consume a certain amount of bandwidth of each link in the network if there are too many agents migration through one or several links at the same time, they will introduce too much transferring overhead to the links eventually, these links will be busy and indirectly block the network traffic, therefore, there is a need of developing routing algorithms that consider about traffic load. In this paper we seek to create cooperation between a probabilistic manner according to the quality measure of the network traffic situation and the agent's migration decision making to the next hop based on decision tree learning algorithms.

Keywords: Agent Migration, Decision Tree learning, ID3 algorithm, Naive Bayes Classifier

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1970

Authors: A. K. Al-Othman, F. S. Al-Fares, K. M. EL-Nagger

Abstract:

This paper presents a new optimization technique based on quantum computing principles to solve a security constrained power system economic dispatch problem (SCED). The proposed technique is a population-based algorithm, which uses some quantum computing elements in coding and evolving groups of potential solutions to reach the optimum following a partially directed random approach. The SCED problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Real Coded Quantum-Inspired Evolution Algorithm (RQIEA) is then applied to solve the constrained optimization formulation. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that RQIEA is very applicable for solving security constrained power system economic dispatch problem (SCED).

Keywords: State Estimation, Fuzzy Linear Regression, FuzzyLinear State Estimator (FLSE) and Measurements Uncertainty.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1694

Authors: Gülfem Alptekin, S. Emre Alptekin

Abstract:

Global competitiveness has recently become the biggest concern of both manufacturing and service companies. Electronic commerce, as a key technology enables the firms to reach all the potential consumers from all over the world. In this study, we have presented commonly used electronic payment systems, and then we have shown the evaluation of these systems in respect to different criteria. The payment systems which are included in this research are the credit card, the virtual credit card, the electronic money, the mobile payment, the credit transfer and the debit instruments. We have realized a systematic comparison of these systems in respect to three main criteria: Technical, economical and social. We have conducted a fuzzy multi-criteria decision making procedure to deal with the multi-attribute nature of the problem. The subjectiveness and imprecision of the evaluation process are modeled using triangular fuzzy numbers.

Keywords: Electronic payment systems, fuzzy multi-criteriadecision making, analytical hierarchy process.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1911

Authors: Zahra Ramezanpanah, Joachim Carvallo, Aurelien Rodriguez

Abstract:

This paper aims to detect anomalies in streaming data using machine learning algorithms. In this regard, we designed two separate pipelines and evaluated the effectiveness of each separately. The first pipeline, based on supervised machine learning methods, consists of two phases. In the first phase, we trained several supervised models using the UNSW-NB15 data set. We measured the efficiency of each using different performance metrics and selected the best model for the second phase. At the beginning of the second phase, we first, using Argus Server, sniffed a local area network. Several types of attacks were simulated and then sent the sniffed data to a running algorithm at short intervals. This algorithm can display the results of each packet of received data in real-time using the trained model. The second pipeline presented in this paper is based on unsupervised algorithms, in which a Temporal Graph Network (TGN) is used to monitor a local network. The TGN is trained to predict the probability of future states of the network based on its past behavior. Our contribution in this section is introducing an indicator to identify anomalies from these predicted probabilities.

Keywords: Cyber-security, Intrusion Detection Systems, Temporal Graph Network, Anomaly Detection.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 451

Authors: Hossein Pazhoumand-Dar, Amir Mohsen Toliyat Abolhassani, Ehsan Saeedi

Abstract:

Speed estimation is one of the important and practical tasks in machine vision, Robotic and Mechatronic. the availability of high quality and inexpensive video cameras, and the increasing need for automated video analysis has generated a great deal of interest in machine vision algorithms. Numerous approaches for speed estimation have been proposed. So classification and survey of the proposed methods can be very useful. The goal of this paper is first to review and verify these methods. Then we will propose a novel algorithm to estimate the speed of moving object by using fuzzy concept. There is a direct relation between motion blur parameters and object speed. In our new approach we will use Radon transform to find direction of blurred image, and Fuzzy sets to estimate motion blur length. The most benefit of this algorithm is its robustness and precision in noisy images. Our method was tested on many images with different range of SNR and is satisfiable.

Keywords: Blur Analysis, Fuzzy sets, Speed estimation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1856

Authors: M. J. Park, S. H. Lee, C. H. Lee, O. M. Kwon

Abstract:

This paper studies a secondary voltage control framework of the microgrids based on the consensus for a communication network of multiagent. The proposed control is designed by the communication network with one-way links. The communication network is modeled by a directed graph. At this time, the concept of sampling is considered as the communication constraint among each distributed generator in the microgrids. To analyze the sampling effects on the secondary voltage control of the microgrids, by using Lyapunov theory and some mathematical techniques, the sufficient condition for such problem will be established regarding linear matrix inequality (LMI). Finally, some simulation results are given to illustrate the necessity of the consideration of the sampling effects on the secondary voltage control of the microgrids.

Keywords: Microgrids, secondary control, multiagent, sampling, LMI.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1432

Authors: Frodouard Minani

Abstract:

Since last decade, wireless sensor networks (WSNs) have been used in many areas like health care, agriculture, defense, military, disaster hit areas and so on. Wireless Sensor Networks consist of a Base Station (BS) and more number of wireless sensors in order to monitor temperature, pressure, motion in different environment conditions. The key parameter that plays a major role in designing a protocol for Wireless Sensor Networks is energy efficiency which is a scarcest resource of sensor nodes and it determines the lifetime of sensor nodes. Maximizing sensor node’s lifetime is an important issue in the design of applications and protocols for Wireless Sensor Networks. Clustering sensor nodes mechanism is an effective topology control approach for helping to achieve the goal of this research. In this paper, the researcher presents an energy efficiency protocol to prolong the network lifetime based on Energy efficient clustering algorithm. The Low Energy Adaptive Clustering Hierarchy (LEACH) is a routing protocol for clusters which is used to lower the energy consumption and also to improve the lifetime of the Wireless Sensor Networks. Maximizing energy dissipation and network lifetime are important matters in the design of applications and protocols for wireless sensor networks. Proposed system is to maximize the lifetime of the Wireless Sensor Networks by choosing the farthest cluster head (CH) instead of the closest CH and forming the cluster by considering the following parameter metrics such as Node’s density, residual-energy and distance between clusters (inter-cluster distance). In this paper, comparisons between the proposed protocol and comparative protocols in different scenarios have been done and the simulation results showed that the proposed protocol performs well over other comparative protocols in various scenarios.

Keywords: Base station, clustering algorithm, energy efficient, wireless sensor networks.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 822

Authors: M. Chaoui, M-T. Laskri

Abstract:

The evolution of information and communication technology has made a very powerful support for the improvement of online learning platforms in creation of courses. This paper presents a study that attempts to explore new web architecture for creating an adaptive online learning system to profiles of learners, using the Web as a source for the automatic creation of courses for the online training platform. This architecture will reduce the time and decrease the effort performed by the drafters of the current e-learning platform, and direct adaptation of the Web content will greatly enrich the quality of online training courses.

Keywords: Web Content, e-Learning, Educational Content, LMS, Profiles of Learners

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1502

Authors: Manisha Rathi, Thierry Chaussalet

Abstract:

Hospital staff and managers are under pressure and concerned for effective use and management of scarce resources. The hospital admissions require many decisions that have complex and uncertain consequences for hospital resource utilization and patient flow. It is challenging to predict risk of admissions and length of stay of a patient due to their vague nature. There is no method to capture the vague definition of admission of a patient. Also, current methods and tools used to predict patients at risk of admission fail to deal with uncertainty in unplanned admission, LOS, patients- characteristics. The main objective of this paper is to deal with uncertainty in health system variables, and handles uncertain relationship among variables. An introduction of machine learning techniques along with statistical methods like Regression methods can be a proposed solution approach to handle uncertainty in health system variables. A model that adapts fuzzy methods to handle uncertain data and uncertain relationships can be an efficient solution to capture the vague definition of admission of a patient.

Keywords: Admission, Fuzzy, Regression, Uncertainty

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1402

Authors: Rong-Jong Wai, Chia-Ming Liu

Abstract:

Generally speaking, the mobile robot is capable of sensing its surrounding environment, interpreting the sensed information to obtain the knowledge of its location and the environment, planning a real-time trajectory to reach the object. In this process, the issue of obstacle avoidance is a fundamental topic to be challenged. Thus, an adaptive path-planning control scheme is designed without detailed environmental information, large memory size and heavy computation burden in this study for the obstacle avoidance of a mobile robot. In this scheme, the robot can gradually approach its object according to the motion tracking mode, obstacle avoidance mode, self-rotation mode, and robot state selection. The effectiveness of the proposed adaptive path-planning control scheme is verified by numerical simulations of a differential-driving mobile robot under the possible occurrence of obstacle shapes.

Keywords: Adaptive Path Planning, Mobile Robot ObstacleAvoidance

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2143

Authors: Sheela Tiwari, R. Naresh, R. Jha

Abstract:

The paper presents an investigation in to the effect of neural network predictive control of UPFC on the transient stability performance of a multimachine power system. The proposed controller consists of a neural network model of the test system. This model is used to predict the future control inputs using the damped Gauss-Newton method which employs ‘backtracking’ as the line search method for step selection. The benchmark 2 area, 4 machine system that mimics the behavior of large power systems is taken as the test system for the study and is subjected to three phase short circuit faults at different locations over a wide range of operating conditions. The simulation results clearly establish the robustness of the proposed controller to the fault location, an increase in the critical clearing time for the circuit breakers, and an improved damping of the power oscillations as compared to the conventional PI controller.

Keywords: Identification, Neural networks, Predictive control, Transient stability, UPFC.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2055

Authors: F. Nejadebrahimi, M. ArdebiliPour

Abstract:

In this paper, we are going to determine the threshold levels of adaptive modulation in a burst by burst CDMA system by a suboptimum method so that the above method attempts to increase the average bit per symbol (BPS) rate of transceiver system by switching between the different modulation modes in variable channel condition. In this method, we choose the minimum values of average bit error rate (BER) and maximum values of average BPS on different values of average channel signal to noise ratio (SNR) and then calculate the relative threshold levels of them, so that when the instantaneous SNR increases, a higher order modulation be employed for increasing throughput and vise-versa when the instantaneous SNR decreases, a lower order modulation be employed for improvement of BER. In transmission step, by this adaptive modulation method, in according to comparison between obtained estimation of pilot symbols and a set of above suboptimum threshold levels, above system chooses one of states no transmission, BPSK, 4QAM and square 16QAM for modulation of data. The expected channel in this paper is a slow Rayleigh fading.

Keywords: AQAM, burst, BER, BPS, CDMA, threshold.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1507

Authors: Su Hyung Jo, Ki Young Kim, Sang Ho Lee

Abstract:

Security management has changed from the management of security equipments and useful interface to manager. It analyzes the whole security conditions of network and preserves the network services from attacks. Secure router technology has security functions, such as intrusion detection, IPsec(IP Security) and access control, are applied to legacy router for secure networking. It controls an unauthorized router access and detects an illegal network intrusion. This paper relates to a security engine management of router based on a security policy, which is the definition of security function against a network intrusion. This paper explains the security policy and designs the structure of security engine management framework.

Keywords: Policy server, security engine, security management, security policy

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1892

Authors: B. Siva Kumar Reddy, B. Lakshmi

Abstract:

Different order modulations combined with different coding schemes, allow sending more bits per symbol, thus achieving higher throughputs and better spectral efficiencies. However, it must also be noted that when using a modulation technique such as 64- QAM with less overhead bits, better signal-to-noise ratios (SNRs) are needed to overcome any Inter symbol Interference (ISI) and maintain a certain bit error ratio (BER). The use of adaptive modulation allows wireless technologies to yielding higher throughputs while also covering long distances. The aim of this paper is to implement an Adaptive Modulation and Coding (AMC) features of the WiMAX PHY in MATLAB and to analyze the performance of the system in different channel conditions (AWGN, Rayleigh and Rician fading channel) with channel estimation and blind equalization. Simulation results have demonstrated that the increment in modulation order causes to increment in throughput and BER values. These results derived a trade-off among modulation order, FFT length, throughput, BER value and spectral efficiency. The BER changes gradually for AWGN channel and arbitrarily for Rayleigh and Rician fade channels.

Keywords: AMC, CSI, CMA, OFDM, OFDMA, WiMAX.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3073

Authors: Ekkaluk Eksook, Chutima Prommak

Abstract:

This paper address the network reliability optimization problem in the optical access network design for the 3G cellular systems. We presents a novel 0-1 integer programming model for designing optical access network topologies comprised of multi-rings with common-edge in order to guarantee always-on services. The results show that the proposed model yields access network topologies with the optimal reliablity and satisfies both network cost limitations and traffic demand requirements.

Keywords: Network Reliability, Topological Network Design, 3G Cellular Networks.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1514

Authors: Yu-Cheng Chou, Po Ting Lin

Abstract:

The network of delivering commodities has been an important design problem in our daily lives and many transportation applications. The delivery performance is evaluated based on the system reliability of delivering commodities from a source node to a sink node in the network. The system reliability is thus maximized to find the optimal routing. However, the design problem is not simple because (1) each path segment has randomly distributed attributes; (2) there are multiple commodities that consume various path capacities; (3) the optimal routing must successfully complete the delivery process within the allowable time constraints. In this paper, we want to focus on the design optimization of the Multi-State Flow Network (MSFN) for multiple commodities. We propose an efficient approach to evaluate the system reliability in the MSFN with respect to randomly distributed path attributes and find the optimal routing subject to the allowable time constraints. The delivery rates, also known as delivery currents, of the path segments are evaluated and the minimal-current arcs are eliminated to reduce the complexity of the MSFN. Accordingly, the correct optimal routing is found and the worst-case reliability is evaluated. It has been shown that the reliability of the optimal routing is at least higher than worst-case measure. Two benchmark examples are utilized to demonstrate the proposed method. The comparisons between the original and the reduced networks show that the proposed method is very efficient.

Keywords: Multiple Commodities, Multi-State Flow Network (MSFN), Time Constraints, Worst-Case Reliability (WCR)

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1430

Authors: Mohamed Othmani, Yassine Khlifi

Abstract:

This paper presents a technique for compact three dimensional (3D) object model reconstruction using wavelet networks. It consists to transform an input surface vertices into signals,and uses wavelet network parameters for signal approximations. To prove this, we use a wavelet network architecture founded on several mother wavelet families. POLYnomials WindOwed with Gaussians (POLYWOG) wavelet families are used to maximize the probability to select the best wavelets which ensure the good generalization of the network. To achieve a better reconstruction, the network is trained several iterations to optimize the wavelet network parameters until the error criterion is small enough. Experimental results will shown that our proposed technique can effectively reconstruct an irregular 3D object models when using the optimized wavelet network parameters. We will prove that an accurateness reconstruction depends on the best choice of the mother wavelets.

Keywords: 3D object, optimization, parametrization, Polywog wavelets, reconstruction, wavelet networks.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1474

Authors: Li Kewen, Su Zhaoxin, Wang Xingmou, Zhu Jian Bing

Abstract:

Conventional reservoir prediction methods ar not sufficient to explore the implicit relation between seismic attributes, and thus data utilization is low. In order to improve the predictive classification accuracy of reservoir lithology, this paper proposes a deep learning lithology prediction method based on ResNet (Residual Neural Network) and SENet (Squeeze-and-Excitation Neural Network). The neural network model is built and trained by using seismic attribute data and lithology data of Shengli oilfield, and the nonlinear mapping relationship between seismic attribute and lithology marker is established. The experimental results show that this method can significantly improve the classification effect of reservoir lithology, and the classification accuracy is close to 70%. This study can effectively predict the lithology of undrilled area and provide support for exploration and development.

Keywords: Convolutional neural network, lithology, prediction of reservoir lithology, seismic attributes.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 622

Authors: Ashish Saini, A.K. Saxena

Abstract:

In competitive electricity markets all over the world, an adoption of suitable transmission pricing model is a problem as transmission segment still operates as a monopoly. Transmission pricing is an important tool to promote investment for various transmission services in order to provide economic, secure and reliable electricity to bulk and retail customers. The nodal pricing based on SRMC (Short Run Marginal Cost) is found extremely useful by researchers for sending correct economic signals. The marginal prices must be determined as a part of solution to optimization problem i.e. to maximize the social welfare. The need to maximize the social welfare subject to number of system operational constraints is a major challenge from computation and societal point of views. The purpose of this paper is to present a nodal transmission pricing model based on SRMC by developing new mathematical expressions of real and reactive power marginal prices using GA-Fuzzy based optimal power flow framework. The impacts of selecting different social welfare functions on power marginal prices are analyzed and verified with results reported in literature. Network revenues for two different power systems are determined using expressions derived for real and reactive power marginal prices in this paper.

Keywords: Deregulation, electricity markets, nodal pricing, social welfare function, short run marginal cost.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1625

Authors: Pingping Lin, Xudong Luo, Yifan Fan

Abstract:

Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.

Keywords: Natural language processing, sentiment analysis, document analysis, multimodal sentiment analysis, deep learning.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1946

Authors: H. Alkhatib, J. Duveau

Abstract:

Genetic algorithms (GAs) have been widely used for global optimization problems. The GA performance depends highly on the choice of the search space for each parameter to be optimized. Often, this choice is a problem-based experience. The search space being a set of potential solutions may contain the global optimum and/or other local optimums. A bad choice of this search space results in poor solutions. In this paper, our approach consists in extending the search space boundaries during the GA optimization, only when it is required. This leads to more diversification of GA population by new solutions that were not available with fixed search space boundaries. So, these dynamic search spaces can improve the GA optimization performances. The proposed approach is applied to power system stabilizer optimization for multimachine power system (16-generator and 68-bus). The obtained results are evaluated and compared with those obtained by ordinary GAs. Eigenvalue analysis and nonlinear system simulation results show the effectiveness of the proposed approach to damp out the electromechanical oscillation and enhance the global system stability.

Keywords: Genetic Algorithms, Multiobjective Optimization, Power System Stabilizer, Small Signal Stability.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1708

Authors: Abhijit Mitra

Abstract:

we propose a new normalized LMS (NLMS) algorithm, which gives satisfactory performance in certain applications in comaprison with con-ventional NLMS recursion. This new algorithm can be treated as a block based simplification of NLMS algorithm with significantly reduced number of multi¬ply and accumulate as well as division operations. It is also shown that such a recursion can be easily implemented in block floating point (BFP) arithmetic, treating the implementational issues much efficiently. In particular, the core challenges of a BFP realization to such adaptive filters are mainly considered in this regard. A global upper bound on the step size control parameter of the new algorithm due to BFP implementation is also proposed to prevent overflow in filtering as well as weight updating operations jointly.

Keywords: Adaptive algorithm, Block floating point arithmetic, Implementation issues, Normalized least mean square methods

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2345

Authors: Lina Yan, Jingjing Di, Ke Wang

Abstract:

A new basis function neural network algorithm is proposed for numerical integration. The main idea is to construct neural network model based on spline basis functions, which is used to approximate the integrand by training neural network weights. The convergence theorem of the neural network algorithm, the theorem for numerical integration and one corollary are presented and proved. The numerical examples, compared with other methods, show that the algorithm is effective and has the characteristics such as high precision and the integrand not required known. Thus, the algorithm presented in this paper can be widely applied in many engineering fields.

Keywords: Numerical integration, Spline basis function, Neural network algorithm

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2903

Authors: Babar S. Kawish, Baber Aslam, Shoab A Khan

Abstract:

In this paper we show that adjusting ART in accordance with static network scenario can substantially improve the performance of AODV by reducing control overheads. We explain the relationship of control overheads with network size and request patterns of the users. Through simulation we show that making ART proportionate to network static time reduces the amount of control overheads independent of network size and user request patterns.

Keywords: AODV, ART, MANET, Route Cache, TTL.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1723

Authors: Shin Je Lee, Go Bong Choi, Jeong Cheol Seo, Jong Min Lee, Gibaek Lee

Abstract:

Water pipe network is installed underground and once equipped, it is difficult to recognize the state of pipes when the leak or burst happens. Accordingly, post management is often delayed after the fault occurs. Therefore, the systematic fault management system of water pipe network is required to prevent the accident and minimize the loss. In this work, we develop online fault detection system of water pipe network using data of pipes such as flow rate or pressure. The transient model describing water flow in pipelines is presented and simulated using MATLAB. The fault situations such as the leak or burst can be also simulated and flow rate or pressure data when the fault happens are collected. Faults are detected using statistical methods of fast Fourier transform and discrete wavelet transform, and they are compared to find which method shows the better fault detection performance.

Keywords: fault detection, water pipeline model, fast Fourier transform, discrete wavelet transform.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2324

Authors: Sitthichon Kanitthakun, Pinit Kumhom, Kosin Chamnongthai

Abstract:

In quality control of freeze-dried durian, crispiness is a key quality index of the product. Generally, crispy testing has to be done by a destructive method. A nondestructive testing of the crispiness is required because the samples can be reused for other kinds of testing. This paper proposed a crispiness classification method of freeze-dried durians using fuzzy logic for decision making. The physical changes of a freeze-dried durian include the pores appearing in the images. Three physical features including (1) the diameters of pores, (2) the ratio of the pore area and the remaining area, and (3) the distribution of the pores are considered to contribute to the crispiness. The fuzzy logic is applied for making the decision. The experimental results comparing with food expert opinion showed that the accuracy of the proposed classification method is 83.33 percent.

Keywords: Durian, crispiness, freeze drying, pore, fuzzy logic.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1949

Authors: Sakshi Kausha, R.K Sharma

Abstract:

High speed networks provide realtime variable bit rate service with diversified traffic flow characteristics and quality requirements. The variable bit rate traffic has stringent delay and packet loss requirements. The burstiness of the correlated traffic makes dynamic buffer management highly desirable to satisfy the Quality of Service (QoS) requirements. This paper presents an algorithm for optimization of adaptive buffer allocation scheme for traffic based on loss of consecutive packets in data-stream and buffer occupancy level. Buffer is designed to allow the input traffic to be partitioned into different priority classes and based on the input traffic behavior it controls the threshold dynamically. This algorithm allows input packets to enter into buffer if its occupancy level is less than the threshold value for priority of that packet. The threshold is dynamically varied in runtime based on packet loss behavior. The simulation is run for two priority classes of the input traffic – realtime and non-realtime classes. The simulation results show that Adaptive Partial Buffer Sharing (ADPBS) has better performance than Static Partial Buffer Sharing (SPBS) and First In First Out (FIFO) queue under the same traffic conditions.

Keywords: Buffer Management, Consecutive packet loss, Quality-of-Service, Priority based packet discarding, partial buffersharing.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1618

Authors: Jirarat Teeravaraprug, Usawadee Inklay

Abstract:

This paper gave an attempt in prioritizing information  technologies that organizations should give concentration. The case  study was organizations in the automotive assembly industry in  Thailand. Data were first collected to gather all information  technologies known and used in the automotive assembly industry in  Thailand. Five experts from the industries were surveyed based on  the concept of fuzzy DEMATEL. The information technologies were  categorized into six groups, which were communication, transaction,  planning, organization management, warehouse management, and  transportation. The cause groups of information technologies for each  group were analyzed and presented. Moreover, the relationship  between the used and the significant information technologies was  given. Discussions based on the used information technologies and  the research results are given.

 

Keywords: Information technology, automotive assembly industry, fuzzy DEMATEL.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1699